Video length: 3:10:43
Transcript
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hey thanks i was just about to take it
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dave thank you so much steve for getting
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us set up with our housekeeping and
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thank you to everybody who's joining us
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today i have to say i guess both good
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morning and good afternoon depending on
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which post you're coming to us from my
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name is amy goldstein and i'm the
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prevention research branch chief at the
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national institute on drug abuse in our
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division of epidemiology services and
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prevention research and i'm pleased to
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welcome you all to this meeting um at
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nida and in the prevention research
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branch our goal is really to think about
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intervention development research that
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can be delivered in real world systems
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and settings so that there's a chance
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for long-term sustainability of
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interventions and we've been thinking a
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lot about the viability of identifying
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individuals at risk for substance use
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and delivering preventive interventions
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for substance use within primary care
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generally in pediatrics specifically and
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it's nearly impossible to think about
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that without talking about electronic
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health records and the role that they
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could play in either identifying
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individuals at risk or somehow
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delivering preventive intervention
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services so really the goal of this
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meeting today is to bring people
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together who are working either in
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substance use or in other fields of
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medicine and thinking about the ehr and
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its role in clinical research and to
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think about the potential for youth
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within substance use prevention research
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so i'm excited for the agenda that we've
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put together um for the talks that we're
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going to have today and with that i'll
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turn it over to united's deputy director
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dr wilson compton
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well thank you amy it's certainly a
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pleasure to be with you and with the
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group today
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you all will be wrestling with an
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important area for
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research and practice development and
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that's what we're talking about today is
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how can we use research at the boundary
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of practice and in this case how can we
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use electronic health records are these
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potentially very rich administrative
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sources of information to
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improve the quality of care and to
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improve the implementation of prevention
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interventions that can enhance the lives
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and well-being of broad swaths of our
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population across the united states
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now certainly a priority at nida is to
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develop and test novel substance use and
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prevention strategies
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and uh being able to do this in the
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settings while they will be delivered uh
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really can help us decrease the research
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to practice gap and so we're looking for
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ways to
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to
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develop research within uh primary care
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settings that'll be reflected in the
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electronic health record and that's what
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you all can give us ideas on how best to
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do this
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now one of the barriers to
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primary care based screening and
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prevention
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is that providers may not know how to
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screen for substance use risk they don't
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have time to do this work and it's not
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really clear how they're going to get
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reimbursed for work and after all that's
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going to be an essential component of
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seeing this
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these practices widely used is that
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there's adequate reimburse reimbursement
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but there's also another key issue which
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is
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if you identify a youth
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uh a child who's at risk or an
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adolescent who's using substances or has
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significant major issues related to
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their substance use what do you do about
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that how do you refer them and where do
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you send them
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treatment services and intervention
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services are not always available and so
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that's a key barrier as well
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now one consideration is that
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reimbursement
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is at least partly dependent on the u.s
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preventive services task force practices
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given an a or b grade are reimbursable
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and right now
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uspstf has recommended screening in
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primary care for adults with a b grade
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but the evidence has been insufficient
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to remain to recommend screening for
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youth i would also point out that even
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in the recommendation for adults it's
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for screening it does not include a
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recommendation around brief
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interventions and so it's mostly
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screening with the idea of linkage to
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services and linkage to treatment for
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those
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with a significant involvement with
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substances and problems related to their
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substances is is the recommendation
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so there's insufficient evidence to
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recommend brief counseling
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in primary care for children adolescents
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and young adults these are
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an irating the insufficient evidence now
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when there's an eye rating that means
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that research might help to inform that
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so
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this is one of the areas where
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we want your thoughts and your help
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research to address the usps tf evidence
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gaps um
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[Music]
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and to inform the implementation of
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evidence-based interventions really can
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involve the electronic health records
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both to identify
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places where this might be conducted and
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also to provide the source of outcomes
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or the source of information to
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determine the impact and effectiveness
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of any interventions
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i will point out that something that i
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know that uh uh dr goldstein and
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colleagues in our prevention research
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brands have emphasized over the last few
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years is the potential value in
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uh implementing what had been either
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school or universal based prevention
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interventions
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within primary care settings and so
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seeing how some of those could be
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incorporated into
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broad-based screening approaches and
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and approaches that include the uh
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electronic health record and these
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large-scale administrator data sets will
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be an exciting and important
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uh next key step
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now you all have a wonderful set of
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opportunities to provide
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guidance to us through round tables over
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the next few hours and i'm very pleased
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with
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and excited by the way uh dr goldstein
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and dr blanco and colleagues in our
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prevention research branch
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here at nida have organized this session
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now i do want to say that i'm speaking
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you today somewhat unexpectedly we
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really did think our our director dr
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nora volkov would be able to welcome you
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uh unfortunately nora had a a a
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emergency and so she asked me to
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substitute for her today and it
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certainly is my pleasure to help welcome
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you on behalf of the national institute
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on drug abuse on behalf of our entire
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team
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at nida we really value your time this
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afternoon or this morning if you're on
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the west coast
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uh and we look forward to your best
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ideas for how we can develop these
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really important areas for prevention
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research and intervention delivery and
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with that i believe i turn it back to
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amy and will you turn it back to be uh
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coordinating from here thanks for
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watching thank you
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great thanks wilson
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now i'd like to introduce for another uh
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opening remark dr carlos blanco who's
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the director of our division of
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epidemiology services and prevention
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research
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thank you i mean so um
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one of the advantages of working at
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naida is that we are pretty much
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aligning our thinking so i'm going to
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spare you repeating what amy and wilson
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have said
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but i cannot help
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but think that today is march 21st so
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it's the first day of spring
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and and i think it is really fitting
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that we are having this workshop today
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because spring at least for me
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is a time of hope and particularly today
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which is very sunny at least where i am
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which is new york city and so for me the
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the sun and the spring are
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really a source of hope
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and and by the same token prevention i
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mean i uh by training i'm mostly a
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treating practitioner but as you all
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know most people with substance use
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disorders never seek treatment so
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prevention for me
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is crucial unless
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unless we really step up our work on
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prevention we're never going to to solve
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the substance use
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crisis so i'm very grateful to to sarah
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steverman and to amy
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goldstein for working on this workshop
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as already amy and wilson have said one
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of our interest is how to use electronic
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health records and also how do we create
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evidence
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to really move some of the interventions
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to be grades a or b
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to the uspstf because one of the things
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that we want to do it's not just
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research that appears on journals but
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but research that can really be
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sustained as interventions so i'm going
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to to stop here i hope that
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that we will have a mixture in our
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audience and presenters of optimists and
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pessimists think optimists are very good
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because we really need hope
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but we also need people like me who
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always finds problems in everything that
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other people present so we can address
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those problems before we bring this to
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the field so i hope that there's a sort
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of debate between people being hopeful
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but also be people being critical and
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finding problems so that at the end we
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get the best product
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so amy and sarah thanks for organizing
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this i think this is i mean i always say
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i i i don't know why they pay me to do
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this job like i should pay to do this
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work no so this is for me better than
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going to the movies and i'm looking
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forward to what you have prepared for
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for us today so thank you
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great thank you carlos yeah i wonder if
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our agenda our meeting should be
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entitled like challenges and
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opportunities because i agree with you
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there's a lot of potential but there
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might also be some limitations to what
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we're going to talk about so just to
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orient everybody to how the afternoon or
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morning is going to be structured we
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have the time divided into three
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sessions so session one will be more of
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an overview of the potential uses
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challenges and opportunities for ehr
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data and primary care and pediatrics and
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our speakers are going to provide the
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perspectives of some of our key
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stakeholders so the uspsdf pediatric
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practices and health care systems
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and then our second session will be
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joined by four researchers who are
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working across different systems so
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mental health pediatrics substance use
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and veterans administration to learn
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about how they've used ehr data in their
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research and some of the challenges that
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they've encountered and lastly we'll
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hear about two knight-of-funded projects
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both of which are using ehr data either
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for risk prediction or to track outcomes
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in their research so in terms of how
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we've structured the time
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we'll take five-minute breaks between
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each sessions just to give people a
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stretch break and a little bit of screen
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break um and we'll do all the
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presentations in block and then have
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time for q a at the end so as we said in
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the beginning feel free to use the chat
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to put in questions and comments and
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we'll be tracking those as we go
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so with that i'm going to turn it over
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to sarah steverman who's a program
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officer in the prevention research
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branch and oversees our research on
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healthcare and healthcare systems and
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has really been the brains behind this
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operation in putting this meeting
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together and cultivating our speakers so
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sarah with that i'll turn it over to you
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great thanks amy
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um and thanks everybody for um
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for joining us i am gonna
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quickly move to our first session and
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introduce um introduce our speakers
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um as amy said this panel um we're gonna
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start to orient ourselves to
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um to to our um our challenges and our
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opportunities for using ehr
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data and research as well as an
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implementation so um the first speaker
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is um bob mcnellis
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he
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has newly joined us in nih's office of
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disease prevention as a senior advisor
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and there he leads the effort to
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identify prevention research areas for
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investment across nih
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and also serves as the nih
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liaison to the u.s preventive services
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task force and the community preventive
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services task force he's also the
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scientific advisor for the office of
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disease prevention pathways to
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prevention program
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and he recently came to nih from the
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agency for healthcare research and
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quality where he worked on a portfolio
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related to primary care research and
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also served as a medical officer for the
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uspstf
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and then after
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after bob we will turn to dr mario
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tehran a physician and clinical
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informaticist for the division of
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digital healthcare research in the
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center for evidence and practice
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improvement at hrq
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um dr tehran is
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has overseen the implementation of ehrs
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across multiple health systems and led
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efforts to improve physician ehr
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optimization and satisfaction
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and then finally we're going to
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move to dr brian jensen
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a physician researcher at
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chop at children's hospital of
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philadelphia
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and dr jensen is a faculty member at
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chop's policy lab an assistant professor
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in the department of pediatrics at
360
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university of pennsylvania and the
361
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medical director for value-based care
362
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for chops
363
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care network
364
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um
365
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he is a board-certified pediatrician and
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informaticist
367
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um and he's going to discuss
368
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his experience with optimizing ehr data
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and then their use by pediatricians and
370
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their health system
371
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so i am very thankful for for these um
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three experts for for you all joining us
373
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and at this point i'm going to turn over
374
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to bob we'll go
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um
376
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we'll go
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through our presentations and then we'll
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have time at the end for questions so
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please in the meantime as questions come
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up go ahead and put them in the chat and
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we'll start to compile them
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and then we'll get to the discussion at
383
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the end
384
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thank you
385
00:13:11,920 --> 00:13:15,519
great thank you sarah and good morning
386
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and good afternoon to all of you it's a
387
00:13:15,519 --> 00:13:19,440
pleasure to be here special thanks to dr
388
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goldstein and blanco and compton for
389
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inviting odp to participate uh in this
390
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session as sarah mentioned i'm bob
391
00:13:23,680 --> 00:13:27,600
mcnallis and i'm starting my sixth week
392
00:13:25,519 --> 00:13:30,320
at odp which officially means i know
393
00:13:27,600 --> 00:13:32,160
enough to be dangerous um but honestly i
394
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am really thrilled to be here today and
395
00:13:32,160 --> 00:13:37,519
while i'm new to odp um today's topic is
396
00:13:35,040 --> 00:13:39,600
not new to me um as sarah mentioned i
397
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came to odp from the agency of
398
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healthcare research and quality where i
399
00:13:40,800 --> 00:13:45,440
was senior advisor for primary care for
400
00:13:43,040 --> 00:13:47,680
the past 10 years and we led several dni
401
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initiatives that really relied on ehr
402
00:13:47,680 --> 00:13:50,959
data so this one is near and dear to me
403
00:13:49,680 --> 00:13:52,399
and then of course i did serve as a
404
00:13:50,959 --> 00:13:54,320
medical officer about five years for the
405
00:13:52,399 --> 00:13:55,680
us preventive services task force and
406
00:13:54,320 --> 00:13:58,720
today what i'm going to talk about just
407
00:13:55,680 --> 00:14:01,920
briefly is odp's role at nih as a
408
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liaison to the task force and share at a
409
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very high level um the task force's
410
00:14:04,240 --> 00:14:07,120
considerations for making
411
00:14:05,519 --> 00:14:10,560
recommendations on clinical preventive
412
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services um like screening for drug use
413
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i i can't speak to how the task force
414
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would view studies that use ehr data but
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i think understanding their process and
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00:14:16,959 --> 00:14:21,440
the rigor of their methods can really
417
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inform thinking uh on this approach
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00:14:21,440 --> 00:14:25,600
so first let me just start with odp i
419
00:14:23,360 --> 00:14:27,120
sort of nuts and bolts odps mission is
420
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to improve public health by increasing
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00:14:27,120 --> 00:14:31,199
the scope and quality the dissemination
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00:14:29,680 --> 00:14:33,600
impact of prevention research that's
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supported by nih we actually also work
424
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across all nih to help to coordinate and
425
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facilitate and make aware um uh research
426
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gaps for uh other institutes and centers
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to to include in their portfolios
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we sit in the office of the director at
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00:14:46,959 --> 00:14:50,880
nih uh within the division of program
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coordination planning and strategic
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00:14:50,880 --> 00:14:54,079
initiatives and actually it's nice
432
00:14:52,320 --> 00:14:56,240
because it gives us we don't not we're
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00:14:54,079 --> 00:14:58,160
agnostic around disorders and diseases
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00:14:56,240 --> 00:15:00,000
and conditions uh and gives us a little
435
00:14:58,160 --> 00:15:02,399
bit of credibility for working broadly
436
00:15:00,000 --> 00:15:04,560
across nih and with other agencies
437
00:15:02,399 --> 00:15:07,040
across hhs
438
00:15:04,560 --> 00:15:08,399
at odp we have uh some strategic
439
00:15:07,040 --> 00:15:10,320
priorities that we've been working on
440
00:15:08,399 --> 00:15:12,320
over the last several years and we've
441
00:15:10,320 --> 00:15:13,839
got six of them listed here we conduct
442
00:15:12,320 --> 00:15:16,639
portfolio analysis and impact
443
00:15:13,839 --> 00:15:19,120
assessments we look for research gaps uh
444
00:15:16,639 --> 00:15:20,880
work on prevention research methods uh
445
00:15:19,120 --> 00:15:23,360
promote collaborative prevention
446
00:15:20,880 --> 00:15:25,839
research and then we actually work to
447
00:15:23,360 --> 00:15:27,680
advance tobacco regulatory science and
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00:15:25,839 --> 00:15:30,320
communicate all of these things and just
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00:15:27,680 --> 00:15:32,560
recently uh within the past year we've
450
00:15:30,320 --> 00:15:34,240
added now a seventh strategic priority
451
00:15:32,560 --> 00:15:36,320
uh working on health disparities used to
452
00:15:34,240 --> 00:15:38,399
be a cross-cutting theme and now it's
453
00:15:36,320 --> 00:15:40,399
actually what a strategic priority in
454
00:15:38,399 --> 00:15:42,000
and of itself to promote and coordinate
455
00:15:40,399 --> 00:15:44,079
prevention research that addresses
456
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health disparities
457
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i work on team two i'm new the new team
458
00:15:46,240 --> 00:15:49,839
two lead uh and still working my way
459
00:15:48,560 --> 00:15:51,600
through this but you can see here's the
460
00:15:49,839 --> 00:15:54,079
strategic priority for team two and that
461
00:15:51,600 --> 00:15:56,160
is to identify prevention research areas
462
00:15:54,079 --> 00:15:57,839
for investment or expanded effort by the
463
00:15:56,160 --> 00:15:59,600
national institutes of health then we
464
00:15:57,839 --> 00:16:01,440
have these three objectives we work with
465
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a variety of stakeholders to identify
466
00:16:01,440 --> 00:16:04,639
needs and these stakeholders include
467
00:16:03,120 --> 00:16:06,480
people like the us preventive services
468
00:16:04,639 --> 00:16:08,240
task force the community preventive
469
00:16:06,480 --> 00:16:10,160
services task force which is located at
470
00:16:08,240 --> 00:16:12,480
the cdc and then the larger healthy
471
00:16:10,160 --> 00:16:14,880
people initiative that's across nih and
472
00:16:12,480 --> 00:16:17,600
actually across many government agencies
473
00:16:14,880 --> 00:16:18,959
and then we compare um
474
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prevention research with the current
475
00:16:18,959 --> 00:16:23,279
portfolio to identify some gaps and then
476
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we work across institutes and centers
477
00:16:23,279 --> 00:16:27,360
and other stakeholders to try to find
478
00:16:25,120 --> 00:16:29,040
ways to invest in filling some of those
479
00:16:27,360 --> 00:16:31,759
gaps
480
00:16:29,040 --> 00:16:33,279
specifically for today's talk what's i
481
00:16:31,759 --> 00:16:34,880
think most important is that we're the
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liaison office
483
00:16:34,880 --> 00:16:37,519
for the us preventive services task
484
00:16:36,320 --> 00:16:39,279
force and the community preventive
485
00:16:37,519 --> 00:16:40,959
services task force as we as we
486
00:16:39,279 --> 00:16:43,120
mentioned and we have some specific
487
00:16:40,959 --> 00:16:45,440
things that we do to address some of the
488
00:16:43,120 --> 00:16:48,639
research gaps um that come out of those
489
00:16:45,440 --> 00:16:51,040
task forces with nih's 27 institutes and
490
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centers to develop activities to address
491
00:16:51,040 --> 00:16:55,600
some of those gaps
492
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so i think i'll just pause and and now
493
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talk a little about the us preventive
494
00:16:56,959 --> 00:17:00,160
services task force and again i don't
495
00:16:58,800 --> 00:17:02,560
don't mean to speak for the task force
496
00:17:00,160 --> 00:17:04,240
but in our liaison role we are very much
497
00:17:02,560 --> 00:17:06,079
aware of what the task force does in
498
00:17:04,240 --> 00:17:07,760
their processes and i can reflect on my
499
00:17:06,079 --> 00:17:10,240
own previous experience as a medical
500
00:17:07,760 --> 00:17:11,919
officer to give you some authoritative
501
00:17:10,240 --> 00:17:14,319
information around this and and first
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it's to say that um the us preventive
503
00:17:14,319 --> 00:17:18,000
service test force is an independent
504
00:17:16,160 --> 00:17:20,079
volunteer panel of clinical and
505
00:17:18,000 --> 00:17:22,480
behavioral health experts and they have
506
00:17:20,079 --> 00:17:25,039
expertise in primary care in prevention
507
00:17:22,480 --> 00:17:27,600
research uh in in prevention research
508
00:17:25,039 --> 00:17:30,000
methodology uh and evidence-based
509
00:17:27,600 --> 00:17:32,000
medicine and so it's that about 16
510
00:17:30,000 --> 00:17:33,840
members who bring together a wide
511
00:17:32,000 --> 00:17:36,320
variety of skills
512
00:17:33,840 --> 00:17:38,000
to consider the evidence and make
513
00:17:36,320 --> 00:17:39,600
recommendations the agency for
514
00:17:38,000 --> 00:17:40,960
healthcare research and quality i'll
515
00:17:39,600 --> 00:17:43,039
hear from my colleague
516
00:17:40,960 --> 00:17:44,400
at arc in a moment provides scientific
517
00:17:43,039 --> 00:17:46,559
technical administration and
518
00:17:44,400 --> 00:17:49,280
dissemination support it is although the
519
00:17:46,559 --> 00:17:52,559
us pstf is not a federal agency it is
520
00:17:49,280 --> 00:17:54,880
supported by ahrq and the task force as
521
00:17:52,559 --> 00:17:56,960
you know and dr compton mentioned issues
522
00:17:54,880 --> 00:17:59,600
recommendations about preventive
523
00:17:56,960 --> 00:18:02,080
services in primary care that can be
524
00:17:59,600 --> 00:18:05,360
generalized to a primary care population
525
00:18:02,080 --> 00:18:07,520
who don't generally have symptoms
526
00:18:05,360 --> 00:18:09,679
of care so it's got to be a broad group
527
00:18:07,520 --> 00:18:12,240
who are not selected usually for these
528
00:18:09,679 --> 00:18:15,039
services based on symptomatology or
529
00:18:12,240 --> 00:18:16,880
previous diseases
530
00:18:15,039 --> 00:18:18,320
uh the task force's visibility went up
531
00:18:16,880 --> 00:18:20,240
quite a lot with the passage of the
532
00:18:18,320 --> 00:18:22,160
affordable care act um and that the
533
00:18:20,240 --> 00:18:23,919
affordable care act mandates coverage of
534
00:18:22,160 --> 00:18:26,000
grade a and b services without cost
535
00:18:23,919 --> 00:18:27,360
sharing that definitely
536
00:18:26,000 --> 00:18:28,960
increased the pressure i think on the
537
00:18:27,360 --> 00:18:30,240
task force around a and b
538
00:18:28,960 --> 00:18:32,320
recommendations
539
00:18:30,240 --> 00:18:33,840
um because there are lots of people who
540
00:18:32,320 --> 00:18:35,600
are interested in having those services
541
00:18:33,840 --> 00:18:37,440
paid for
542
00:18:35,600 --> 00:18:40,400
however as you can see the list of
543
00:18:37,440 --> 00:18:43,919
uspstf recommendation grades those are a
544
00:18:40,400 --> 00:18:47,440
b c d and i um specifically i think
545
00:18:43,919 --> 00:18:49,760
we're focused today on i statements and
546
00:18:47,440 --> 00:18:51,360
mostly the task force looks at um
547
00:18:49,760 --> 00:18:53,440
evidence and then comes to two
548
00:18:51,360 --> 00:18:55,840
considerations and one is about the
549
00:18:53,440 --> 00:18:57,679
magnitude of net benefit for for
550
00:18:55,840 --> 00:19:00,880
delivering a particular service and then
551
00:18:57,679 --> 00:19:02,960
the certainty around that benefit um
552
00:19:00,880 --> 00:19:05,039
mostly based on the quality of evidence
553
00:19:02,960 --> 00:19:06,640
itself and if there's high certainty
554
00:19:05,039 --> 00:19:07,919
that there's a substantial net benefit
555
00:19:06,640 --> 00:19:10,080
then they'll give a service in a
556
00:19:07,919 --> 00:19:12,640
recommendation if there's high certainty
557
00:19:10,080 --> 00:19:14,000
that the net benefit is moderate or or
558
00:19:12,640 --> 00:19:16,880
on the other hand it's only moderate
559
00:19:14,000 --> 00:19:18,640
certainty about a significant
560
00:19:16,880 --> 00:19:20,480
benefit significant net benefit then
561
00:19:18,640 --> 00:19:22,480
they'll give it a b recommendation when
562
00:19:20,480 --> 00:19:24,960
the balance is tricky about the net
563
00:19:22,480 --> 00:19:27,120
benefit um uh or either around certainty
564
00:19:24,960 --> 00:19:28,880
and that magnitude then then really a c
565
00:19:27,120 --> 00:19:30,799
recommendation and that really focuses
566
00:19:28,880 --> 00:19:32,240
on discussions between patients and
567
00:19:30,799 --> 00:19:34,160
their clinicians about whether that
568
00:19:32,240 --> 00:19:36,880
service is right for them and then there
569
00:19:34,160 --> 00:19:38,559
are um services that are are can be
570
00:19:36,880 --> 00:19:40,080
harmful or at least have no benefit at
571
00:19:38,559 --> 00:19:41,760
all and those are typically given a d
572
00:19:40,080 --> 00:19:43,600
recommendation and then as we mentioned
573
00:19:41,760 --> 00:19:45,520
the eye is issued when evidence is
574
00:19:43,600 --> 00:19:47,120
insufficient to balance those benefits
575
00:19:45,520 --> 00:19:48,240
and harms or there's a great deal of
576
00:19:47,120 --> 00:19:50,000
uncertainty
577
00:19:48,240 --> 00:19:51,760
and we've figured that nih is well
578
00:19:50,000 --> 00:19:53,440
positioned to support research needed to
579
00:19:51,760 --> 00:19:54,960
close some of those evidence gaps around
580
00:19:53,440 --> 00:19:56,880
i statements especially if they're in
581
00:19:54,960 --> 00:19:59,200
line with some of the missions of the
582
00:19:56,880 --> 00:20:00,960
institutes and centers
583
00:19:59,200 --> 00:20:03,039
there is a long process that the task
584
00:20:00,960 --> 00:20:05,200
force goes through starting from topic
585
00:20:03,039 --> 00:20:08,080
nominations all the way to their final
586
00:20:05,200 --> 00:20:09,440
recommendation um statements and then
587
00:20:08,080 --> 00:20:11,039
they have several opportunities for
588
00:20:09,440 --> 00:20:13,039
public comment along the way first they
589
00:20:11,039 --> 00:20:14,799
begin with topic nominations and in
590
00:20:13,039 --> 00:20:16,400
addition to adding in new topics they're
591
00:20:14,799 --> 00:20:18,159
always reconsidering topics that they've
592
00:20:16,400 --> 00:20:20,799
had from the past to try to keep them
593
00:20:18,159 --> 00:20:22,000
updated every five years once they've
594
00:20:20,799 --> 00:20:23,840
identified the topic that they're going
595
00:20:22,000 --> 00:20:25,280
to work on to begin to develop a draft
596
00:20:23,840 --> 00:20:27,200
research plan and that draft research
597
00:20:25,280 --> 00:20:28,960
plan is usually based on a peacock's
598
00:20:27,200 --> 00:20:32,000
kind of framework that looks at the
599
00:20:28,960 --> 00:20:34,960
patient population uh interventions uh
600
00:20:32,000 --> 00:20:38,320
looks at various types of treatments as
601
00:20:34,960 --> 00:20:40,880
well as um uh timing of those services
602
00:20:38,320 --> 00:20:42,480
um and uh and and then the settings that
603
00:20:40,880 --> 00:20:44,080
those are in and
604
00:20:42,480 --> 00:20:46,400
as well as the comparisons for many of
605
00:20:44,080 --> 00:20:48,640
those things and that the that work is
606
00:20:46,400 --> 00:20:50,960
done by an evidence-based practice
607
00:20:48,640 --> 00:20:53,039
center or epc so if we talk about epc
608
00:20:50,960 --> 00:20:54,880
reports they're the ones who synthesize
609
00:20:53,039 --> 00:20:56,799
the evidence across things and actually
610
00:20:54,880 --> 00:20:58,159
they help develop that research plan
611
00:20:56,799 --> 00:21:00,640
that research plan has an opportunity
612
00:20:58,159 --> 00:21:02,240
for public comment and and then it gets
613
00:21:00,640 --> 00:21:04,400
finalized and then based on that
614
00:21:02,240 --> 00:21:06,960
research plan the task force will begin
615
00:21:04,400 --> 00:21:08,640
an evidence review that when will lead
616
00:21:06,960 --> 00:21:10,480
to development of their final
617
00:21:08,640 --> 00:21:11,760
recommendation with an opportunity for
618
00:21:10,480 --> 00:21:13,440
public comment for that draft
619
00:21:11,760 --> 00:21:15,039
recommendation and the evidence report
620
00:21:13,440 --> 00:21:16,799
in between
621
00:21:15,039 --> 00:21:18,640
here's just a standard template the task
622
00:21:16,799 --> 00:21:21,200
force uses an analytic framework to do
623
00:21:18,640 --> 00:21:23,120
this work um uh and and this is a
624
00:21:21,200 --> 00:21:24,480
screening one so it may not apply to
625
00:21:23,120 --> 00:21:26,240
behavioral counseling interventions
626
00:21:24,480 --> 00:21:28,640
where there's a slightly different uh
627
00:21:26,240 --> 00:21:30,240
framework as well as for preventive
628
00:21:28,640 --> 00:21:31,840
medications also a slightly different
629
00:21:30,240 --> 00:21:33,520
framework but
630
00:21:31,840 --> 00:21:35,039
as you can see there's linkages of
631
00:21:33,520 --> 00:21:37,679
evidence across the way here and it's
632
00:21:35,039 --> 00:21:40,000
pretty rare that you get an overarching
633
00:21:37,679 --> 00:21:42,000
um pathway from say for screening for
634
00:21:40,000 --> 00:21:43,760
instance all the way to outcomes in one
635
00:21:42,000 --> 00:21:45,679
study typically what you do have to have
636
00:21:43,760 --> 00:21:47,280
to build a chain of evidence over time
637
00:21:45,679 --> 00:21:49,200
to connect screening with early
638
00:21:47,280 --> 00:21:50,640
detection then with treatment with
639
00:21:49,200 --> 00:21:52,559
potentially intermediate outcomes and
640
00:21:50,640 --> 00:21:53,679
then at least have a sense for um how
641
00:21:52,559 --> 00:21:55,440
those intermediate outcomes are
642
00:21:53,679 --> 00:21:57,840
associated with final outcomes around
643
00:21:55,440 --> 00:21:59,200
morbidity and mortality they also look
644
00:21:57,840 --> 00:22:01,840
carefully first
645
00:21:59,200 --> 00:22:03,919
side effects adverse effects either from
646
00:22:01,840 --> 00:22:05,039
screening or treatment or counseling as
647
00:22:03,919 --> 00:22:07,919
it might be
648
00:22:05,039 --> 00:22:09,520
and then evaluate all of this into their
649
00:22:07,919 --> 00:22:12,640
chain of evidence and look for the
650
00:22:09,520 --> 00:22:14,640
coherence across all of these linkages
651
00:22:12,640 --> 00:22:15,840
in their chain of evidence
652
00:22:14,640 --> 00:22:18,080
as they look at the evidence they
653
00:22:15,840 --> 00:22:20,880
actually look very carefully at these
654
00:22:18,080 --> 00:22:22,559
six principles um these questions are
655
00:22:20,880 --> 00:22:24,000
are critical to the way
656
00:22:22,559 --> 00:22:26,559
the task force thinks about it hence the
657
00:22:24,000 --> 00:22:28,080
name critical appraisal questions
658
00:22:26,559 --> 00:22:29,919
first do the studies have appropriate
659
00:22:28,080 --> 00:22:31,600
research designed to answer those key
660
00:22:29,919 --> 00:22:33,600
questions to what extent are the
661
00:22:31,600 --> 00:22:35,360
existing studies of sufficient qualities
662
00:22:33,600 --> 00:22:37,440
but looking specifically for example at
663
00:22:35,360 --> 00:22:38,559
their internal validity to what extent
664
00:22:37,440 --> 00:22:40,880
are the results of the studies
665
00:22:38,559 --> 00:22:43,039
generalizable again to the u.s primary
666
00:22:40,880 --> 00:22:44,799
care population of interest for the
667
00:22:43,039 --> 00:22:46,080
intervention in the particular setting
668
00:22:44,799 --> 00:22:47,760
or situation
669
00:22:46,080 --> 00:22:49,360
how many and how large are the studies
670
00:22:47,760 --> 00:22:51,440
that address these questions how
671
00:22:49,360 --> 00:22:53,679
consistent are the results and are there
672
00:22:51,440 --> 00:22:55,440
additional factors that i'll assist the
673
00:22:53,679 --> 00:22:58,080
task force in drawing conclusions so for
674
00:22:55,440 --> 00:22:59,360
example a biologic model and then across
675
00:22:58,080 --> 00:23:01,039
all of these critical appraisal
676
00:22:59,360 --> 00:23:03,120
questions they look at each individual
677
00:23:01,039 --> 00:23:05,280
key question in that analytic framework
678
00:23:03,120 --> 00:23:07,520
and then look for coherence about how it
679
00:23:05,280 --> 00:23:10,480
all hangs together is there consistency
680
00:23:07,520 --> 00:23:11,919
across those key questions
681
00:23:10,480 --> 00:23:13,360
in addition to
682
00:23:11,919 --> 00:23:16,000
those critical appraisal questions they
683
00:23:13,360 --> 00:23:17,280
also look very closely at applicability
684
00:23:16,000 --> 00:23:19,840
and that's the extent to which the
685
00:23:17,280 --> 00:23:22,720
results are generalizable to the general
686
00:23:19,840 --> 00:23:24,640
asymptomatic primary care population or
687
00:23:22,720 --> 00:23:26,640
a specific primary care population of
688
00:23:24,640 --> 00:23:28,559
interest and frequently studies evaluate
689
00:23:26,640 --> 00:23:30,720
different populations or providers or
690
00:23:28,559 --> 00:23:32,240
settings than the asymptomatic primary
691
00:23:30,720 --> 00:23:34,159
care population and that's where
692
00:23:32,240 --> 00:23:36,640
challenges can come in and create some
693
00:23:34,159 --> 00:23:38,960
of those evidence gaps so specifically
694
00:23:36,640 --> 00:23:40,240
looking at u.s populations and then when
695
00:23:38,960 --> 00:23:42,159
you're looking at interventions the
696
00:23:40,240 --> 00:23:44,640
acceptability and feasibility and the
697
00:23:42,159 --> 00:23:47,120
availability of those interventions
698
00:23:44,640 --> 00:23:49,120
in primary care and the task force has
699
00:23:47,120 --> 00:23:50,799
done an amazing job so documenting their
700
00:23:49,120 --> 00:23:52,880
processes you can find them all if you
701
00:23:50,799 --> 00:23:53,919
go to their website u.s preventive
702
00:23:52,880 --> 00:23:55,520
services
703
00:23:53,919 --> 00:23:58,159
taskforce.org
704
00:23:55,520 --> 00:24:00,240
you can find their um their methods
705
00:23:58,159 --> 00:24:02,400
manual and uh and lots of great
706
00:24:00,240 --> 00:24:04,960
information there about how
707
00:24:02,400 --> 00:24:06,640
the process works for them
708
00:24:04,960 --> 00:24:08,240
so from our perspective in the office of
709
00:24:06,640 --> 00:24:10,000
disease prevention we collaborate with
710
00:24:08,240 --> 00:24:11,919
art very closely and really trying to
711
00:24:10,000 --> 00:24:13,440
disseminate some of these evidence gaps
712
00:24:11,919 --> 00:24:15,760
in clinical prevention and you can find
713
00:24:13,440 --> 00:24:17,200
those evidence gaps in several places
714
00:24:15,760 --> 00:24:18,960
through the task force's work you can
715
00:24:17,200 --> 00:24:20,720
find them in the evidence reports that
716
00:24:18,960 --> 00:24:22,880
are generated by arc
717
00:24:20,720 --> 00:24:24,640
and in the epcs you can find those
718
00:24:22,880 --> 00:24:26,320
evidence gaps in the recommendation
719
00:24:24,640 --> 00:24:29,520
statements themselves in the research
720
00:24:26,320 --> 00:24:31,440
needs and gaps section um they also the
721
00:24:29,520 --> 00:24:33,360
task force produces an annual report to
722
00:24:31,440 --> 00:24:35,840
congress and it highlights many of the
723
00:24:33,360 --> 00:24:37,600
high priority research gaps there
724
00:24:35,840 --> 00:24:39,279
we at our website at odp we have a
725
00:24:37,600 --> 00:24:41,039
complete listing of all the i statements
726
00:24:39,279 --> 00:24:42,559
in their course to finding research
727
00:24:41,039 --> 00:24:44,520
needs and gaps
728
00:24:42,559 --> 00:24:46,320
and you can find it at
729
00:24:44,520 --> 00:24:48,799
prevention.nih.gov and just look for the
730
00:24:46,320 --> 00:24:51,039
research priorities link there
731
00:24:48,799 --> 00:24:53,600
in addition we take those i statements
732
00:24:51,039 --> 00:24:55,200
and those needs and gaps and then we we
733
00:24:53,600 --> 00:24:57,440
communicate them with all the nih
734
00:24:55,200 --> 00:25:00,240
institutes and centers through an annual
735
00:24:57,440 --> 00:25:02,080
um uh i statement reporting survey uh
736
00:25:00,240 --> 00:25:04,400
around april of every year we send out
737
00:25:02,080 --> 00:25:07,360
that survey to all the ics with some
738
00:25:04,400 --> 00:25:09,760
pre-populated um i statements that are
739
00:25:07,360 --> 00:25:11,440
relevant to their work their mission and
740
00:25:09,760 --> 00:25:14,880
try to understand what's being done in
741
00:25:11,440 --> 00:25:16,559
terms of grants uh foas contracts and
742
00:25:14,880 --> 00:25:18,480
other types of research or research
743
00:25:16,559 --> 00:25:19,679
activities that could inform some of
744
00:25:18,480 --> 00:25:22,000
those gaps
745
00:25:19,679 --> 00:25:26,400
and then our office along with arc often
746
00:25:22,000 --> 00:25:26,400
convened meetings around those nih uh
747
00:25:26,720 --> 00:25:30,880
some of that nih work um and to present
748
00:25:28,960 --> 00:25:32,720
some of those evidence gaps at national
749
00:25:30,880 --> 00:25:34,640
meetings and we're specifically
750
00:25:32,720 --> 00:25:36,320
interested in in new and innovative
751
00:25:34,640 --> 00:25:38,000
research
752
00:25:36,320 --> 00:25:40,960
and as dr compton mentioned he
753
00:25:38,000 --> 00:25:42,960
highlighted the um b and i statements
754
00:25:40,960 --> 00:25:44,720
around screening for drug use there's
755
00:25:42,960 --> 00:25:46,960
also an eye statement around primary
756
00:25:44,720 --> 00:25:48,320
care space interventions in children
757
00:25:46,960 --> 00:25:50,559
adolescents and young adults this is
758
00:25:48,320 --> 00:25:52,320
just an example of what the i statement
759
00:25:50,559 --> 00:25:54,320
looks like and i won't read it to you
760
00:25:52,320 --> 00:25:56,400
but you can get a sense for for how
761
00:25:54,320 --> 00:25:58,799
detailed it is around the populations
762
00:25:56,400 --> 00:26:01,279
the balance of benefits and harms
763
00:25:58,799 --> 00:26:03,440
and what even some when the potential
764
00:26:01,279 --> 00:26:04,559
interventions are and then here the list
765
00:26:03,440 --> 00:26:06,240
of research
766
00:26:04,559 --> 00:26:07,279
needs and gaps that came out of it you
767
00:26:06,240 --> 00:26:09,279
can see they're they're fairly
768
00:26:07,279 --> 00:26:10,960
substantial and some can be more
769
00:26:09,279 --> 00:26:12,400
specific than others
770
00:26:10,960 --> 00:26:14,240
around cannabis prevention or
771
00:26:12,400 --> 00:26:16,880
standardizing outcome measurement
772
00:26:14,240 --> 00:26:18,559
looking for replication um other types
773
00:26:16,880 --> 00:26:19,600
of things as well as other evidence
774
00:26:18,559 --> 00:26:22,840
around
775
00:26:19,600 --> 00:26:26,000
prevention i think in technology-based
776
00:26:22,840 --> 00:26:28,080
interventions so it's it's wise that you
777
00:26:26,000 --> 00:26:29,279
uh re re-title the session to some
778
00:26:28,080 --> 00:26:30,480
degree challenges and opportunities
779
00:26:29,279 --> 00:26:31,919
because that's exactly where they lie
780
00:26:30,480 --> 00:26:33,360
here with the task force and some of
781
00:26:31,919 --> 00:26:34,799
these challenges or the evidence gaps
782
00:26:33,360 --> 00:26:36,320
are often described in multiple places
783
00:26:34,799 --> 00:26:37,760
either in the epc report or in the
784
00:26:36,320 --> 00:26:39,360
recommendation statement some of the
785
00:26:37,760 --> 00:26:41,360
descriptions are non-specific so it's
786
00:26:39,360 --> 00:26:43,279
hard to know what what types of high
787
00:26:41,360 --> 00:26:44,720
quality studies which would we need but
788
00:26:43,279 --> 00:26:46,799
there's some real opportunities here for
789
00:26:44,720 --> 00:26:48,640
linking some of these gaps um to the
790
00:26:46,799 --> 00:26:50,799
task force criteria for study inclusion
791
00:26:48,640 --> 00:26:51,600
to sort of create a more coordinated
792
00:26:50,799 --> 00:26:53,679
effort
793
00:26:51,600 --> 00:26:55,360
to describe and communicate some of
794
00:26:53,679 --> 00:26:57,120
those evidence gaps with the ultimate
795
00:26:55,360 --> 00:26:59,520
goal of really reducing the number of i
796
00:26:57,120 --> 00:27:01,600
statements improving the certainty
797
00:26:59,520 --> 00:27:03,520
that clinicians have in delivering care
798
00:27:01,600 --> 00:27:06,080
and really i think nih has a critical
799
00:27:03,520 --> 00:27:07,840
role in disseminating and addressing
800
00:27:06,080 --> 00:27:10,640
those evidence gaps and while this
801
00:27:07,840 --> 00:27:12,720
doesn't speak to uh i haven't spoken to
802
00:27:10,640 --> 00:27:15,279
elect use of electronic health records
803
00:27:12,720 --> 00:27:17,200
you do get a sense of if you had a study
804
00:27:15,279 --> 00:27:19,440
where electronic health record data was
805
00:27:17,200 --> 00:27:21,120
included it would still have to be held
806
00:27:19,440 --> 00:27:23,600
to sort of a very similar standard as
807
00:27:21,120 --> 00:27:26,880
the task force worked through their um
808
00:27:23,600 --> 00:27:28,640
uh reports uh through the epc to base
809
00:27:26,880 --> 00:27:30,080
their recommendation statements so with
810
00:27:28,640 --> 00:27:32,159
that i'll just leave you with my contact
811
00:27:30,080 --> 00:27:33,919
information and i'm gonna stop sharing
812
00:27:32,159 --> 00:27:35,440
and uh thanks for the time and look
813
00:27:33,919 --> 00:27:38,399
forward to the um
814
00:27:35,440 --> 00:27:40,240
uh the conversation
815
00:27:38,399 --> 00:27:41,919
uh but um
816
00:27:40,240 --> 00:27:43,919
my name is mario turon
817
00:27:41,919 --> 00:27:48,240
i am a medical officer at physician
818
00:27:43,919 --> 00:27:50,080
informaticis uh within arc at uh within
819
00:27:48,240 --> 00:27:51,440
the division of healthcare
820
00:27:50,080 --> 00:27:53,120
research
821
00:27:51,440 --> 00:27:55,200
within the center for evidence and
822
00:27:53,120 --> 00:27:56,080
practice improvement and all that outfit
823
00:27:55,200 --> 00:27:58,080
sue
824
00:27:56,080 --> 00:28:03,000
and i'm going to take uh somewhat of a
825
00:27:58,080 --> 00:28:03,000
step back and share with you
826
00:28:03,919 --> 00:28:09,520
a greater view and sense of efforts to
827
00:28:05,919 --> 00:28:12,240
enhance ehr-based clinical decision
828
00:28:09,520 --> 00:28:14,960
support interventions to improve
829
00:28:12,240 --> 00:28:17,840
substance abuse prevention
830
00:28:14,960 --> 00:28:17,840
i have no
831
00:28:18,240 --> 00:28:24,240
uh relevant uh disclosures
832
00:28:21,039 --> 00:28:24,240
you can go to the next slide
833
00:28:24,720 --> 00:28:29,200
so our background within the division of
834
00:28:26,799 --> 00:28:32,080
healthcare research our mission is to
835
00:28:29,200 --> 00:28:33,520
determine how the various components of
836
00:28:32,080 --> 00:28:35,840
ever evolving digital healthcare
837
00:28:33,520 --> 00:28:38,000
ecosystem can best come together to
838
00:28:35,840 --> 00:28:39,600
positively affect healthcare delivery
839
00:28:38,000 --> 00:28:40,799
and create value for patients and their
840
00:28:39,600 --> 00:28:42,960
families
841
00:28:40,799 --> 00:28:44,559
our vision is that every patient and
842
00:28:42,960 --> 00:28:47,120
care team
843
00:28:44,559 --> 00:28:48,640
will have ready access to all applicable
844
00:28:47,120 --> 00:28:51,279
data and knowledge
845
00:28:48,640 --> 00:28:53,600
mediated by advanced analytics and
846
00:28:51,279 --> 00:28:57,039
understandable visualizations to address
847
00:28:53,600 --> 00:28:59,120
a patient's health and health care
848
00:28:57,039 --> 00:29:01,600
we are after the ultimate data
849
00:28:59,120 --> 00:29:03,679
and knowledge liquid liquidity
850
00:29:01,600 --> 00:29:04,880
uh at the point of care and it's this
851
00:29:03,679 --> 00:29:07,679
last point
852
00:29:04,880 --> 00:29:09,760
uh of focus and one of the ways we are
853
00:29:07,679 --> 00:29:12,320
trying to achieve this point of focus is
854
00:29:09,760 --> 00:29:15,120
through clinical decision support i can
855
00:29:12,320 --> 00:29:15,120
go to the next slide
856
00:29:18,880 --> 00:29:21,840
so
857
00:29:19,679 --> 00:29:23,440
what is clinical decision support and to
858
00:29:21,840 --> 00:29:24,559
give you a brief overview and a broad
859
00:29:23,440 --> 00:29:26,640
view is
860
00:29:24,559 --> 00:29:28,880
based on what we know as uh the five
861
00:29:26,640 --> 00:29:31,039
rights that clinical decision support or
862
00:29:28,880 --> 00:29:33,200
cds should deliver the right information
863
00:29:31,039 --> 00:29:36,000
to the right people in the right formats
864
00:29:33,200 --> 00:29:38,640
the right channels at the right times
865
00:29:36,000 --> 00:29:41,120
although it's commonly associated
866
00:29:38,640 --> 00:29:45,039
i'll make clear cds is not
867
00:29:41,120 --> 00:29:46,799
just alerts or on-screen pop-ups
868
00:29:45,039 --> 00:29:48,880
nor is it only for
869
00:29:46,799 --> 00:29:50,040
physicians or those at the
870
00:29:48,880 --> 00:29:51,279
point of care making
871
00:29:50,040 --> 00:29:53,440
[Music]
872
00:29:51,279 --> 00:29:55,360
health care decisions
873
00:29:53,440 --> 00:29:57,520
clinical decision support is a process
874
00:29:55,360 --> 00:30:00,159
in a set of tools that are technology
875
00:29:57,520 --> 00:30:03,039
enabled but in the end can support a
876
00:30:00,159 --> 00:30:05,919
person's capacities and hopefully
877
00:30:03,039 --> 00:30:08,880
improve the quality of care
878
00:30:05,919 --> 00:30:12,000
next slide
879
00:30:08,880 --> 00:30:13,600
our ongoing initiative since 2016 aims
880
00:30:12,000 --> 00:30:16,320
at getting the evidence and support and
881
00:30:13,600 --> 00:30:18,399
practice to both patients and clinicians
882
00:30:16,320 --> 00:30:20,559
through clinical decision support that
883
00:30:18,399 --> 00:30:23,120
is more shareable standards based and
884
00:30:20,559 --> 00:30:24,720
publicly available i'll go over some of
885
00:30:23,120 --> 00:30:27,039
our efforts and how
886
00:30:24,720 --> 00:30:28,320
cds and the ehr can be leveraged and
887
00:30:27,039 --> 00:30:31,279
utilized
888
00:30:28,320 --> 00:30:33,600
for substance abuse prevention
889
00:30:31,279 --> 00:30:36,159
next slide
890
00:30:33,600 --> 00:30:38,559
so due to its high penetration most but
891
00:30:36,159 --> 00:30:41,600
not all clinical settings the ehr can be
892
00:30:38,559 --> 00:30:43,840
viewed as an avenue to get cds into the
893
00:30:41,600 --> 00:30:46,240
hands of those that need it most
894
00:30:43,840 --> 00:30:48,559
this figure helps illustrate an overview
895
00:30:46,240 --> 00:30:50,399
of the cds ehr ecosystem and the
896
00:30:48,559 --> 00:30:52,559
interplay where we can see the flow of
897
00:30:50,399 --> 00:30:54,960
evidence data and knowledge and their
898
00:30:52,559 --> 00:30:56,799
sources into cds and eventually into the
899
00:30:54,960 --> 00:30:58,720
ehr
900
00:30:56,799 --> 00:31:00,640
it emphasizes the multiple channels that
901
00:30:58,720 --> 00:31:02,880
are needed to be connected not only to
902
00:31:00,640 --> 00:31:06,640
get cds into the ehr but to make sure
903
00:31:02,880 --> 00:31:08,559
that cds is relevant and trustworthy
904
00:31:06,640 --> 00:31:11,039
however due to these multiple channels
905
00:31:08,559 --> 00:31:13,840
and sources of information evidence
906
00:31:11,039 --> 00:31:16,399
exchange between them can be complex and
907
00:31:13,840 --> 00:31:16,399
difficult
908
00:31:16,480 --> 00:31:20,159
efforts
909
00:31:18,080 --> 00:31:21,200
efforts to create cds are sometimes
910
00:31:20,159 --> 00:31:23,600
siloed
911
00:31:21,200 --> 00:31:26,480
as we can see with these uh
912
00:31:23,600 --> 00:31:29,039
somewhat clinical silos at the bottom
913
00:31:26,480 --> 00:31:31,519
and only compatible for those who create
914
00:31:29,039 --> 00:31:34,159
it leading to duplicate efforts because
915
00:31:31,519 --> 00:31:35,919
of an inability to share
916
00:31:34,159 --> 00:31:37,679
cds efficiently
917
00:31:35,919 --> 00:31:41,279
so to combat these
918
00:31:37,679 --> 00:31:43,840
duplicative efforts and promote uh
919
00:31:41,279 --> 00:31:45,039
free exchange interoperability standards
920
00:31:43,840 --> 00:31:47,440
have
921
00:31:45,039 --> 00:31:50,399
are being promoted and have been created
922
00:31:47,440 --> 00:31:52,880
however they're not yet widespread
923
00:31:50,399 --> 00:31:54,720
amongst all the hr vendors and
924
00:31:52,880 --> 00:31:56,399
organizations
925
00:31:54,720 --> 00:31:59,760
uh the main exchange standard you should
926
00:31:56,399 --> 00:32:01,840
be aware of uh if not already is the
927
00:31:59,760 --> 00:32:04,399
fast healthcare intraoperatively
928
00:32:01,840 --> 00:32:06,000
resources standard also known as fire
929
00:32:04,399 --> 00:32:08,720
it is a standard for exchanging health
930
00:32:06,000 --> 00:32:10,880
information electronically and specifies
931
00:32:08,720 --> 00:32:12,880
the content of the data exchange between
932
00:32:10,880 --> 00:32:14,640
health care applications and how the
933
00:32:12,880 --> 00:32:17,360
exchange is implemented
934
00:32:14,640 --> 00:32:19,600
and managed i won't go into detail on uh
935
00:32:17,360 --> 00:32:22,159
the background of this but just to make
936
00:32:19,600 --> 00:32:24,399
those in the audience aware that
937
00:32:22,159 --> 00:32:26,320
when implementing clinical decision
938
00:32:24,399 --> 00:32:28,559
report into the ehr
939
00:32:26,320 --> 00:32:30,640
we're trying to move our efforts uh to
940
00:32:28,559 --> 00:32:33,360
include these standards to make them ehr
941
00:32:30,640 --> 00:32:36,080
agnostic and available to everyone
942
00:32:33,360 --> 00:32:36,080
uh next slide
943
00:32:37,200 --> 00:32:40,480
and um
944
00:32:38,640 --> 00:32:42,799
so these standards and their promotion
945
00:32:40,480 --> 00:32:44,720
and use are critical in our work
946
00:32:42,799 --> 00:32:46,720
surrounding cds and believe it is an
947
00:32:44,720 --> 00:32:49,519
important component in the cds
948
00:32:46,720 --> 00:32:51,760
ecosystem so to support these efforts in
949
00:32:49,519 --> 00:32:54,720
partnership with the mitre corporation
950
00:32:51,760 --> 00:32:57,840
we have created cds connect
951
00:32:54,720 --> 00:32:57,840
go to the next slide
952
00:32:59,279 --> 00:33:04,640
so this is a publicly available and free
953
00:33:02,000 --> 00:33:07,039
open source tool that not only is a
954
00:33:04,640 --> 00:33:10,399
repository for clinical decision support
955
00:33:07,039 --> 00:33:13,039
tools but also is an authoring tool to
956
00:33:10,399 --> 00:33:14,000
allow the creation of clinical decision
957
00:33:13,039 --> 00:33:16,080
support
958
00:33:14,000 --> 00:33:18,000
using interoperable standards it also
959
00:33:16,080 --> 00:33:20,720
has the capabilities to test your
960
00:33:18,000 --> 00:33:23,120
clinical decision support with uh
961
00:33:20,720 --> 00:33:26,159
synthetic patient data as well and
962
00:33:23,120 --> 00:33:29,360
this concept of operation shows how from
963
00:33:26,159 --> 00:33:31,840
going left to right how you have cds
964
00:33:29,360 --> 00:33:33,200
contributors authors
965
00:33:31,840 --> 00:33:35,720
uh can
966
00:33:33,200 --> 00:33:39,279
contribute to cds connect where it will
967
00:33:35,720 --> 00:33:41,440
create um interoperable clinical
968
00:33:39,279 --> 00:33:43,519
decision support after
969
00:33:41,440 --> 00:33:46,159
review with our partners at mitre to
970
00:33:43,519 --> 00:33:49,880
make sure that your cds is clinically
971
00:33:46,159 --> 00:33:49,880
relevant and safe
972
00:33:51,000 --> 00:33:54,109
[Music]
973
00:33:55,519 --> 00:33:58,159
you know some nice background music
974
00:33:57,039 --> 00:34:00,399
there nice
975
00:33:58,159 --> 00:34:02,320
um and then using uh interoperable
976
00:34:00,399 --> 00:34:05,519
standards to get it into the point of
977
00:34:02,320 --> 00:34:07,360
care at the ehr or uh with patients and
978
00:34:05,519 --> 00:34:10,399
cells
979
00:34:07,360 --> 00:34:13,200
uh can you go to the next slide
980
00:34:10,399 --> 00:34:15,359
so to showcase how we leverage uh cds
981
00:34:13,200 --> 00:34:17,040
and the ehr into play
982
00:34:15,359 --> 00:34:19,280
to support substance abuse prevention
983
00:34:17,040 --> 00:34:20,960
and primary primary care i'm going to
984
00:34:19,280 --> 00:34:23,440
share some of our previous and ongoing
985
00:34:20,960 --> 00:34:25,520
efforts in chronic pain and opioid
986
00:34:23,440 --> 00:34:27,359
management although not specific to
987
00:34:25,520 --> 00:34:29,599
substance abuse prevention there are
988
00:34:27,359 --> 00:34:31,359
many parallels to both and highlight
989
00:34:29,599 --> 00:34:32,639
avenues that can be utilized for
990
00:34:31,359 --> 00:34:34,879
prevention
991
00:34:32,639 --> 00:34:37,200
these include patient patient apps uh
992
00:34:34,879 --> 00:34:39,679
the boston shared decision making and
993
00:34:37,200 --> 00:34:43,200
clinician-facing apps that utilize
994
00:34:39,679 --> 00:34:44,960
ehr data uh at the point of care uh the
995
00:34:43,200 --> 00:34:47,359
first example i'd like to highlight is
996
00:34:44,960 --> 00:34:49,599
uh the tapering and patient reported
997
00:34:47,359 --> 00:34:51,599
outcomes for chronic pain management app
998
00:34:49,599 --> 00:34:54,800
or known as the taper
999
00:34:51,599 --> 00:34:57,520
in a contracted effort with medstar and
1000
00:34:54,800 --> 00:34:58,640
also in collaboration with input from
1001
00:34:57,520 --> 00:35:01,680
chronic
1002
00:34:58,640 --> 00:35:04,240
pain patients caregivers
1003
00:35:01,680 --> 00:35:06,880
developers and pain specialists a
1004
00:35:04,240 --> 00:35:09,440
patient-basing and provider-facing
1005
00:35:06,880 --> 00:35:11,440
standards-based app was developed and is
1006
00:35:09,440 --> 00:35:12,560
currently finishing out its uh piloted
1007
00:35:11,440 --> 00:35:15,720
roll-out
1008
00:35:12,560 --> 00:35:15,720
next slide
1009
00:35:16,480 --> 00:35:20,480
so to walk you through this at an
1010
00:35:18,240 --> 00:35:22,560
initial visit a patient is introduced to
1011
00:35:20,480 --> 00:35:24,160
uh the taper app
1012
00:35:22,560 --> 00:35:26,240
and
1013
00:35:24,160 --> 00:35:29,200
uh they're able to track their pain and
1014
00:35:26,240 --> 00:35:31,440
daily function uh with the with the help
1015
00:35:29,200 --> 00:35:34,320
of the app the clinician on the back end
1016
00:35:31,440 --> 00:35:36,240
is able to see the patient's inputs and
1017
00:35:34,320 --> 00:35:38,320
either between visits or during a
1018
00:35:36,240 --> 00:35:40,640
follow-up able to review patient data
1019
00:35:38,320 --> 00:35:42,960
and work together with the patient uh to
1020
00:35:40,640 --> 00:35:44,960
create a future plan for
1021
00:35:42,960 --> 00:35:47,520
opioid tampering
1022
00:35:44,960 --> 00:35:49,280
uh next slide
1023
00:35:47,520 --> 00:35:50,320
the patient home screen welcome patient
1024
00:35:49,280 --> 00:35:51,760
and gives a
1025
00:35:50,320 --> 00:35:53,440
an overview
1026
00:35:51,760 --> 00:35:56,800
of the patient's current therapies and
1027
00:35:53,440 --> 00:35:56,800
regimen next slide
1028
00:35:57,680 --> 00:36:01,760
it allows journaling activities by the
1029
00:35:59,680 --> 00:36:04,400
patient and allows them to mark their
1030
00:36:01,760 --> 00:36:06,640
pain scores
1031
00:36:04,400 --> 00:36:10,400
next slide
1032
00:36:06,640 --> 00:36:12,400
utilizes it utilizes promised
1033
00:36:10,400 --> 00:36:13,520
questionnaire to further capture patient
1034
00:36:12,400 --> 00:36:15,599
input
1035
00:36:13,520 --> 00:36:17,520
and outcomes
1036
00:36:15,599 --> 00:36:20,000
next slide
1037
00:36:17,520 --> 00:36:21,200
and on the provider side the provider is
1038
00:36:20,000 --> 00:36:23,599
able to
1039
00:36:21,200 --> 00:36:26,240
view paper history
1040
00:36:23,599 --> 00:36:27,680
their plan summaries and also see what
1041
00:36:26,240 --> 00:36:28,800
the patient
1042
00:36:27,680 --> 00:36:30,000
reported
1043
00:36:28,800 --> 00:36:32,560
as well
1044
00:36:30,000 --> 00:36:32,560
next slide
1045
00:36:34,000 --> 00:36:36,880
so
1046
00:36:34,960 --> 00:36:39,920
on the ehr
1047
00:36:36,880 --> 00:36:41,680
data screen this relies a review of ehr
1048
00:36:39,920 --> 00:36:44,079
link patient data that is current with
1049
00:36:41,680 --> 00:36:45,599
their medications and also linked with
1050
00:36:44,079 --> 00:36:48,079
pdmp data
1051
00:36:45,599 --> 00:36:48,079
next slide
1052
00:36:48,320 --> 00:36:52,960
it allows then for a
1053
00:36:50,560 --> 00:36:55,119
taper plan to be created
1054
00:36:52,960 --> 00:36:56,800
that gives information on you can see on
1055
00:36:55,119 --> 00:36:59,119
the right hand side with your
1056
00:36:56,800 --> 00:37:00,640
recommendation and the mme reduction
1057
00:36:59,119 --> 00:37:01,680
percentage
1058
00:37:00,640 --> 00:37:04,240
along with
1059
00:37:01,680 --> 00:37:06,720
some recommendation prompts if needed
1060
00:37:04,240 --> 00:37:06,720
next slide
1061
00:37:07,520 --> 00:37:12,160
it also gives information on
1062
00:37:09,760 --> 00:37:14,480
alternative opioid pain medications and
1063
00:37:12,160 --> 00:37:16,160
other therapies that can be tried for
1064
00:37:14,480 --> 00:37:17,920
the patient as well as
1065
00:37:16,160 --> 00:37:18,960
medications for withdrawal symptoms as
1066
00:37:17,920 --> 00:37:22,119
well
1067
00:37:18,960 --> 00:37:22,119
next slide
1068
00:37:22,160 --> 00:37:26,320
our second application in partnership
1069
00:37:24,480 --> 00:37:29,200
with rti international created an
1070
00:37:26,320 --> 00:37:31,280
ehr-linked patient and provider facing
1071
00:37:29,200 --> 00:37:33,680
pain management app
1072
00:37:31,280 --> 00:37:36,640
to facilitate shared decision making
1073
00:37:33,680 --> 00:37:39,599
using a shared model approach
1074
00:37:36,640 --> 00:37:41,440
on the patient side called my pain
1075
00:37:39,599 --> 00:37:43,920
this app intakes patient reported
1076
00:37:41,440 --> 00:37:45,040
outcomes measures provides patients
1077
00:37:43,920 --> 00:37:47,920
information with their current
1078
00:37:45,040 --> 00:37:50,800
medication and alternatives
1079
00:37:47,920 --> 00:37:52,079
seeks input about their pain goals
1080
00:37:50,800 --> 00:37:53,839
as well
1081
00:37:52,079 --> 00:37:55,440
via questionnaire and then also free
1082
00:37:53,839 --> 00:37:57,200
text as well
1083
00:37:55,440 --> 00:37:59,200
on the provider side
1084
00:37:57,200 --> 00:38:01,760
called pain manager providers have
1085
00:37:59,200 --> 00:38:04,400
access to patients ehr linked histories
1086
00:38:01,760 --> 00:38:06,320
and data pdmp data
1087
00:38:04,400 --> 00:38:08,320
and results of
1088
00:38:06,320 --> 00:38:10,240
the patient's my pain questionnaire and
1089
00:38:08,320 --> 00:38:12,079
input to facilitate shared decision
1090
00:38:10,240 --> 00:38:14,000
making from the patient's pain
1091
00:38:12,079 --> 00:38:15,760
management or for the patient's pain
1092
00:38:14,000 --> 00:38:16,839
management
1093
00:38:15,760 --> 00:38:21,920
next
1094
00:38:16,839 --> 00:38:24,720
slide so to give you a quick review of
1095
00:38:21,920 --> 00:38:27,760
what the patient sees
1096
00:38:24,720 --> 00:38:29,920
and the questions asked you'll have
1097
00:38:27,760 --> 00:38:31,520
self-described goals
1098
00:38:29,920 --> 00:38:33,119
for the patient if you can click through
1099
00:38:31,520 --> 00:38:34,640
it will come up with some
1100
00:38:33,119 --> 00:38:36,960
um
1101
00:38:34,640 --> 00:38:38,880
next slides
1102
00:38:36,960 --> 00:38:41,920
and showing you what the patient
1103
00:38:38,880 --> 00:38:43,760
is able to input and review and will go
1104
00:38:41,920 --> 00:38:46,560
directly to
1105
00:38:43,760 --> 00:38:48,160
the physician-facing portion
1106
00:38:46,560 --> 00:38:49,280
my pain
1107
00:38:48,160 --> 00:38:51,440
manager
1108
00:38:49,280 --> 00:38:54,560
next slide
1109
00:38:51,440 --> 00:38:54,560
so on the provider side
1110
00:38:54,640 --> 00:38:59,760
their view is linked with ehr
1111
00:38:57,280 --> 00:39:02,000
data to embed pertinent
1112
00:38:59,760 --> 00:39:03,920
information such as past medical history
1113
00:39:02,000 --> 00:39:05,440
and other comorbidities when using
1114
00:39:03,920 --> 00:39:07,920
opioids
1115
00:39:05,440 --> 00:39:09,760
next slide
1116
00:39:07,920 --> 00:39:13,680
it shows current treatments an mme
1117
00:39:09,760 --> 00:39:15,280
calculator and also incorporates recent
1118
00:39:13,680 --> 00:39:18,400
patient stuff reported treatments as
1119
00:39:15,280 --> 00:39:18,400
well next slide
1120
00:39:18,880 --> 00:39:22,320
it also allows for review of recent ehr
1121
00:39:21,119 --> 00:39:25,359
linked data
1122
00:39:22,320 --> 00:39:28,079
from recent talk screens within the ehr
1123
00:39:25,359 --> 00:39:30,320
and also allows you to review patient
1124
00:39:28,079 --> 00:39:32,000
goals to further facilitate shared
1125
00:39:30,320 --> 00:39:32,960
decision making
1126
00:39:32,000 --> 00:39:35,680
either
1127
00:39:32,960 --> 00:39:38,960
via communication with the patient in my
1128
00:39:35,680 --> 00:39:42,160
pain or at the next clinic visit
1129
00:39:38,960 --> 00:39:44,960
next slide
1130
00:39:42,160 --> 00:39:47,839
so the next part of this work with my
1131
00:39:44,960 --> 00:39:50,000
pain pain managers to scale it and we
1132
00:39:47,839 --> 00:39:52,320
have awarded a grant to dr christopher
1133
00:39:50,000 --> 00:39:54,480
harley from the university of florida uh
1134
00:39:52,320 --> 00:39:56,880
for the opportunity to do so this work
1135
00:39:54,480 --> 00:39:59,280
will create a tailored implementation
1136
00:39:56,880 --> 00:40:00,960
strategy in order to facilitate
1137
00:39:59,280 --> 00:40:03,599
increased clinical decision support
1138
00:40:00,960 --> 00:40:06,160
adoption mainly of my pain and pain
1139
00:40:03,599 --> 00:40:08,160
manager in order to increase shared
1140
00:40:06,160 --> 00:40:09,119
decision making
1141
00:40:08,160 --> 00:40:12,000
and
1142
00:40:09,119 --> 00:40:14,240
hopefully improve outcomes improve pain
1143
00:40:12,000 --> 00:40:16,640
and physical function scores
1144
00:40:14,240 --> 00:40:18,720
uh next slide
1145
00:40:16,640 --> 00:40:21,359
uh additional work that we're funding to
1146
00:40:18,720 --> 00:40:23,359
also help facilitate getting data at the
1147
00:40:21,359 --> 00:40:27,520
point of uh delivery
1148
00:40:23,359 --> 00:40:30,160
is uh efforts uh by dr daniel
1149
00:40:27,520 --> 00:40:33,680
hartung out of ohsu
1150
00:40:30,160 --> 00:40:36,640
to facilitate ehr pdmp integration
1151
00:40:33,680 --> 00:40:38,720
uh this work hopes to determine how pmpa
1152
00:40:36,640 --> 00:40:40,560
integration facilitates provider use of
1153
00:40:38,720 --> 00:40:43,599
the pdmp program
1154
00:40:40,560 --> 00:40:45,760
and evaluates
1155
00:40:43,599 --> 00:40:48,319
these efforts on controlled setups and
1156
00:40:45,760 --> 00:40:50,800
prescribing
1157
00:40:48,319 --> 00:40:50,800
next slide
1158
00:40:50,880 --> 00:40:55,760
so although i have highlighted some
1159
00:40:53,599 --> 00:40:57,760
successes of our efforts uh there are
1160
00:40:55,760 --> 00:40:58,960
still many challenges and potential
1161
00:40:57,760 --> 00:40:59,839
opportunities
1162
00:40:58,960 --> 00:41:02,720
um
1163
00:40:59,839 --> 00:41:05,839
for not only arcs future focus but uh
1164
00:41:02,720 --> 00:41:08,000
nih as well and we hope that you will
1165
00:41:05,839 --> 00:41:10,240
think about these and moving forward uh
1166
00:41:08,000 --> 00:41:12,079
throughout the the remaining time in
1167
00:41:10,240 --> 00:41:14,640
these uh in these presentations and
1168
00:41:12,079 --> 00:41:16,079
workshops on the technical side just a
1169
00:41:14,640 --> 00:41:18,160
brief overview there are multiple
1170
00:41:16,079 --> 00:41:20,880
challenges remaining in regard to
1171
00:41:18,160 --> 00:41:23,359
ehr data interoperability
1172
00:41:20,880 --> 00:41:26,079
the use of ehr
1173
00:41:23,359 --> 00:41:28,000
data standards by vendors
1174
00:41:26,079 --> 00:41:30,960
a lack of a seamless integrated health
1175
00:41:28,000 --> 00:41:34,400
it infrastructure which ultimately
1176
00:41:30,960 --> 00:41:36,240
limits the use and scalability of cds
1177
00:41:34,400 --> 00:41:38,319
we are also still trying to show the
1178
00:41:36,240 --> 00:41:40,160
return of investment of clinical
1179
00:41:38,319 --> 00:41:43,280
decision support and there's ongoing
1180
00:41:40,160 --> 00:41:46,000
efforts to define clinical trials
1181
00:41:43,280 --> 00:41:47,200
showing how cds can improve the quality
1182
00:41:46,000 --> 00:41:49,200
of care
1183
00:41:47,200 --> 00:41:51,440
additionally how do we effectively
1184
00:41:49,200 --> 00:41:54,480
engage our patients their families and
1185
00:41:51,440 --> 00:41:56,160
caregivers in these technologies all
1186
00:41:54,480 --> 00:41:57,599
while trying not to create further
1187
00:41:56,160 --> 00:42:00,000
divides and
1188
00:41:57,599 --> 00:42:02,319
inequalities
1189
00:42:00,000 --> 00:42:04,240
also and especially for this topic
1190
00:42:02,319 --> 00:42:06,880
focused creating and disseminating the
1191
00:42:04,240 --> 00:42:09,520
appropriate evidence-based content for
1192
00:42:06,880 --> 00:42:12,480
the prevention of substance use i hope
1193
00:42:09,520 --> 00:42:15,359
in sharing some of these
1194
00:42:12,480 --> 00:42:17,040
arcs efforts and in ces can inspire and
1195
00:42:15,359 --> 00:42:19,200
provide some new ideas for those in the
1196
00:42:17,040 --> 00:42:20,720
audience i encourage everyone to reach
1197
00:42:19,200 --> 00:42:23,200
out and connect with us at our because
1198
00:42:20,720 --> 00:42:24,960
we need diverse feedback and ideas to
1199
00:42:23,200 --> 00:42:26,319
combat some of these challenges i've
1200
00:42:24,960 --> 00:42:27,760
shared
1201
00:42:26,319 --> 00:42:29,359
lastly
1202
00:42:27,760 --> 00:42:31,760
for those who are interested in
1203
00:42:29,359 --> 00:42:33,200
advancing cds efforts or creating it arc
1204
00:42:31,760 --> 00:42:35,599
has an interest in receiving health
1205
00:42:33,200 --> 00:42:37,200
services research grants
1206
00:42:35,599 --> 00:42:38,640
that propose innovative and
1207
00:42:37,200 --> 00:42:40,400
evidence-based interventions that
1208
00:42:38,640 --> 00:42:42,640
advance the nation's goal of achieving
1209
00:42:40,400 --> 00:42:44,480
equity in delivery of health care
1210
00:42:42,640 --> 00:42:47,040
services including reducing health
1211
00:42:44,480 --> 00:42:49,200
disparities in quality of care patient
1212
00:42:47,040 --> 00:42:52,240
safety health care utilization and
1213
00:42:49,200 --> 00:42:55,440
access and ultimately health outcomes uh
1214
00:42:52,240 --> 00:42:55,440
here are some of
1215
00:42:55,680 --> 00:42:59,760
information that can link us to some of
1216
00:42:57,920 --> 00:43:02,480
our efforts and also my contact
1217
00:42:59,760 --> 00:43:04,079
information so i look forward to the
1218
00:43:02,480 --> 00:43:06,079
discussion and any questions you might
1219
00:43:04,079 --> 00:43:08,960
have and hopefully you'll reach out and
1220
00:43:06,079 --> 00:43:08,960
partner with us
1221
00:43:10,400 --> 00:43:15,119
thanks so much so great as sarah
1222
00:43:13,040 --> 00:43:17,040
introduced me i'm brian jensen i'm a
1223
00:43:15,119 --> 00:43:18,720
practicing pediatrician i'm also a
1224
00:43:17,040 --> 00:43:20,240
researcher and a couple different hats i
1225
00:43:18,720 --> 00:43:21,440
have at the children's hospital of
1226
00:43:20,240 --> 00:43:22,560
philadelphia
1227
00:43:21,440 --> 00:43:24,160
uh we're gonna do something a little
1228
00:43:22,560 --> 00:43:25,520
different from the previous two speakers
1229
00:43:24,160 --> 00:43:26,560
we're gonna focus on learning through
1230
00:43:25,520 --> 00:43:28,319
failure
1231
00:43:26,560 --> 00:43:30,240
and really how to best
1232
00:43:28,319 --> 00:43:32,079
not leverage the ehr and leverage the
1233
00:43:30,240 --> 00:43:34,480
ehr for adolescent substance use
1234
00:43:32,079 --> 00:43:37,200
prevention and treatment
1235
00:43:34,480 --> 00:43:38,960
uh first i'm mainly my main focus has
1236
00:43:37,200 --> 00:43:40,560
started in the tobacco
1237
00:43:38,960 --> 00:43:42,079
control space and has moved into
1238
00:43:40,560 --> 00:43:43,680
substance use disorders other substance
1239
00:43:42,079 --> 00:43:45,520
disorders so first i have no relevant
1240
00:43:43,680 --> 00:43:47,040
conflict of interest to disclose of any
1241
00:43:45,520 --> 00:43:48,079
ownership in tobacco or e-cigarette
1242
00:43:47,040 --> 00:43:51,359
companies i also don't have any
1243
00:43:48,079 --> 00:43:54,000
ownership and any ehr companies or
1244
00:43:51,359 --> 00:43:55,440
similar health i.t companies
1245
00:43:54,000 --> 00:43:57,680
mainly what i'm going to talk about
1246
00:43:55,440 --> 00:43:59,760
briefly in about 10 15 minutes is
1247
00:43:57,680 --> 00:44:01,200
describe the lessons learned regarding
1248
00:43:59,760 --> 00:44:02,960
adolescent e-cigarette screening
1249
00:44:01,200 --> 00:44:06,480
connecting a treatment through a large
1250
00:44:02,960 --> 00:44:06,480
pediatric primary care health system
1251
00:44:06,560 --> 00:44:10,000
so
1252
00:44:07,359 --> 00:44:12,400
where this comes from first so there's
1253
00:44:10,000 --> 00:44:13,520
mario is giving a great talk about ahrq
1254
00:44:12,400 --> 00:44:15,520
and their different priorities and
1255
00:44:13,520 --> 00:44:18,000
opportunities just a little reminder
1256
00:44:15,520 --> 00:44:20,319
about how kind of the history of ehrs
1257
00:44:18,000 --> 00:44:21,280
and then how pediatric ehrs are
1258
00:44:20,319 --> 00:44:23,920
different
1259
00:44:21,280 --> 00:44:25,200
so ehrs were really built for adult
1260
00:44:23,920 --> 00:44:27,200
patients
1261
00:44:25,200 --> 00:44:28,960
uh pediatrics for anyone in that space
1262
00:44:27,200 --> 00:44:30,560
clinically or doing research knows or if
1263
00:44:28,960 --> 00:44:32,319
they have children or if you're a child
1264
00:44:30,560 --> 00:44:33,599
yourself at some point pediatrics
1265
00:44:32,319 --> 00:44:34,960
involves unique shifting development on
1266
00:44:33,599 --> 00:44:37,040
the aids of the children parents what we
1267
00:44:34,960 --> 00:44:38,720
say is there's an in for most in the
1268
00:44:37,040 --> 00:44:40,800
adult space there's a dyadic
1269
00:44:38,720 --> 00:44:42,880
relationship between the physician
1270
00:44:40,800 --> 00:44:44,880
provider and their patient in our space
1271
00:44:42,880 --> 00:44:46,319
in pediatrics it's triatic and many
1272
00:44:44,880 --> 00:44:48,240
times when i'm showing you just on this
1273
00:44:46,319 --> 00:44:49,680
classic picture yes i might take care i
1274
00:44:48,240 --> 00:44:51,599
take care of the child but in many ways
1275
00:44:49,680 --> 00:44:53,520
i'm also taking care of the mother so
1276
00:44:51,599 --> 00:44:55,359
there's a triatic relationship
1277
00:44:53,520 --> 00:44:58,880
there have been key priorities addressed
1278
00:44:55,359 --> 00:45:00,880
for improvement to help better adapt the
1279
00:44:58,880 --> 00:45:03,200
again adult focus dhr for the pediatric
1280
00:45:00,880 --> 00:45:04,400
space there are consensus guidelines i
1281
00:45:03,200 --> 00:45:05,680
have a reference to one of our papers
1282
00:45:04,400 --> 00:45:07,200
that recently highlighted this from the
1283
00:45:05,680 --> 00:45:08,640
american account of pediatrics and the
1284
00:45:07,200 --> 00:45:09,760
office of national coordinator for
1285
00:45:08,640 --> 00:45:11,599
health i.t
1286
00:45:09,760 --> 00:45:14,160
but the two main things for today for
1287
00:45:11,599 --> 00:45:16,560
this audience to know how ehrs and
1288
00:45:14,160 --> 00:45:18,640
pediatric space are different than the
1289
00:45:16,560 --> 00:45:20,720
adult is there needs to be better
1290
00:45:18,640 --> 00:45:23,200
systems to document all guardians and
1291
00:45:20,720 --> 00:45:24,640
connect families ehr is built for one
1292
00:45:23,200 --> 00:45:26,319
patient and the provider but in
1293
00:45:24,640 --> 00:45:28,079
pediatrics you might have multiple
1294
00:45:26,319 --> 00:45:30,000
different parents guardians caregivers
1295
00:45:28,079 --> 00:45:31,920
who need to access the ehr
1296
00:45:30,000 --> 00:45:34,480
and then you need to come up with ways
1297
00:45:31,920 --> 00:45:36,480
to connect the families together the
1298
00:45:34,480 --> 00:45:37,599
ehrs is currently built can't tell
1299
00:45:36,480 --> 00:45:39,599
siblings
1300
00:45:37,599 --> 00:45:41,520
can't connect siblings to one another
1301
00:45:39,599 --> 00:45:43,040
the other big issue is we need better
1302
00:45:41,520 --> 00:45:45,040
segmented access to information
1303
00:45:43,040 --> 00:45:46,240
communication channels because of that
1304
00:45:45,040 --> 00:45:49,520
shifting relationship i mentioned
1305
00:45:46,240 --> 00:45:50,720
between parent child and pediatrician
1306
00:45:49,520 --> 00:45:52,640
what happens over time is there's
1307
00:45:50,720 --> 00:45:54,480
increase in adolescent autonomy and we
1308
00:45:52,640 --> 00:45:56,160
need channels that can both communicate
1309
00:45:54,480 --> 00:45:57,760
back and forth with the teenager but
1310
00:45:56,160 --> 00:45:59,280
also separately with the parent to
1311
00:45:57,760 --> 00:46:01,440
support their relationship but also
1312
00:45:59,280 --> 00:46:02,720
protect adolescent confidentiality
1313
00:46:01,440 --> 00:46:04,079
that in and of itself is a whole talk
1314
00:46:02,720 --> 00:46:06,720
but that's just high level how the
1315
00:46:04,079 --> 00:46:08,079
unique needs of pediatric ehr
1316
00:46:06,720 --> 00:46:09,760
so what i'm going to talk more about is
1317
00:46:08,079 --> 00:46:11,920
an effort to focus on prevention and
1318
00:46:09,760 --> 00:46:13,599
treatment of tobacco use in particular
1319
00:46:11,920 --> 00:46:14,960
e-cigarette use
1320
00:46:13,599 --> 00:46:16,240
so what lessons could be learned from
1321
00:46:14,960 --> 00:46:17,760
cigarettes well
1322
00:46:16,240 --> 00:46:20,240
teen cigarette smokers want to quit
1323
00:46:17,760 --> 00:46:22,000
that's pretty clear few teens seek help
1324
00:46:20,240 --> 00:46:24,400
there are limited to essentially no
1325
00:46:22,000 --> 00:46:26,880
evidence-based treatment options
1326
00:46:24,400 --> 00:46:28,640
for adolescent cigarette use and even
1327
00:46:26,880 --> 00:46:30,800
fewer options for adolescent e-cigarette
1328
00:46:28,640 --> 00:46:32,640
use but pediatricians are uniquely
1329
00:46:30,800 --> 00:46:35,119
positioned to intervene because the vast
1330
00:46:32,640 --> 00:46:36,560
majority of children in the united
1331
00:46:35,119 --> 00:46:38,800
states the vast majority of teenagers
1332
00:46:36,560 --> 00:46:40,079
come to a pediatric provider
1333
00:46:38,800 --> 00:46:42,000
there's limited data on how to treat
1334
00:46:40,079 --> 00:46:43,920
teens for e-cigarette addiction though a
1335
00:46:42,000 --> 00:46:46,000
large percentage of teens based on most
1336
00:46:43,920 --> 00:46:47,440
recent surveys want to quit and there
1337
00:46:46,000 --> 00:46:48,720
have been some new targeted treatment
1338
00:46:47,440 --> 00:46:50,720
options and i'll highlight one that we
1339
00:46:48,720 --> 00:46:52,720
connected with
1340
00:46:50,720 --> 00:46:55,119
so we created a study that we were
1341
00:46:52,720 --> 00:46:56,640
calling our chopteen be smoke-free
1342
00:46:55,119 --> 00:46:58,640
cessation study
1343
00:46:56,640 --> 00:47:00,640
and we brought together a whole bunch of
1344
00:46:58,640 --> 00:47:02,079
innovative approaches that combined
1345
00:47:00,640 --> 00:47:03,760
interesting technology and electronic
1346
00:47:02,079 --> 00:47:05,520
health records we had a three-arm
1347
00:47:03,760 --> 00:47:07,440
pragmatic randomized trial to help teens
1348
00:47:05,520 --> 00:47:09,119
engage in treatment and quit we
1349
00:47:07,440 --> 00:47:10,319
incorporate behavioral economic concepts
1350
00:47:09,119 --> 00:47:12,240
that's beyond the scope of this talk
1351
00:47:10,319 --> 00:47:14,480
what we're focused on between us a
1352
00:47:12,240 --> 00:47:16,560
seemingly small recruitment goal with 60
1353
00:47:14,480 --> 00:47:18,400
participants i'll say seemingly small
1354
00:47:16,560 --> 00:47:20,720
and i'll show you why uh over the next
1355
00:47:18,400 --> 00:47:22,640
couple slides and we leverage three
1356
00:47:20,720 --> 00:47:24,640
critical components we have a large
1357
00:47:22,640 --> 00:47:27,920
pediatric health system
1358
00:47:24,640 --> 00:47:30,480
we were going to enroll and identify
1359
00:47:27,920 --> 00:47:32,720
children teenagers via electronic health
1360
00:47:30,480 --> 00:47:34,720
record-based prompts and then engage
1361
00:47:32,720 --> 00:47:36,640
them in treatment through a really novel
1362
00:47:34,720 --> 00:47:38,480
text messaging program and then we're
1363
00:47:36,640 --> 00:47:40,079
going to connect them to a novel
1364
00:47:38,480 --> 00:47:41,680
treatment program that was organized
1365
00:47:40,079 --> 00:47:43,359
through our state
1366
00:47:41,680 --> 00:47:44,960
quit line our state tobacco treatment
1367
00:47:43,359 --> 00:47:46,640
program
1368
00:47:44,960 --> 00:47:48,240
i mentioned we have a large primary care
1369
00:47:46,640 --> 00:47:49,280
system so
1370
00:47:48,240 --> 00:47:51,839
as sarah mentioned on the medical
1371
00:47:49,280 --> 00:47:53,359
director in our large primary care
1372
00:47:51,839 --> 00:47:55,520
health system that's based in 31
1373
00:47:53,359 --> 00:47:57,359
practices across pennsylvania new jersey
1374
00:47:55,520 --> 00:47:59,839
we have approximately 300 000 patients
1375
00:47:57,359 --> 00:48:01,920
about 80 000 teenagers and we have an
1376
00:47:59,839 --> 00:48:04,240
integrated electronic health record we
1377
00:48:01,920 --> 00:48:06,079
use epic and that system has been in use
1378
00:48:04,240 --> 00:48:07,920
for more than 20 years so we've been at
1379
00:48:06,079 --> 00:48:10,480
kind of the tip of the sphere in terms
1380
00:48:07,920 --> 00:48:12,400
of innovation efforts within the ehr our
1381
00:48:10,480 --> 00:48:15,119
demographics are for the most part
1382
00:48:12,400 --> 00:48:17,280
representative of the larger national
1383
00:48:15,119 --> 00:48:19,119
population just highlighted here on this
1384
00:48:17,280 --> 00:48:20,960
slide
1385
00:48:19,119 --> 00:48:23,440
and we leveraged relevant to this talk
1386
00:48:20,960 --> 00:48:25,359
some really advanced ehr techniques uh
1387
00:48:23,440 --> 00:48:27,040
we had screen that was based embedded
1388
00:48:25,359 --> 00:48:28,720
within clinical practice
1389
00:48:27,040 --> 00:48:30,480
what this what we did was a provider
1390
00:48:28,720 --> 00:48:33,440
prompt within the confidential
1391
00:48:30,480 --> 00:48:35,839
adolescent visit documentation to then
1392
00:48:33,440 --> 00:48:37,200
to ask about tobacco use and e-cigarette
1393
00:48:35,839 --> 00:48:38,800
use what i'm showing you on the
1394
00:48:37,200 --> 00:48:41,040
right-hand side of this screen is the
1395
00:48:38,800 --> 00:48:42,240
documentation that are prompts for the
1396
00:48:41,040 --> 00:48:44,240
physician pediatrician nurse
1397
00:48:42,240 --> 00:48:45,599
practitioner in clinical practice to go
1398
00:48:44,240 --> 00:48:47,839
all through these things during the
1399
00:48:45,599 --> 00:48:49,520
confidential visit portion of the visit
1400
00:48:47,839 --> 00:48:51,280
if the team were to be positive for
1401
00:48:49,520 --> 00:48:53,040
e-cigarette use any tobacco use
1402
00:48:51,280 --> 00:48:54,800
cigarette use there were additional
1403
00:48:53,040 --> 00:48:57,599
problems
1404
00:48:54,800 --> 00:48:59,680
the there was scripts on assessing
1405
00:48:57,599 --> 00:49:01,680
interest in quitting or engaging in
1406
00:48:59,680 --> 00:49:03,040
treatment from the pediatrician and then
1407
00:49:01,680 --> 00:49:04,480
permission from the study for the study
1408
00:49:03,040 --> 00:49:06,319
team to follow up the team via text
1409
00:49:04,480 --> 00:49:07,839
messaging this has been an approach that
1410
00:49:06,319 --> 00:49:10,319
we've been leveraging for more than 10
1411
00:49:07,839 --> 00:49:12,640
years it works really well to identify
1412
00:49:10,319 --> 00:49:14,559
individuals who could uh participate in
1413
00:49:12,640 --> 00:49:16,720
the study and then connect them to the
1414
00:49:14,559 --> 00:49:18,079
study team so this has been a well-worn
1415
00:49:16,720 --> 00:49:20,079
approach
1416
00:49:18,079 --> 00:49:21,680
we also leveraged
1417
00:49:20,079 --> 00:49:23,359
text messaging which is really the best
1418
00:49:21,680 --> 00:49:24,880
way to engage teams
1419
00:49:23,359 --> 00:49:26,720
we have a program based through the
1420
00:49:24,880 --> 00:49:29,200
university of pennsylvania that's a
1421
00:49:26,720 --> 00:49:30,559
research platform that
1422
00:49:29,200 --> 00:49:32,720
combines a whole bunch of different
1423
00:49:30,559 --> 00:49:34,640
techniques into a text messaging
1424
00:49:32,720 --> 00:49:37,520
platform to immediately engage
1425
00:49:34,640 --> 00:49:39,040
individuals in a study or in treatment
1426
00:49:37,520 --> 00:49:40,720
so a novel thing that we were connect
1427
00:49:39,040 --> 00:49:41,760
that we were able to immediately engage
1428
00:49:40,720 --> 00:49:43,599
teens in
1429
00:49:41,760 --> 00:49:45,280
and then we were collaborating with our
1430
00:49:43,599 --> 00:49:46,960
partner national jewish health they're
1431
00:49:45,280 --> 00:49:49,760
the servicer for the pennsylvania quit
1432
00:49:46,960 --> 00:49:52,559
line they had at the time a novel
1433
00:49:49,760 --> 00:49:54,319
program this was back in 2018 2019 where
1434
00:49:52,559 --> 00:49:56,240
they created both counseling over the
1435
00:49:54,319 --> 00:49:58,640
phone but a program that really
1436
00:49:56,240 --> 00:50:00,480
a text messaging based program and a
1437
00:49:58,640 --> 00:50:02,480
portal-based program to really help
1438
00:50:00,480 --> 00:50:05,599
teens who were vaping using other
1439
00:50:02,480 --> 00:50:07,119
tobacco products engaging quitting
1440
00:50:05,599 --> 00:50:09,440
and what happened here here is the
1441
00:50:07,119 --> 00:50:11,599
emphasis on learning through failure
1442
00:50:09,440 --> 00:50:14,240
unsurprisingly to anyone
1443
00:50:11,599 --> 00:50:16,720
on this meeting right now helping engage
1444
00:50:14,240 --> 00:50:18,800
teens in treatment is incredibly hard
1445
00:50:16,720 --> 00:50:20,960
but we were surprised about how much of
1446
00:50:18,800 --> 00:50:23,200
a flop this was it was a failed
1447
00:50:20,960 --> 00:50:25,760
feasibility study we screened more than
1448
00:50:23,200 --> 00:50:27,520
80 000 teams in the span of one year for
1449
00:50:25,760 --> 00:50:29,040
vaping that's a success
1450
00:50:27,520 --> 00:50:30,240
but only one percent of teens reported
1451
00:50:29,040 --> 00:50:32,559
current use
1452
00:50:30,240 --> 00:50:34,640
so either our teens are
1453
00:50:32,559 --> 00:50:36,000
perfect or we were missing something
1454
00:50:34,640 --> 00:50:38,079
because at the time
1455
00:50:36,000 --> 00:50:40,960
the school-based normative surveys were
1456
00:50:38,079 --> 00:50:42,480
suggesting 20 to 25 percent of teens
1457
00:50:40,960 --> 00:50:44,319
were current users
1458
00:50:42,480 --> 00:50:47,280
so we were missing something
1459
00:50:44,319 --> 00:50:50,000
uh of the roughly 5 000 teens that did
1460
00:50:47,280 --> 00:50:51,920
ultimately report use only 52 were
1461
00:50:50,000 --> 00:50:53,359
referred to our study another big flop
1462
00:50:51,920 --> 00:50:55,520
because we had a much better track
1463
00:50:53,359 --> 00:50:57,599
record of using engaging teens
1464
00:50:55,520 --> 00:50:59,200
in other research studies and we closed
1465
00:50:57,599 --> 00:51:01,280
the study early because we were only
1466
00:50:59,200 --> 00:51:02,480
able to enroll 16 individuals across two
1467
00:51:01,280 --> 00:51:04,800
years
1468
00:51:02,480 --> 00:51:06,880
so we published this luckily uh nice to
1469
00:51:04,800 --> 00:51:08,960
the journal to acknowledge that this was
1470
00:51:06,880 --> 00:51:11,520
a failed study but what we really
1471
00:51:08,960 --> 00:51:13,440
identified was the most immediate issue
1472
00:51:11,520 --> 00:51:15,920
before we even get to treatment
1473
00:51:13,440 --> 00:51:18,000
was improved systems to identify teens
1474
00:51:15,920 --> 00:51:20,079
at risk in other words improved clinical
1475
00:51:18,000 --> 00:51:22,400
based screening which has been a theme
1476
00:51:20,079 --> 00:51:24,400
mentioned at the start of this whole
1477
00:51:22,400 --> 00:51:26,079
session today
1478
00:51:24,400 --> 00:51:27,760
so what were our key lessons learned if
1479
00:51:26,079 --> 00:51:29,599
there's one slide
1480
00:51:27,760 --> 00:51:30,640
to remember and a couple key points it's
1481
00:51:29,599 --> 00:51:32,800
this one
1482
00:51:30,640 --> 00:51:34,720
first if you're going to do anything to
1483
00:51:32,800 --> 00:51:36,000
identify health risk you need to create
1484
00:51:34,720 --> 00:51:37,920
the right environment to maximize
1485
00:51:36,000 --> 00:51:40,319
disclosure i'm also an innovation
1486
00:51:37,920 --> 00:51:42,160
researcher so what we did was um we had
1487
00:51:40,319 --> 00:51:43,680
another study live in various practices
1488
00:51:42,160 --> 00:51:45,680
and i was walking around engaging with
1489
00:51:43,680 --> 00:51:47,200
our pediatricians
1490
00:51:45,680 --> 00:51:48,559
ostensibly for this other study but i
1491
00:51:47,200 --> 00:51:50,720
was really there to also observe what
1492
00:51:48,559 --> 00:51:52,960
was happening with screening and we
1493
00:51:50,720 --> 00:51:54,160
found that um
1494
00:51:52,960 --> 00:51:55,680
even though we had trained the
1495
00:51:54,160 --> 00:51:56,880
pediatricians and the nurse
1496
00:51:55,680 --> 00:51:58,960
practitioners and the nurses and the
1497
00:51:56,880 --> 00:52:00,720
best ways to ask certain questions we
1498
00:51:58,960 --> 00:52:02,480
often heard a nurse and i was supposed
1499
00:52:00,720 --> 00:52:04,800
to be the pediatrician asking the
1500
00:52:02,480 --> 00:52:05,920
question of the team next to the parent
1501
00:52:04,800 --> 00:52:07,200
and the parent was supposed to be
1502
00:52:05,920 --> 00:52:09,040
outside of the room
1503
00:52:07,200 --> 00:52:10,559
uh you don't you don't they do you don't
1504
00:52:09,040 --> 00:52:12,960
use any tobaccos and that's not the
1505
00:52:10,559 --> 00:52:14,800
evidence-based way of screening so you
1506
00:52:12,960 --> 00:52:15,760
really want to make sure that in this
1507
00:52:14,800 --> 00:52:17,839
environment you're not doing
1508
00:52:15,760 --> 00:52:19,520
face-to-face based screening and not
1509
00:52:17,839 --> 00:52:21,119
screening teens for health risks with
1510
00:52:19,520 --> 00:52:22,880
the parent right next to them that
1511
00:52:21,119 --> 00:52:24,240
really hasn't created the hasn't
1512
00:52:22,880 --> 00:52:25,359
maximized the right environment for
1513
00:52:24,240 --> 00:52:27,680
disclosure
1514
00:52:25,359 --> 00:52:29,760
now the other big thing related to ehr's
1515
00:52:27,680 --> 00:52:32,960
work is you really have to understand
1516
00:52:29,760 --> 00:52:35,839
the clinical workflow problem before you
1517
00:52:32,960 --> 00:52:37,599
build the correct ehr based solution
1518
00:52:35,839 --> 00:52:40,240
so for those who might be thinking oh if
1519
00:52:37,599 --> 00:52:42,480
only we could use ehr documentation to
1520
00:52:40,240 --> 00:52:44,160
identify something uh to then build a
1521
00:52:42,480 --> 00:52:45,760
better research platform or build a
1522
00:52:44,160 --> 00:52:47,680
better intervention
1523
00:52:45,760 --> 00:52:48,800
ehr documentation
1524
00:52:47,680 --> 00:52:50,559
is flawed
1525
00:52:48,800 --> 00:52:52,000
we often talk about
1526
00:52:50,559 --> 00:52:55,119
when you hear kind of terms like big
1527
00:52:52,000 --> 00:52:57,200
data big data is really found data in
1528
00:52:55,119 --> 00:52:59,040
many ways it's if you have bad data in
1529
00:52:57,200 --> 00:53:01,359
you get bad data out so what we learned
1530
00:52:59,040 --> 00:53:03,359
was yes it looked like the teens were
1531
00:53:01,359 --> 00:53:04,720
getting screened for e-cigarette use but
1532
00:53:03,359 --> 00:53:06,880
they weren't really weren't being
1533
00:53:04,720 --> 00:53:08,800
screened in the best possible way
1534
00:53:06,880 --> 00:53:10,960
so for the next couple slides
1535
00:53:08,800 --> 00:53:12,720
i'll highlight how we can do better and
1536
00:53:10,960 --> 00:53:14,240
we started to do better which is this is
1537
00:53:12,720 --> 00:53:15,599
really the direction one needs to go if
1538
00:53:14,240 --> 00:53:16,960
you're going to focus on pediatric
1539
00:53:15,599 --> 00:53:20,160
focused
1540
00:53:16,960 --> 00:53:22,319
substance use prevention and treatment
1541
00:53:20,160 --> 00:53:25,200
so pretty much all humans but especially
1542
00:53:22,319 --> 00:53:27,359
teenagers prefer electronic screening
1543
00:53:25,200 --> 00:53:29,040
directly of them as the best way to
1544
00:53:27,359 --> 00:53:30,400
identify health risk it can be
1545
00:53:29,040 --> 00:53:32,160
administered on a tablet or other mobile
1546
00:53:30,400 --> 00:53:33,599
devices and that's been identified
1547
00:53:32,160 --> 00:53:34,960
through multiple studies small studies
1548
00:53:33,599 --> 00:53:36,559
compared to either paper screen or
1549
00:53:34,960 --> 00:53:38,800
general questions that are asked by the
1550
00:53:36,559 --> 00:53:40,640
clinician face to face during the visit
1551
00:53:38,800 --> 00:53:42,880
and this approach can increase validity
1552
00:53:40,640 --> 00:53:44,400
increases the true positives
1553
00:53:42,880 --> 00:53:45,680
one can increase disclosure of health
1554
00:53:44,400 --> 00:53:47,040
risks
1555
00:53:45,680 --> 00:53:48,400
and then especially if you combine that
1556
00:53:47,040 --> 00:53:50,640
with private confidential time with the
1557
00:53:48,400 --> 00:53:51,920
pediatricians and here's the value add
1558
00:53:50,640 --> 00:53:55,680
you don't necessarily have to just focus
1559
00:53:51,920 --> 00:53:57,280
on reimbursement but giving time back to
1560
00:53:55,680 --> 00:53:59,200
physicians is such an important area
1561
00:53:57,280 --> 00:54:00,800
where you can get hidden value
1562
00:53:59,200 --> 00:54:02,240
this approach actually takes less time
1563
00:54:00,800 --> 00:54:03,599
than the current face-to-face approach
1564
00:54:02,240 --> 00:54:05,520
because most satellite social history is
1565
00:54:03,599 --> 00:54:08,240
screening this negative so you can speed
1566
00:54:05,520 --> 00:54:10,079
up the visit and focus on other issues
1567
00:54:08,240 --> 00:54:11,680
saves about 5-10 minutes of face to face
1568
00:54:10,079 --> 00:54:13,359
time and then you can more easily
1569
00:54:11,680 --> 00:54:15,599
identify the positives for in-depth
1570
00:54:13,359 --> 00:54:17,440
discussion this last section is how we
1571
00:54:15,599 --> 00:54:19,920
really pitched to our pediatricians
1572
00:54:17,440 --> 00:54:22,319
across our 31 practices why we needed to
1573
00:54:19,920 --> 00:54:23,599
move to an electronic screen approach
1574
00:54:22,319 --> 00:54:24,640
because the other way i didn't want to
1575
00:54:23,599 --> 00:54:26,000
say direct with them but they weren't
1576
00:54:24,640 --> 00:54:27,200
doing the right things to maximize
1577
00:54:26,000 --> 00:54:28,800
disclosure
1578
00:54:27,200 --> 00:54:30,480
so what we moved to
1579
00:54:28,800 --> 00:54:31,520
was a pre-visit adolescent health
1580
00:54:30,480 --> 00:54:33,680
questionnaire i'm showing on the
1581
00:54:31,520 --> 00:54:35,920
left-hand side we have eight domains
1582
00:54:33,680 --> 00:54:37,760
it's a 30-question questionnaire that's
1583
00:54:35,920 --> 00:54:39,839
administered in a confidential manner on
1584
00:54:37,760 --> 00:54:41,760
a tablet when the teenager walks into
1585
00:54:39,839 --> 00:54:43,440
the office what often happens is the
1586
00:54:41,760 --> 00:54:45,599
teenager picks up the tablet and walks
1587
00:54:43,440 --> 00:54:47,119
around the waiting area or gets shuttled
1588
00:54:45,599 --> 00:54:48,640
back shuffled back to the room and
1589
00:54:47,119 --> 00:54:50,799
completes the tablet while they're
1590
00:54:48,640 --> 00:54:52,400
waiting for the pediatrician i mentioned
1591
00:54:50,799 --> 00:54:54,480
30 questions i'm just highlighting this
1592
00:54:52,400 --> 00:54:56,720
is actually showing this audience
1593
00:54:54,480 --> 00:54:58,799
focused on substance use disorders
1594
00:54:56,720 --> 00:55:01,920
uh the craft questionnaire incorporating
1595
00:54:58,799 --> 00:55:03,760
this directly in into this questionnaire
1596
00:55:01,920 --> 00:55:05,760
and what we focused on was building this
1597
00:55:03,760 --> 00:55:07,040
into the correct workflow so i'm showing
1598
00:55:05,760 --> 00:55:08,720
you here is in our development
1599
00:55:07,040 --> 00:55:10,480
environment again with epic our main
1600
00:55:08,720 --> 00:55:11,760
electronic health record really
1601
00:55:10,480 --> 00:55:13,599
integrating this into the physician
1602
00:55:11,760 --> 00:55:15,520
workflow you don't have to just focus on
1603
00:55:13,599 --> 00:55:17,520
reimbursement again making lives easier
1604
00:55:15,520 --> 00:55:19,599
for physicians and nurses is a great
1605
00:55:17,520 --> 00:55:21,440
value add and so this is showing you the
1606
00:55:19,599 --> 00:55:22,960
questionnaire on the left-hand side and
1607
00:55:21,440 --> 00:55:24,960
how we automatically pull the
1608
00:55:22,960 --> 00:55:26,960
documentation into the notes for the
1609
00:55:24,960 --> 00:55:28,640
pediatricians so if there's no issue
1610
00:55:26,960 --> 00:55:30,319
they can automatically say oh no issues
1611
00:55:28,640 --> 00:55:32,319
discuss priorities and that there were
1612
00:55:30,319 --> 00:55:34,400
issues we supported the documentation
1613
00:55:32,319 --> 00:55:36,079
for that
1614
00:55:34,400 --> 00:55:37,839
it's been a huge operational success
1615
00:55:36,079 --> 00:55:41,440
this questionnaire is now live in all 31
1616
00:55:37,839 --> 00:55:43,680
of our practices as of january 2022
1617
00:55:41,440 --> 00:55:45,599
i mentioned we have 80 000 teenagers the
1618
00:55:43,680 --> 00:55:48,640
questionnaire has been completed 31 000
1619
00:55:45,599 --> 00:55:49,920
times across our 31 primary care sites
1620
00:55:48,640 --> 00:55:51,760
lower numbers right now because we just
1621
00:55:49,920 --> 00:55:53,760
went live in our practices we have a
1622
00:55:51,760 --> 00:55:55,920
high completion rate for the individual
1623
00:55:53,760 --> 00:55:57,440
visit about 92 percent of the time the
1624
00:55:55,920 --> 00:55:58,559
questionnaire is completed
1625
00:55:57,440 --> 00:55:59,760
and there's no real meaningful
1626
00:55:58,559 --> 00:56:01,760
difference in completion by practice
1627
00:55:59,760 --> 00:56:03,520
setting vast majority of teens prefer to
1628
00:56:01,760 --> 00:56:04,799
answer these questionnaires questions
1629
00:56:03,520 --> 00:56:06,160
electronically we embedded a
1630
00:56:04,799 --> 00:56:08,160
questionnaire into the questionnaire to
1631
00:56:06,160 --> 00:56:10,240
confirm that and on average just takes
1632
00:56:08,160 --> 00:56:12,480
five to ten minutes now here's the real
1633
00:56:10,240 --> 00:56:14,000
success again learning through failure
1634
00:56:12,480 --> 00:56:16,319
prior to moving live which i'm going to
1635
00:56:14,000 --> 00:56:18,400
show you in the next slide to this
1636
00:56:16,319 --> 00:56:19,680
electronic approach when you looked at
1637
00:56:18,400 --> 00:56:21,839
health risks that were supposed to be
1638
00:56:19,680 --> 00:56:23,680
captured across the board we found about
1639
00:56:21,839 --> 00:56:26,079
one to two percent of teens reported
1640
00:56:23,680 --> 00:56:28,640
that they were using tobacco using
1641
00:56:26,079 --> 00:56:30,079
marijuana using alcohol and even only
1642
00:56:28,640 --> 00:56:32,160
three to four percent were reporting
1643
00:56:30,079 --> 00:56:33,839
sexual activity which also is not
1644
00:56:32,160 --> 00:56:36,000
aligned with the school-based norm of
1645
00:56:33,839 --> 00:56:38,000
surveys nor our own anecdotal experience
1646
00:56:36,000 --> 00:56:40,000
as pediatricians
1647
00:56:38,000 --> 00:56:41,760
moving to electronic screening it's a
1648
00:56:40,000 --> 00:56:43,599
pre-post model this is kind of a messy
1649
00:56:41,760 --> 00:56:45,599
innovation study but it's embedded now
1650
00:56:43,599 --> 00:56:46,880
in the large health system dramatically
1651
00:56:45,599 --> 00:56:48,880
improves disclosure i'm just showing you
1652
00:56:46,880 --> 00:56:50,079
some of the high level uh unsurprisingly
1653
00:56:48,880 --> 00:56:51,040
the vast majority of teens don't eat the
1654
00:56:50,079 --> 00:56:52,240
right amount of fruits and veggies i
1655
00:56:51,040 --> 00:56:53,200
know this is beyond substance use but
1656
00:56:52,240 --> 00:56:54,400
just highlighting how there are a whole
1657
00:56:53,200 --> 00:56:56,400
bunch of other health risks we talk
1658
00:56:54,400 --> 00:56:58,880
about a lot of teenagers have a gun in
1659
00:56:56,400 --> 00:57:00,799
the home that they know about most many
1660
00:56:58,880 --> 00:57:02,720
teens don't wear their seatbelt but of
1661
00:57:00,799 --> 00:57:04,079
the interests of this audience so
1662
00:57:02,720 --> 00:57:06,000
previous implementation we're talking
1663
00:57:04,079 --> 00:57:08,319
about one percent of teens disclosing
1664
00:57:06,000 --> 00:57:10,240
substance use uh now we're up to nine
1665
00:57:08,319 --> 00:57:11,920
percent reporting alcohol nine percent
1666
00:57:10,240 --> 00:57:14,240
reporting marijuana use eight percent
1667
00:57:11,920 --> 00:57:15,359
regarding tobacco product use and um
1668
00:57:14,240 --> 00:57:16,880
another area that we're focused on
1669
00:57:15,359 --> 00:57:18,960
sexual activity 23 percent of
1670
00:57:16,880 --> 00:57:20,799
adolescents recruit sexual activity and
1671
00:57:18,960 --> 00:57:23,040
something else is we also include um
1672
00:57:20,799 --> 00:57:24,960
questions around sexual identity 14 of
1673
00:57:23,040 --> 00:57:26,640
our teens i'm proud of this next one 14
1674
00:57:24,960 --> 00:57:29,200
of our teams i feel comfortable
1675
00:57:26,640 --> 00:57:31,760
disclosing that they're they identify as
1676
00:57:29,200 --> 00:57:33,680
lgbtq on finally on the right hand side
1677
00:57:31,760 --> 00:57:35,119
i'm just showing the craft score to show
1678
00:57:33,680 --> 00:57:37,119
you where we can move next we can do
1679
00:57:35,119 --> 00:57:38,720
profiling obtained or kind of i should
1680
00:57:37,119 --> 00:57:40,960
say stratification of teams that are at
1681
00:57:38,720 --> 00:57:41,760
risk and then target interventions for
1682
00:57:40,960 --> 00:57:43,440
them
1683
00:57:41,760 --> 00:57:45,040
the final thing we're focused on now is
1684
00:57:43,440 --> 00:57:46,160
really decision support to address the
1685
00:57:45,040 --> 00:57:48,640
needs
1686
00:57:46,160 --> 00:57:50,400
based on issues identified through our
1687
00:57:48,640 --> 00:57:52,400
electronic questionnaire approach this
1688
00:57:50,400 --> 00:57:54,799
is a busy slide but it's showing you
1689
00:57:52,400 --> 00:57:56,640
prompts towards the physicians around
1690
00:57:54,799 --> 00:57:59,359
sexual
1691
00:57:56,640 --> 00:58:01,520
sti-based screening prevention and
1692
00:57:59,359 --> 00:58:03,520
treatment meaning that if a teen
1693
00:58:01,520 --> 00:58:04,720
identifies as being sexually active but
1694
00:58:03,520 --> 00:58:05,920
our system shows they've never been
1695
00:58:04,720 --> 00:58:07,839
screened or haven't recently been
1696
00:58:05,920 --> 00:58:09,760
appropriately screened for stis this
1697
00:58:07,839 --> 00:58:11,599
then is one of our ways of getting this
1698
00:58:09,760 --> 00:58:15,040
in front of a physician to order
1699
00:58:11,599 --> 00:58:16,400
appropriate labs and get those labs done
1700
00:58:15,040 --> 00:58:18,400
with that
1701
00:58:16,400 --> 00:58:20,559
i'll close and i think we'll open up for
1702
00:58:18,400 --> 00:58:20,559
q
1703
00:58:20,839 --> 00:58:26,240
a thank you ryan um
1704
00:58:23,920 --> 00:58:27,760
and thanks to each of you that was great
1705
00:58:26,240 --> 00:58:28,480
um
1706
00:58:27,760 --> 00:58:29,520
we
1707
00:58:28,480 --> 00:58:32,559
um
1708
00:58:29,520 --> 00:58:34,559
i'd love for anyone who has questions to
1709
00:58:32,559 --> 00:58:37,200
um to put them in the chat
1710
00:58:34,559 --> 00:58:38,559
um go ahead and ask and just as we're
1711
00:58:37,200 --> 00:58:41,280
we're kind of assembling and others are
1712
00:58:38,559 --> 00:58:42,720
thinking of questions um brian there was
1713
00:58:41,280 --> 00:58:45,200
a question that i know we talked about
1714
00:58:42,720 --> 00:58:46,000
and you and you kind of alluded to but
1715
00:58:45,200 --> 00:58:47,920
um
1716
00:58:46,000 --> 00:58:50,240
a question about how close the school
1717
00:58:47,920 --> 00:58:52,559
reported data populations align with
1718
00:58:50,240 --> 00:58:55,520
those um in this study i know it was way
1719
00:58:52,559 --> 00:58:56,640
off for your initial study um but what
1720
00:58:55,520 --> 00:58:58,880
um
1721
00:58:56,640 --> 00:59:00,240
how close did you get to
1722
00:58:58,880 --> 00:59:03,040
kind of
1723
00:59:00,240 --> 00:59:04,799
believing that those screening data were
1724
00:59:03,040 --> 00:59:07,119
aligned with what we're
1725
00:59:04,799 --> 00:59:08,640
seeing in population-based studies
1726
00:59:07,119 --> 00:59:10,400
yeah i'll launch that in two ways first
1727
00:59:08,640 --> 00:59:12,000
as the preface is often thinking about
1728
00:59:10,400 --> 00:59:13,359
the alternative and recognizing that
1729
00:59:12,000 --> 00:59:14,799
when you move things from a research
1730
00:59:13,359 --> 00:59:15,680
enterprise into clinic enterprise it's
1731
00:59:14,799 --> 00:59:17,599
messy
1732
00:59:15,680 --> 00:59:19,040
and so i would say though it's closer
1733
00:59:17,599 --> 00:59:21,040
when you look at our regional
1734
00:59:19,040 --> 00:59:23,119
school-based surveys
1735
00:59:21,040 --> 00:59:24,960
e-cigarette use is more like in tobacco
1736
00:59:23,119 --> 00:59:26,960
use overall more like in the
1737
00:59:24,960 --> 00:59:28,799
mid-teen range at this point which is
1738
00:59:26,960 --> 00:59:30,960
probably still another report
1739
00:59:28,799 --> 00:59:32,799
similarly for alcohol marijuana the
1740
00:59:30,960 --> 00:59:35,520
sexual activity though is interesting uh
1741
00:59:32,799 --> 00:59:37,040
is more and more aligned um so i would
1742
00:59:35,520 --> 00:59:38,880
say we've moved in the right direction
1743
00:59:37,040 --> 00:59:41,119
dramatically the final thing i think
1744
00:59:38,880 --> 00:59:44,319
about even if it doesn't perfectly align
1745
00:59:41,119 --> 00:59:46,160
with anonymous school-based surveys you
1746
00:59:44,319 --> 00:59:48,799
at least now have a population of teens
1747
00:59:46,160 --> 00:59:50,640
that are identifying that they use which
1748
00:59:48,799 --> 00:59:52,640
is probably a t a group of teens that
1749
00:59:50,640 --> 00:59:54,000
are more amenable to engaging in some
1750
00:59:52,640 --> 00:59:58,440
sort of treatment
1751
00:59:54,000 --> 00:59:58,440
or prevention-based kind of exercise
1752
01:00:00,400 --> 01:00:06,240
so to to back up a little bit so we
1753
01:00:03,760 --> 01:00:08,160
most of the folks on this call um are
1754
01:00:06,240 --> 01:00:10,240
researchers and we have three we have
1755
01:00:08,160 --> 01:00:12,720
three clinicians um
1756
01:00:10,240 --> 01:00:15,520
on our panel um so
1757
01:00:12,720 --> 01:00:16,799
as we're thinking about research um
1758
01:00:15,520 --> 01:00:19,119
you know
1759
01:00:16,799 --> 01:00:20,960
we sort of i i i think of and we have
1760
01:00:19,119 --> 01:00:22,720
another question as well about about
1761
01:00:20,960 --> 01:00:24,960
parents within a pediatric population
1762
01:00:22,720 --> 01:00:26,839
but there's kind of three users of these
1763
01:00:24,960 --> 01:00:29,359
data potentially there's there's the
1764
01:00:26,839 --> 01:00:32,319
patient um or the patient in the family
1765
01:00:29,359 --> 01:00:33,839
the caregiver um there's the clinician
1766
01:00:32,319 --> 01:00:36,559
and then there's the
1767
01:00:33,839 --> 01:00:37,920
then there's a potential the researcher
1768
01:00:36,559 --> 01:00:39,119
there's other masters right there's
1769
01:00:37,920 --> 01:00:40,319
there's uh
1770
01:00:39,119 --> 01:00:42,240
there's
1771
01:00:40,319 --> 01:00:43,680
the health system and there's billing
1772
01:00:42,240 --> 01:00:46,640
and there's quality right there's
1773
01:00:43,680 --> 01:00:48,559
there's a lot of uses for these data um
1774
01:00:46,640 --> 01:00:52,000
but how you know putting on your
1775
01:00:48,559 --> 01:00:54,640
clinician hats how um
1776
01:00:52,000 --> 01:00:56,319
how can we sort of think about
1777
01:00:54,640 --> 01:00:58,960
the questions that we're asking as
1778
01:00:56,319 --> 01:01:01,040
researchers um and make sure that what
1779
01:00:58,960 --> 01:01:01,920
we're asking is
1780
01:01:01,040 --> 01:01:03,839
um
1781
01:01:01,920 --> 01:01:07,280
and what we what we're hoping to see in
1782
01:01:03,839 --> 01:01:10,559
ehr data is is feasible and useful for
1783
01:01:07,280 --> 01:01:12,559
clinicians and and patients as well um
1784
01:01:10,559 --> 01:01:14,640
so i think i think you know
1785
01:01:12,559 --> 01:01:17,359
one of our goals is to increase the use
1786
01:01:14,640 --> 01:01:18,960
of ehr data and research um but we don't
1787
01:01:17,359 --> 01:01:21,280
want to do that um
1788
01:01:18,960 --> 01:01:22,720
to the detriment of of clinical
1789
01:01:21,280 --> 01:01:25,359
encounters to
1790
01:01:22,720 --> 01:01:26,880
you know to the detriment of clinicians
1791
01:01:25,359 --> 01:01:28,880
um and the work that they need to get
1792
01:01:26,880 --> 01:01:30,640
done and patient patient health outcomes
1793
01:01:28,880 --> 01:01:32,240
obviously
1794
01:01:30,640 --> 01:01:35,520
and that's kind of a big question does
1795
01:01:32,240 --> 01:01:35,520
anyone have any thoughts on it
1796
01:01:36,240 --> 01:01:39,920
well i can i can feel that but i'm going
1797
01:01:37,839 --> 01:01:41,920
to defer to mario and bob who are
1798
01:01:39,920 --> 01:01:43,440
smarter than me but i i think the um
1799
01:01:41,920 --> 01:01:45,520
what you need to do on the research side
1800
01:01:43,440 --> 01:01:46,559
so part of our role is i
1801
01:01:45,520 --> 01:01:48,400
you need to find people who multiple
1802
01:01:46,559 --> 01:01:50,000
hats who can bridge the gap so i think
1803
01:01:48,400 --> 01:01:51,839
if you're thinking you know clinical
1804
01:01:50,000 --> 01:01:53,200
based research one make sure that you're
1805
01:01:51,839 --> 01:01:55,200
falling in love with problem not
1806
01:01:53,200 --> 01:01:56,960
solutions and really helping discover
1807
01:01:55,200 --> 01:01:58,000
your problem by talking to your clinical
1808
01:01:56,960 --> 01:02:00,000
partners
1809
01:01:58,000 --> 01:02:01,920
and i think the other thing on the ehr
1810
01:02:00,000 --> 01:02:04,000
side is you need to find good partners
1811
01:02:01,920 --> 01:02:05,920
who are clinical information like mar
1812
01:02:04,000 --> 01:02:07,200
and i who can help you you can challenge
1813
01:02:05,920 --> 01:02:08,880
them but also can help you think about
1814
01:02:07,200 --> 01:02:11,520
what's feasible and what's not it's
1815
01:02:08,880 --> 01:02:12,880
gonna identify well you might wanna
1816
01:02:11,520 --> 01:02:14,240
focus on that but we've done that that's
1817
01:02:12,880 --> 01:02:16,240
not the best approach here's another
1818
01:02:14,240 --> 01:02:17,760
suggestion so i think it's really just
1819
01:02:16,240 --> 01:02:20,160
to summarize is finding those right
1820
01:02:17,760 --> 01:02:22,480
clinical partners uh to talk with and
1821
01:02:20,160 --> 01:02:23,680
really looking them as partners not that
1822
01:02:22,480 --> 01:02:25,520
you're going to tell them how to do
1823
01:02:23,680 --> 01:02:27,280
something so you can really fall in love
1824
01:02:25,520 --> 01:02:28,400
with the problem not your potential
1825
01:02:27,280 --> 01:02:31,119
solution
1826
01:02:28,400 --> 01:02:31,119
if that makes sense
1827
01:02:32,480 --> 01:02:36,240
yeah to add on to what brian just said
1828
01:02:35,440 --> 01:02:39,039
um
1829
01:02:36,240 --> 01:02:41,599
and that partnering part is uh
1830
01:02:39,039 --> 01:02:43,359
collaborating with patients uh
1831
01:02:41,599 --> 01:02:45,440
caregivers and clinicians actually
1832
01:02:43,359 --> 01:02:47,920
getting their input on
1833
01:02:45,440 --> 01:02:50,880
what they would like to see the outcomes
1834
01:02:47,920 --> 01:02:53,359
are what is important to them and
1835
01:02:50,880 --> 01:02:56,799
working with them to try to execute that
1836
01:02:53,359 --> 01:02:58,400
it's uh it's almost like you're
1837
01:02:56,799 --> 01:02:59,680
trying to like the
1838
01:02:58,400 --> 01:03:01,839
example that comes to mind is like the
1839
01:02:59,680 --> 01:03:03,200
delorean it looks cool it's pretty
1840
01:03:01,839 --> 01:03:05,440
outside of
1841
01:03:03,200 --> 01:03:08,720
time travel you know how much was it
1842
01:03:05,440 --> 01:03:10,559
utilized and how much was it uptake
1843
01:03:08,720 --> 01:03:12,799
from the general population so if you
1844
01:03:10,559 --> 01:03:14,000
can work with your stakeholders
1845
01:03:12,799 --> 01:03:17,039
to
1846
01:03:14,000 --> 01:03:18,720
create common goals and create uh
1847
01:03:17,039 --> 01:03:20,799
get what their
1848
01:03:18,720 --> 01:03:22,960
uh outcomes would uh would be what
1849
01:03:20,799 --> 01:03:24,559
they'd like to see then uh i believe you
1850
01:03:22,960 --> 01:03:26,960
get uh
1851
01:03:24,559 --> 01:03:29,039
greater access to uh to ehr and then
1852
01:03:26,960 --> 01:03:31,280
also
1853
01:03:29,039 --> 01:03:33,760
uh input and uh
1854
01:03:31,280 --> 01:03:35,760
and serviceability from uh from patients
1855
01:03:33,760 --> 01:03:38,559
and those providing uh
1856
01:03:35,760 --> 01:03:38,559
uh support to them
1857
01:03:39,839 --> 01:03:43,599
the only thing i'll add and i love the
1858
01:03:41,680 --> 01:03:45,680
way you deframed is multiple uses for
1859
01:03:43,599 --> 01:03:47,920
the ehr sarah i mean and that's part of
1860
01:03:45,680 --> 01:03:49,200
the problem too um you know is and we've
1861
01:03:47,920 --> 01:03:50,799
really had to focus at least in my
1862
01:03:49,200 --> 01:03:53,039
experience is the usability piece it's
1863
01:03:50,799 --> 01:03:54,799
got to be something that's easily usable
1864
01:03:53,039 --> 01:03:56,960
by the clinician otherwise you know the
1865
01:03:54,799 --> 01:03:58,319
stories we hear about burnout and people
1866
01:03:56,960 --> 01:04:00,240
have spending more screen time than
1867
01:03:58,319 --> 01:04:01,680
patient time i think what will continue
1868
01:04:00,240 --> 01:04:03,119
to be to be a problem and then as i
1869
01:04:01,680 --> 01:04:05,119
think further about it you know we think
1870
01:04:03,119 --> 01:04:06,640
about ehrs for individual patient care
1871
01:04:05,119 --> 01:04:09,039
right so the information in there has to
1872
01:04:06,640 --> 01:04:10,640
be adequate to deliver patient care
1873
01:04:09,039 --> 01:04:11,760
we've explored whether it's useful for
1874
01:04:10,640 --> 01:04:13,119
quality improvement can you get a
1875
01:04:11,760 --> 01:04:14,720
feedback loop in there enough so you can
1876
01:04:13,119 --> 01:04:16,720
see how well you're doing and i think
1877
01:04:14,720 --> 01:04:18,240
that's not quite ready yet i mean i
1878
01:04:16,720 --> 01:04:19,680
think it's getting better but not quite
1879
01:04:18,240 --> 01:04:21,280
ready then the third one is for research
1880
01:04:19,680 --> 01:04:22,799
can you actually generate data that will
1881
01:04:21,280 --> 01:04:24,880
give you generalizable knowledge that
1882
01:04:22,799 --> 01:04:26,559
you can apply to other populations i
1883
01:04:24,880 --> 01:04:28,400
think all three of those they're not at
1884
01:04:26,559 --> 01:04:30,799
odds with each other but but man you got
1885
01:04:28,400 --> 01:04:32,480
to sort of work to to get them all lined
1886
01:04:30,799 --> 01:04:33,680
up and not put more burden on the
1887
01:04:32,480 --> 01:04:36,240
clinician i think if you really want to
1888
01:04:33,680 --> 01:04:36,240
make this work
1889
01:04:38,880 --> 01:04:44,480
one other another question um
1890
01:04:42,480 --> 01:04:46,880
at what level do you think clinical
1891
01:04:44,480 --> 01:04:48,880
decision support is best scaled up after
1892
01:04:46,880 --> 01:04:50,319
testing at the health system level a
1893
01:04:48,880 --> 01:04:54,160
state level
1894
01:04:50,319 --> 01:04:56,799
um ehr vendor level um you know how much
1895
01:04:54,160 --> 01:04:59,680
do we need to know about what's working
1896
01:04:56,799 --> 01:05:01,760
um and with whom um and what sort of
1897
01:04:59,680 --> 01:05:03,680
what ehr
1898
01:05:01,760 --> 01:05:05,920
what health systems or what populations
1899
01:05:03,680 --> 01:05:09,760
or what clinician types
1900
01:05:05,920 --> 01:05:11,520
before we can start to to deploy this
1901
01:05:09,760 --> 01:05:13,280
more broadly and therefore kind of you
1902
01:05:11,520 --> 01:05:15,280
know start thinking about scaling up
1903
01:05:13,280 --> 01:05:16,960
some of these primary care based
1904
01:05:15,280 --> 01:05:20,319
interventions that are supported by
1905
01:05:16,960 --> 01:05:20,319
clinical decision support
1906
01:05:21,440 --> 01:05:25,680
i can jump in so this is uh actually one
1907
01:05:23,680 --> 01:05:28,000
of the areas of focus of one of our
1908
01:05:25,680 --> 01:05:30,079
funding opportunities and i highlighted
1909
01:05:28,000 --> 01:05:32,079
uh dr christopher harley's work uh
1910
01:05:30,079 --> 01:05:33,839
university of florida so
1911
01:05:32,079 --> 01:05:35,359
there really isn't a
1912
01:05:33,839 --> 01:05:37,280
right answer
1913
01:05:35,359 --> 01:05:39,599
of how you scale up and who you scale up
1914
01:05:37,280 --> 01:05:41,680
to do you start you know at the state
1915
01:05:39,599 --> 01:05:43,599
level uh do you work your
1916
01:05:41,680 --> 01:05:46,400
work your way down or do you start just
1917
01:05:43,599 --> 01:05:48,240
by trying to go across the street to the
1918
01:05:46,400 --> 01:05:50,880
primary care clinic
1919
01:05:48,240 --> 01:05:53,280
that's affiliated with uh your hospital
1920
01:05:50,880 --> 01:05:55,119
uh so there is no right answer the i
1921
01:05:53,280 --> 01:05:57,200
think uh one of the main tenants that
1922
01:05:55,119 --> 01:05:59,839
we're trying to get is one once you
1923
01:05:57,200 --> 01:06:00,799
piloted your clinical decision support
1924
01:05:59,839 --> 01:06:03,760
shows
1925
01:06:00,799 --> 01:06:06,000
show that it works in your local setting
1926
01:06:03,760 --> 01:06:08,319
has some benefit or even if you're
1927
01:06:06,000 --> 01:06:12,400
unsure if it has benefit that's another
1928
01:06:08,319 --> 01:06:14,160
opportunity for scaling is partner with
1929
01:06:12,400 --> 01:06:17,440
other collaborators your other
1930
01:06:14,160 --> 01:06:19,839
stakeholders who want to scale this
1931
01:06:17,440 --> 01:06:22,079
as researchers you know given time
1932
01:06:19,839 --> 01:06:24,000
effort budget you know do what is
1933
01:06:22,079 --> 01:06:26,160
allowed in what you're you're capable
1934
01:06:24,000 --> 01:06:27,280
and feel comfortable executing and then
1935
01:06:26,160 --> 01:06:29,680
from there
1936
01:06:27,280 --> 01:06:31,359
you know reporting on your outcomes
1937
01:06:29,680 --> 01:06:33,119
reporting on your results and then
1938
01:06:31,359 --> 01:06:36,000
sharing that information disseminating
1939
01:06:33,119 --> 01:06:37,440
it with not only uh peers but ourselves
1940
01:06:36,000 --> 01:06:39,039
so that we can get a sense of what
1941
01:06:37,440 --> 01:06:41,359
worked what didn't work and then hope
1942
01:06:39,039 --> 01:06:43,760
you can share lessons learned and then
1943
01:06:41,359 --> 01:06:47,839
from there someone can pivot on
1944
01:06:43,760 --> 01:06:47,839
on on your work so
1945
01:06:51,520 --> 01:06:54,640
great um thanks
1946
01:06:53,440 --> 01:06:56,720
um
1947
01:06:54,640 --> 01:06:59,200
maybe we might just have a question for
1948
01:06:56,720 --> 01:07:01,039
or time for one more um
1949
01:06:59,200 --> 01:07:02,960
so um
1950
01:07:01,039 --> 01:07:04,240
as we are um
1951
01:07:02,960 --> 01:07:06,160
there's been a lot of questions and i
1952
01:07:04,240 --> 01:07:06,960
think we're all still thinking about
1953
01:07:06,160 --> 01:07:10,319
this
1954
01:07:06,960 --> 01:07:12,319
um about the the relationship or how
1955
01:07:10,319 --> 01:07:14,160
we're using these tools and virtual
1956
01:07:12,319 --> 01:07:17,760
versus
1957
01:07:14,160 --> 01:07:19,359
in-person um in person settings so um
1958
01:07:17,760 --> 01:07:21,119
are there any is there anything that we
1959
01:07:19,359 --> 01:07:22,559
need to do differently and and brian
1960
01:07:21,119 --> 01:07:25,119
there's you know kind of some specific
1961
01:07:22,559 --> 01:07:26,640
questions for you about whether or not
1962
01:07:25,119 --> 01:07:29,039
your screening
1963
01:07:26,640 --> 01:07:31,039
was done in person or only during
1964
01:07:29,039 --> 01:07:32,240
in-person visits or if it's something
1965
01:07:31,039 --> 01:07:34,000
that can be
1966
01:07:32,240 --> 01:07:35,119
deployed in virtual care settings as
1967
01:07:34,000 --> 01:07:37,440
well
1968
01:07:35,119 --> 01:07:39,119
yeah it's a lot of great questions um
1969
01:07:37,440 --> 01:07:41,920
let me feel that in a couple of ways so
1970
01:07:39,119 --> 01:07:43,359
what we've um one of the big issues is
1971
01:07:41,920 --> 01:07:44,720
as we mentioned as i mentioned and the
1972
01:07:43,359 --> 01:07:46,640
comments are speaking to is the
1973
01:07:44,720 --> 01:07:48,640
confidentiality issue of how do you get
1974
01:07:46,640 --> 01:07:49,839
information from the teen electronically
1975
01:07:48,640 --> 01:07:51,760
ensuring
1976
01:07:49,839 --> 01:07:52,960
especially if it's remote and ensuring
1977
01:07:51,760 --> 01:07:54,960
it's not the parent who's completing
1978
01:07:52,960 --> 01:07:56,640
that content so we did our own pilot
1979
01:07:54,960 --> 01:07:59,119
studies to show that we couldn't rely on
1980
01:07:56,640 --> 01:08:01,280
sending this content ahead of time
1981
01:07:59,119 --> 01:08:02,640
because um and the stanford-based group
1982
01:08:01,280 --> 01:08:04,160
also identified this when they did
1983
01:08:02,640 --> 01:08:06,000
natural language processing to look at
1984
01:08:04,160 --> 01:08:07,920
the language coming back from supposedly
1985
01:08:06,000 --> 01:08:09,520
the teenager it was the parent who was
1986
01:08:07,920 --> 01:08:11,599
completing the content which is
1987
01:08:09,520 --> 01:08:12,720
frustrating because it's like
1988
01:08:11,599 --> 01:08:14,319
you know you think you're committed to
1989
01:08:12,720 --> 01:08:16,080
the teen it says team but it's actually
1990
01:08:14,319 --> 01:08:17,440
the mom dad responding back so there's
1991
01:08:16,080 --> 01:08:19,679
an intellectual dishonesty there that
1992
01:08:17,440 --> 01:08:21,040
you have to navigate um as a physician
1993
01:08:19,679 --> 01:08:23,359
as a health system
1994
01:08:21,040 --> 01:08:25,440
so what we did first is make sure we
1995
01:08:23,359 --> 01:08:27,279
have this completed when the individual
1996
01:08:25,440 --> 01:08:28,480
team comes into the office that was our
1997
01:08:27,279 --> 01:08:29,759
first approach because that was the only
1998
01:08:28,480 --> 01:08:31,600
way you could verify it was the team
1999
01:08:29,759 --> 01:08:33,520
actually completing this
2000
01:08:31,600 --> 01:08:35,520
now what we've done with an acceleration
2001
01:08:33,520 --> 01:08:37,520
because of pandemic and better services
2002
01:08:35,520 --> 01:08:39,839
for remote services better opportunities
2003
01:08:37,520 --> 01:08:41,679
and technology remote services
2004
01:08:39,839 --> 01:08:43,839
we've figured out
2005
01:08:41,679 --> 01:08:45,279
the proxy systems and making sure that
2006
01:08:43,839 --> 01:08:46,799
it's actually the team who's completing
2007
01:08:45,279 --> 01:08:48,640
the content and once we did that you
2008
01:08:46,799 --> 01:08:50,000
could verify that then we could send out
2009
01:08:48,640 --> 01:08:51,759
and open up opportunities to do
2010
01:08:50,000 --> 01:08:53,759
telehealth well visits where we're
2011
01:08:51,759 --> 01:08:54,880
actually kind of screening and capturing
2012
01:08:53,759 --> 01:08:57,120
this data
2013
01:08:54,880 --> 01:08:58,960
and i really um for those interested in
2014
01:08:57,120 --> 01:09:01,679
this is and i'm playing off of what uh
2015
01:08:58,960 --> 01:09:02,799
wilson had commented on it's not
2016
01:09:01,679 --> 01:09:04,400
one of the other reasons why you want to
2017
01:09:02,799 --> 01:09:05,679
find your collaborators ask them what
2018
01:09:04,400 --> 01:09:07,440
are the problems their facing so again
2019
01:09:05,679 --> 01:09:09,600
fall in love with problems not solutions
2020
01:09:07,440 --> 01:09:11,040
and bob had mentioned usability is so
2021
01:09:09,600 --> 01:09:13,120
important making sure you're building
2022
01:09:11,040 --> 01:09:15,040
solutions or we're helping other people
2023
01:09:13,120 --> 01:09:16,319
identify the solutions to really fit and
2024
01:09:15,040 --> 01:09:18,000
meet the needs
2025
01:09:16,319 --> 01:09:20,719
when we heard people saying that you
2026
01:09:18,000 --> 01:09:22,080
know talking to teens takes too long
2027
01:09:20,719 --> 01:09:23,679
we were like okay we're on to something
2028
01:09:22,080 --> 01:09:25,040
we can we can come up with we can do
2029
01:09:23,679 --> 01:09:26,560
time saving there and just get the right
2030
01:09:25,040 --> 01:09:27,920
information to them at the right time
2031
01:09:26,560 --> 01:09:30,880
which tomorrow's talking about the five
2032
01:09:27,920 --> 01:09:32,719
tenets of effective um ehr based
2033
01:09:30,880 --> 01:09:34,319
solutions and cds
2034
01:09:32,719 --> 01:09:35,759
so there it was through discussions that
2035
01:09:34,319 --> 01:09:36,799
we learned more about this problem so i
2036
01:09:35,759 --> 01:09:38,640
know i just answered kind of three
2037
01:09:36,799 --> 01:09:40,080
questions in the comments at once but
2038
01:09:38,640 --> 01:09:42,239
i'm happy to talk further anyway i left
2039
01:09:40,080 --> 01:09:45,600
my email at any time more about some of
2040
01:09:42,239 --> 01:09:45,600
these issues and i'll stop talking
2041
01:09:46,159 --> 01:09:50,239
thank you brian um and i know that um i
2042
01:09:48,960 --> 01:09:52,719
know that we all have a lot more to say
2043
01:09:50,239 --> 01:09:55,600
but we're gonna take a very quick five
2044
01:09:52,719 --> 01:09:56,400
minute break um grab some water um thank
2045
01:09:55,600 --> 01:09:58,960
you
2046
01:09:56,400 --> 01:10:00,880
bob mario and brian for um
2047
01:09:58,960 --> 01:10:03,280
for your um
2048
01:10:00,880 --> 01:10:06,320
for your contributions um and for your
2049
01:10:03,280 --> 01:10:08,640
um your time today and um yes feel free
2050
01:10:06,320 --> 01:10:10,239
to continue to ask questions in the chat
2051
01:10:08,640 --> 01:10:11,520
um and anything that we didn't get to we
2052
01:10:10,239 --> 01:10:14,320
will try to
2053
01:10:11,520 --> 01:10:16,480
um we'll try to get into our um
2054
01:10:14,320 --> 01:10:18,719
our summary um of our
2055
01:10:16,480 --> 01:10:20,000
of our um meeting that we'll be putting
2056
01:10:18,719 --> 01:10:21,840
together
2057
01:10:20,000 --> 01:10:23,280
um okay so we've got five minute break
2058
01:10:21,840 --> 01:10:24,640
um
2059
01:10:23,280 --> 01:10:26,159
we have a
2060
01:10:24,640 --> 01:10:29,600
uh
2061
01:10:26,159 --> 01:10:31,760
timer up on the screen so everyone can
2062
01:10:29,600 --> 01:10:33,920
run get some get some water stretch your
2063
01:10:31,760 --> 01:10:36,880
legs and we'll meet you back here in
2064
01:10:33,920 --> 01:10:36,880
five minutes thank you
2065
01:10:37,360 --> 01:10:40,880
like to welcome everybody back from
2066
01:10:38,800 --> 01:10:42,640
break the serene water picture has
2067
01:10:40,880 --> 01:10:44,880
disappeared
2068
01:10:42,640 --> 01:10:46,320
i will take over from there and welcome
2069
01:10:44,880 --> 01:10:48,320
you back to our second panel
2070
01:10:46,320 --> 01:10:49,840
transitioning from our first
2071
01:10:48,320 --> 01:10:51,920
we're now going to focus on examples of
2072
01:10:49,840 --> 01:10:54,400
research that have successfully used ehr
2073
01:10:51,920 --> 01:10:56,640
data in mental health pediatrics health
2074
01:10:54,400 --> 01:10:59,600
disparities substance use and veterans
2075
01:10:56,640 --> 01:11:01,360
health research so um as sarah did i'll
2076
01:10:59,600 --> 01:11:03,520
go ahead and introduce all the speakers
2077
01:11:01,360 --> 01:11:05,280
at the start and then you know feel free
2078
01:11:03,520 --> 01:11:06,880
to start dumping questions in the chat
2079
01:11:05,280 --> 01:11:08,400
and we'll have a opportunity for
2080
01:11:06,880 --> 01:11:10,080
discussion at the end
2081
01:11:08,400 --> 01:11:12,320
so our first speaker will be dr greg
2082
01:11:10,080 --> 01:11:14,400
simon dr simon is a psychiatrist and a
2083
01:11:12,320 --> 01:11:16,080
senior investigator at kaiser permanente
2084
01:11:14,400 --> 01:11:17,520
in washington
2085
01:11:16,080 --> 01:11:19,280
he leads the mental health research
2086
01:11:17,520 --> 01:11:21,280
network a consortium of research centers
2087
01:11:19,280 --> 01:11:22,880
affiliated with 13 large health systems
2088
01:11:21,280 --> 01:11:24,960
across the united states conducting
2089
01:11:22,880 --> 01:11:26,560
practical mental health research
2090
01:11:24,960 --> 01:11:28,560
next we'll hear from dr dina chisholm
2091
01:11:26,560 --> 01:11:30,159
who's a health services epidemiologist
2092
01:11:28,560 --> 01:11:32,159
and the director of the center for child
2093
01:11:30,159 --> 01:11:34,159
health equity and outcomes research at
2094
01:11:32,159 --> 01:11:36,239
abigail wexner research institute at
2095
01:11:34,159 --> 01:11:37,920
nationwide children's hospital
2096
01:11:36,239 --> 01:11:39,840
she's also the vice president of health
2097
01:11:37,920 --> 01:11:41,679
services research in the abigail wexner
2098
01:11:39,840 --> 01:11:43,520
research institute and a professor of
2099
01:11:41,679 --> 01:11:45,840
pediatrics at ohio state's college of
2100
01:11:43,520 --> 01:11:47,679
medicine and public health
2101
01:11:45,840 --> 01:11:49,920
following dr chisholm will be joined by
2102
01:11:47,679 --> 01:11:51,360
dr stacie sterling a research scientist
2103
01:11:49,920 --> 01:11:53,600
with kaiser permanente northern
2104
01:11:51,360 --> 01:11:54,880
california she's co-director for the
2105
01:11:53,600 --> 01:11:56,239
center for addiction and mental health
2106
01:11:54,880 --> 01:11:57,440
research and kaiser's division of
2107
01:11:56,239 --> 01:11:59,360
research
2108
01:11:57,440 --> 01:12:01,360
and finally we'll conclude this past
2109
01:11:59,360 --> 01:12:03,600
presentations with dr elizabeth
2110
01:12:01,360 --> 01:12:05,840
dr oliva is an investigator at the va
2111
01:12:03,600 --> 01:12:08,320
center for innovation to implementation
2112
01:12:05,840 --> 01:12:10,159
at the va palo alto healthcare system
2113
01:12:08,320 --> 01:12:12,640
and a senior evaluator for the va
2114
01:12:10,159 --> 01:12:15,280
program evaluation and research center
2115
01:12:12,640 --> 01:12:16,880
she is currently the va national opioid
2116
01:12:15,280 --> 01:12:19,040
overdose education and naloxone
2117
01:12:16,880 --> 01:12:21,440
distribution coordinator
2118
01:12:19,040 --> 01:12:23,360
so with that i will turn it over to dr
2119
01:12:21,440 --> 01:12:27,120
simon
2120
01:12:23,360 --> 01:12:32,320
thanks very much can you hear me okay
2121
01:12:27,120 --> 01:12:32,320
okay and i will share my screen here
2122
01:12:32,640 --> 01:12:35,640
and
2123
01:12:36,880 --> 01:12:43,199
taking a second let's see
2124
01:12:40,159 --> 01:12:45,600
i think we are okay and then
2125
01:12:43,199 --> 01:12:47,600
are you you know i will do the high risk
2126
01:12:45,600 --> 01:12:49,280
maneuver or switching to presentation
2127
01:12:47,600 --> 01:12:51,600
mode are you seeing the correct version
2128
01:12:49,280 --> 01:12:52,480
now or the other version
2129
01:12:51,600 --> 01:12:54,000
correct
2130
01:12:52,480 --> 01:12:56,640
okay good all right then i think we're
2131
01:12:54,000 --> 01:12:59,440
all good so thanks very much um i'm
2132
01:12:56,640 --> 01:13:01,280
going to uh talk today about uh using
2133
01:12:59,440 --> 01:13:02,880
what i call the sort of data exhaust of
2134
01:13:01,280 --> 01:13:04,320
health care i'm actually gonna you'll
2135
01:13:02,880 --> 01:13:05,760
i'll echo a few of the things that i
2136
01:13:04,320 --> 01:13:08,880
heard brian jensen say just a few
2137
01:13:05,760 --> 01:13:10,960
minutes ago um i'm talking about some of
2138
01:13:08,880 --> 01:13:12,320
our work using those sorts of data to
2139
01:13:10,960 --> 01:13:14,640
assess the mental health impact of
2140
01:13:12,320 --> 01:13:17,360
covid19 not because that's the primary
2141
01:13:14,640 --> 01:13:19,199
uh topic of this webinar but because i
2142
01:13:17,360 --> 01:13:21,199
think there's some nice cautionary tales
2143
01:13:19,199 --> 01:13:23,360
we can tell this was work done by our
2144
01:13:21,199 --> 01:13:24,800
mental health research network
2145
01:13:23,360 --> 01:13:26,159
which involves several large health
2146
01:13:24,800 --> 01:13:27,440
systems but i want to especially
2147
01:13:26,159 --> 01:13:28,800
acknowledge some of the people more
2148
01:13:27,440 --> 01:13:31,120
involved in the work i'll talk about
2149
01:13:28,800 --> 01:13:33,120
here rebecca rossum at health partners
2150
01:13:31,120 --> 01:13:35,520
brian amadani and henry ford and my
2151
01:13:33,120 --> 01:13:38,159
colleagues chris stewart and rob penfold
2152
01:13:35,520 --> 01:13:41,040
here at kp washington
2153
01:13:38,159 --> 01:13:42,880
so my main message is you know when you
2154
01:13:41,040 --> 01:13:44,800
ask about can you trust the data that
2155
01:13:42,880 --> 01:13:46,400
come out of electronic health records or
2156
01:13:44,800 --> 01:13:48,480
sometimes health insurance claims or
2157
01:13:46,400 --> 01:13:50,159
pharmacy dispensing data to measure
2158
01:13:48,480 --> 01:13:52,640
things about people's health the answer
2159
01:13:50,159 --> 01:13:54,880
is it depends um you often hear sort of
2160
01:13:52,640 --> 01:13:56,719
broad over generalizations
2161
01:13:54,880 --> 01:13:58,400
that you know big data will solve all
2162
01:13:56,719 --> 01:14:00,080
problems and a large sample size
2163
01:13:58,400 --> 01:14:01,920
overcomes all issues with measurement
2164
01:14:00,080 --> 01:14:03,520
error and on the other hand you'll hear
2165
01:14:01,920 --> 01:14:05,600
data from health records are garbage and
2166
01:14:03,520 --> 01:14:07,199
nonsense and you can't learn anything
2167
01:14:05,600 --> 01:14:09,040
and the truth is it's somewhere in
2168
01:14:07,199 --> 01:14:10,320
between but it's more complicated
2169
01:14:09,040 --> 01:14:12,800
because i think you need to get very
2170
01:14:10,320 --> 01:14:14,480
specific about that so along the lines
2171
01:14:12,800 --> 01:14:16,400
of getting specific i'm going to put in
2172
01:14:14,480 --> 01:14:18,480
a plug here for a paper that i wrote
2173
01:14:16,400 --> 01:14:20,960
along with some other people this was
2174
01:14:18,480 --> 01:14:23,199
came out of a national academy's
2175
01:14:20,960 --> 01:14:25,120
series of workshops which was focused
2176
01:14:23,199 --> 01:14:26,640
more on evaluating medical treatments
2177
01:14:25,120 --> 01:14:29,040
but i think the points we make in this
2178
01:14:26,640 --> 01:14:30,880
paper are relevant very relevant to what
2179
01:14:29,040 --> 01:14:32,960
we're talking about today when we ask
2180
01:14:30,880 --> 01:14:35,679
when can we trust so-called real world
2181
01:14:32,960 --> 01:14:37,520
data or the data exhausted healthcare to
2182
01:14:35,679 --> 01:14:38,800
accurately measure things about people's
2183
01:14:37,520 --> 01:14:41,360
health
2184
01:14:38,800 --> 01:14:43,040
and our point was that there is a clear
2185
01:14:41,360 --> 01:14:45,520
sort of you could say chain of custody
2186
01:14:43,040 --> 01:14:47,520
or series of steps if we begin with a
2187
01:14:45,520 --> 01:14:49,280
health state that a person experiences
2188
01:14:47,520 --> 01:14:51,040
and at the end of the day we have data
2189
01:14:49,280 --> 01:14:53,760
in a data warehouse we need to think
2190
01:14:51,040 --> 01:14:55,600
about each of the steps along the way
2191
01:14:53,760 --> 01:14:57,120
whether that person who experiences that
2192
01:14:55,600 --> 01:14:59,199
health state would actually present to
2193
01:14:57,120 --> 01:15:01,360
the health care system how that health
2194
01:14:59,199 --> 01:15:03,600
state would be diagnosed or recognized
2195
01:15:01,360 --> 01:15:05,760
by a health care provider how it would
2196
01:15:03,600 --> 01:15:07,679
be recorded and how that recording would
2197
01:15:05,760 --> 01:15:09,920
be influenced by the local sort of
2198
01:15:07,679 --> 01:15:12,000
characteristics the social cultural
2199
01:15:09,920 --> 01:15:13,600
economic and technical characteristics
2200
01:15:12,000 --> 01:15:15,600
of the practice setting
2201
01:15:13,600 --> 01:15:17,280
how those data would be extracted and
2202
01:15:15,600 --> 01:15:20,000
harmonized before they were put into
2203
01:15:17,280 --> 01:15:21,600
some research data warehouse or data set
2204
01:15:20,000 --> 01:15:23,360
so we need to consider each of those
2205
01:15:21,600 --> 01:15:25,120
steps and i'm going to illustrate that
2206
01:15:23,360 --> 01:15:27,120
process by talking about some of our
2207
01:15:25,120 --> 01:15:29,440
work on looking at the mental health
2208
01:15:27,120 --> 01:15:30,560
impacts of covert 19.
2209
01:15:29,440 --> 01:15:32,320
so
2210
01:15:30,560 --> 01:15:34,560
there were three big questions that we
2211
01:15:32,320 --> 01:15:37,920
were thinking about back sort of in mid
2212
01:15:34,560 --> 01:15:39,840
to late 2020 how did the covet 19 uh
2213
01:15:37,920 --> 01:15:42,800
pandemic affect overall levels of
2214
01:15:39,840 --> 01:15:44,800
psychological distress how did it affect
2215
01:15:42,800 --> 01:15:47,040
more in in more concerning the sort of
2216
01:15:44,800 --> 01:15:49,280
rate of mental health crises or suicide
2217
01:15:47,040 --> 01:15:51,120
attempts and then finally how did it
2218
01:15:49,280 --> 01:15:52,880
affect suicide deaths or suicide
2219
01:15:51,120 --> 01:15:55,679
mortality and i'm going to talk about
2220
01:15:52,880 --> 01:15:57,360
those actually in reverse order now
2221
01:15:55,679 --> 01:15:59,360
if we go back to those early days of the
2222
01:15:57,360 --> 01:16:01,520
pandemic some of you may remember there
2223
01:15:59,360 --> 01:16:04,000
were some very early alarms about the
2224
01:16:01,520 --> 01:16:06,080
idea that the covet 19 pandemic might
2225
01:16:04,000 --> 01:16:07,520
produce sort of an epidemic of suicide
2226
01:16:06,080 --> 01:16:09,520
this was a prominent paper that was
2227
01:16:07,520 --> 01:16:11,120
published you could see april 10th so
2228
01:16:09,520 --> 01:16:12,880
just a few weeks after the sort of
2229
01:16:11,120 --> 01:16:15,040
pandemic began to really break out
2230
01:16:12,880 --> 01:16:16,960
across the u.s and it was thought to be
2231
01:16:15,040 --> 01:16:19,040
a potential perfect storm
2232
01:16:16,960 --> 01:16:21,199
and as you may remember
2233
01:16:19,040 --> 01:16:22,880
it even got fairly political you know
2234
01:16:21,199 --> 01:16:25,679
this is from that medical journal the
2235
01:16:22,880 --> 01:16:28,000
wall street journal an editorial talking
2236
01:16:25,679 --> 01:16:29,679
about how so-called lockdowns or public
2237
01:16:28,000 --> 01:16:32,320
health measures to reduce the spread of
2238
01:16:29,679 --> 01:16:33,840
covert 19 might lead to an epidemic of
2239
01:16:32,320 --> 01:16:35,760
suicide
2240
01:16:33,840 --> 01:16:37,440
if you looked at the literature about
2241
01:16:35,760 --> 01:16:39,440
various kinds of sort of natural
2242
01:16:37,440 --> 01:16:42,239
disasters or other crises and how they
2243
01:16:39,440 --> 01:16:44,480
affected suicide mortality it actually
2244
01:16:42,239 --> 01:16:46,320
is mixed historically there's even some
2245
01:16:44,480 --> 01:16:48,320
evidence that sort of things like
2246
01:16:46,320 --> 01:16:50,800
earthquakes and floods things that may
2247
01:16:48,320 --> 01:16:52,480
affect a community may sometimes
2248
01:16:50,800 --> 01:16:54,239
actually be followed by decreased
2249
01:16:52,480 --> 01:16:56,239
especially in the short term suicide
2250
01:16:54,239 --> 01:16:58,480
mortality possibly because people feel
2251
01:16:56,239 --> 01:17:00,400
more connected to each other so when we
2252
01:16:58,480 --> 01:17:02,719
were interested in assessing this we
2253
01:17:00,400 --> 01:17:04,560
said what data can we get and that
2254
01:17:02,719 --> 01:17:06,320
naturally those would be data that our
2255
01:17:04,560 --> 01:17:08,159
health systems often
2256
01:17:06,320 --> 01:17:09,920
get from state health departments
2257
01:17:08,159 --> 01:17:11,920
because we've been doing ongoing work
2258
01:17:09,920 --> 01:17:14,560
looking at uh suicide mortality in these
2259
01:17:11,920 --> 01:17:16,480
health systems
2260
01:17:14,560 --> 01:17:18,640
so as many of you may know the sort of
2261
01:17:16,480 --> 01:17:20,320
so-called final mortality data that
2262
01:17:18,640 --> 01:17:21,920
passed from state health departments to
2263
01:17:20,320 --> 01:17:24,239
the center for disease control and come
2264
01:17:21,920 --> 01:17:26,400
back via the national death index are
2265
01:17:24,239 --> 01:17:28,880
typically delayed by up to 20 months
2266
01:17:26,400 --> 01:17:31,440
that means that 2020 data would not be
2267
01:17:28,880 --> 01:17:33,600
available until the fall of 2021 and we
2268
01:17:31,440 --> 01:17:35,040
would hope not to wait that long
2269
01:17:33,600 --> 01:17:37,120
several of the health systems in our
2270
01:17:35,040 --> 01:17:38,800
network had established relationships
2271
01:17:37,120 --> 01:17:40,320
with state departments of health to get
2272
01:17:38,800 --> 01:17:42,159
access to interim data which were
2273
01:17:40,320 --> 01:17:44,560
typically produced quarterly or even
2274
01:17:42,159 --> 01:17:46,800
monthly but we had some questions about
2275
01:17:44,560 --> 01:17:48,960
the timeliness or accuracy of those data
2276
01:17:46,800 --> 01:17:51,520
especially during the pandemic
2277
01:17:48,960 --> 01:17:53,120
so here we are in fall of 2020 and we're
2278
01:17:51,520 --> 01:17:54,960
looking at data from three healthcare
2279
01:17:53,120 --> 01:17:57,440
systems kaiser permanente washington
2280
01:17:54,960 --> 01:17:59,360
henry ford and health partners
2281
01:17:57,440 --> 01:18:01,520
and looking at what we see about the
2282
01:17:59,360 --> 01:18:03,280
number of suicide deaths per month in
2283
01:18:01,520 --> 01:18:04,560
each of those health care systems using
2284
01:18:03,280 --> 01:18:06,159
these data that each of these health
2285
01:18:04,560 --> 01:18:08,159
care systems receives from their
2286
01:18:06,159 --> 01:18:10,719
respective states from washington from
2287
01:18:08,159 --> 01:18:12,320
michigan and from minnesota
2288
01:18:10,719 --> 01:18:14,400
what you see here when you look at when
2289
01:18:12,320 --> 01:18:17,520
the pandemic was really taking off their
2290
01:18:14,400 --> 01:18:19,679
march april and may um certainly uh you
2291
01:18:17,520 --> 01:18:21,840
know you you don't see any evidence of
2292
01:18:19,679 --> 01:18:24,640
an increase it's possible that you see a
2293
01:18:21,840 --> 01:18:26,400
decrease in suicide mortality but also
2294
01:18:24,640 --> 01:18:28,080
what you see there is the data for the
2295
01:18:26,400 --> 01:18:30,560
most recent few months in each of those
2296
01:18:28,080 --> 01:18:31,760
places may really not be credible
2297
01:18:30,560 --> 01:18:33,600
certainly if we look at kaiser
2298
01:18:31,760 --> 01:18:35,199
permanente washington data for june of
2299
01:18:33,600 --> 01:18:37,360
2020 we say
2300
01:18:35,199 --> 01:18:39,120
we must have really incomplete capture
2301
01:18:37,360 --> 01:18:41,840
or if we look at henry ford data from
2302
01:18:39,120 --> 01:18:43,520
october we must have incomplete capture
2303
01:18:41,840 --> 01:18:46,080
the question is how believable are the
2304
01:18:43,520 --> 01:18:49,280
data from a few months back
2305
01:18:46,080 --> 01:18:51,280
so the next step we do is we look at
2306
01:18:49,280 --> 01:18:53,040
at kp washington what happens when we
2307
01:18:51,280 --> 01:18:54,400
look at the data from second quarter and
2308
01:18:53,040 --> 01:18:56,239
then the data from third quarter and
2309
01:18:54,400 --> 01:18:58,320
match them up with each other
2310
01:18:56,239 --> 01:19:00,239
and what we see here is and this is to
2311
01:18:58,320 --> 01:19:02,000
me a very interesting story i won't go
2312
01:19:00,239 --> 01:19:03,840
into the details of all the numbers
2313
01:19:02,000 --> 01:19:06,239
because that would take too long
2314
01:19:03,840 --> 01:19:08,400
but what we see here is that
2315
01:19:06,239 --> 01:19:09,440
when we look at the quarter three data
2316
01:19:08,400 --> 01:19:11,440
and and
2317
01:19:09,440 --> 01:19:13,600
cross check those against what we got
2318
01:19:11,440 --> 01:19:16,159
sort of preliminarily in quarter two we
2319
01:19:13,600 --> 01:19:18,080
see that the data on suicide mortality
2320
01:19:16,159 --> 01:19:20,480
look like they may not be complete for
2321
01:19:18,080 --> 01:19:22,640
three or four months back interestingly
2322
01:19:20,480 --> 01:19:24,560
the data on covet 19 deaths look like
2323
01:19:22,640 --> 01:19:26,320
they were really up to date and if you
2324
01:19:24,560 --> 01:19:29,040
look those total mortality numbers
2325
01:19:26,320 --> 01:19:31,040
hardly changed so we see here a very
2326
01:19:29,040 --> 01:19:33,760
important message that data regarding
2327
01:19:31,040 --> 01:19:35,679
suicide mortality especially seemed to
2328
01:19:33,760 --> 01:19:37,760
be delayed by a few months and really
2329
01:19:35,679 --> 01:19:40,480
are not trustworthy for the most recent
2330
01:19:37,760 --> 01:19:43,120
few months at least in 2020
2331
01:19:40,480 --> 01:19:46,000
and then final piece of that picture
2332
01:19:43,120 --> 01:19:48,960
these are data looking at final uh 2020
2333
01:19:46,000 --> 01:19:51,920
data that arrived in 2021 and how those
2334
01:19:48,960 --> 01:19:54,320
compared to fourth quarter 2020 data and
2335
01:19:51,920 --> 01:19:57,040
this is sort of with these uh uh what
2336
01:19:54,320 --> 01:19:59,199
the lines show is what proportion of
2337
01:19:57,040 --> 01:20:01,199
those deaths in the final data were
2338
01:19:59,199 --> 01:20:02,960
actually recorded in the interim data
2339
01:20:01,199 --> 01:20:05,440
for the fourth quarter by the sort of
2340
01:20:02,960 --> 01:20:07,679
broad category of cause of death
2341
01:20:05,440 --> 01:20:09,840
what we see is for most medical causes
2342
01:20:07,679 --> 01:20:12,239
of death they're relatively up to date
2343
01:20:09,840 --> 01:20:14,560
that means those lines stay near 100
2344
01:20:12,239 --> 01:20:15,840
almost out to the end of the year
2345
01:20:14,560 --> 01:20:17,840
deaths that were said to be due to
2346
01:20:15,840 --> 01:20:19,840
undetermined intent or maybe of interest
2347
01:20:17,840 --> 01:20:21,280
to this group especially accidental
2348
01:20:19,840 --> 01:20:22,960
poisonings which would include deaths
2349
01:20:21,280 --> 01:20:24,639
related to opioid overdose that was
2350
01:20:22,960 --> 01:20:26,880
considered to be accidental were
2351
01:20:24,639 --> 01:20:28,480
actually quite a bit delayed and suicide
2352
01:20:26,880 --> 01:20:30,159
or self-harm deaths are somewhere in
2353
01:20:28,480 --> 01:20:32,080
between
2354
01:20:30,159 --> 01:20:34,000
so what we see here is we certainly
2355
01:20:32,080 --> 01:20:36,159
found when we looked at those data no
2356
01:20:34,000 --> 01:20:37,840
evidence of increase we saw a potential
2357
01:20:36,159 --> 01:20:39,920
signal of decrease which we thought was
2358
01:20:37,840 --> 01:20:42,239
really not plausible when we dug into
2359
01:20:39,920 --> 01:20:43,920
the data we said we really don't have we
2360
01:20:42,239 --> 01:20:46,400
can't trust these up to the minute data
2361
01:20:43,920 --> 01:20:47,600
we need to wait and the final version of
2362
01:20:46,400 --> 01:20:48,960
the story
2363
01:20:47,600 --> 01:20:51,760
you know when this is a paper that was
2364
01:20:48,960 --> 01:20:53,440
published uh later in 2020 looking at
2365
01:20:51,760 --> 01:20:54,880
all across you know the data that were
2366
01:20:53,440 --> 01:20:57,199
available different countries you know
2367
01:20:54,880 --> 01:20:58,880
what suggests is the final story about
2368
01:20:57,199 --> 01:21:01,280
suicide mortality data during the
2369
01:20:58,880 --> 01:21:04,239
pandemic was it probably did not change
2370
01:21:01,280 --> 01:21:05,920
much at all anywhere um so going back to
2371
01:21:04,239 --> 01:21:08,159
that little picture i showed you you
2372
01:21:05,920 --> 01:21:10,480
know what we're saying here is when we
2373
01:21:08,159 --> 01:21:12,880
look at this step in the data generating
2374
01:21:10,480 --> 01:21:15,120
process how data were extracted and
2375
01:21:12,880 --> 01:21:16,880
harmonized especially those data from
2376
01:21:15,120 --> 01:21:19,120
health departments during the pandemic
2377
01:21:16,880 --> 01:21:21,440
we found that there was a sort of you
2378
01:21:19,120 --> 01:21:23,280
could say a change in the process or in
2379
01:21:21,440 --> 01:21:25,280
some ways a breakdown in the process
2380
01:21:23,280 --> 01:21:27,679
here that it was important for us to
2381
01:21:25,280 --> 01:21:30,639
recognize or we might have been misled
2382
01:21:27,679 --> 01:21:32,239
about what was really going on
2383
01:21:30,639 --> 01:21:33,920
so on to that second question the
2384
01:21:32,239 --> 01:21:35,440
effects of the pandemic on mental health
2385
01:21:33,920 --> 01:21:37,360
crises
2386
01:21:35,440 --> 01:21:40,239
this was an early report that got a fair
2387
01:21:37,360 --> 01:21:42,800
bit of attention um from the mmwr
2388
01:21:40,239 --> 01:21:44,960
looking at the proportion of emergency
2389
01:21:42,800 --> 01:21:47,440
department visits by adolescents that
2390
01:21:44,960 --> 01:21:49,199
had mental health diagnoses and this was
2391
01:21:47,440 --> 01:21:50,560
a report saying that the proportion of
2392
01:21:49,199 --> 01:21:52,400
emergency department visits with mental
2393
01:21:50,560 --> 01:21:54,159
health diagnoses had really bumped up
2394
01:21:52,400 --> 01:21:56,320
you can see this in this graph at the
2395
01:21:54,159 --> 01:21:58,080
bottom these are weeks during 2020 so
2396
01:21:56,320 --> 01:21:59,679
that's right about march april when the
2397
01:21:58,080 --> 01:22:01,440
pandemic took off
2398
01:21:59,679 --> 01:22:03,120
and a big bump in the proportion that
2399
01:22:01,440 --> 01:22:05,199
appeared to be due to mental health
2400
01:22:03,120 --> 01:22:06,159
which was sustained throughout the year
2401
01:22:05,199 --> 01:22:08,000
um
2402
01:22:06,159 --> 01:22:10,159
when we took a look at the data from our
2403
01:22:08,000 --> 01:22:12,800
health systems what we saw looking not
2404
01:22:10,159 --> 01:22:14,960
at the proportion but at the absolute uh
2405
01:22:12,800 --> 01:22:16,880
you know the the population rate the
2406
01:22:14,960 --> 01:22:19,120
population rate of mental health
2407
01:22:16,880 --> 01:22:21,679
emergency department visits we actually
2408
01:22:19,120 --> 01:22:25,280
see a big drop there you can see in
2409
01:22:21,679 --> 01:22:26,800
march april of 2020 some recovery
2410
01:22:25,280 --> 01:22:28,639
in some health systems up to the
2411
01:22:26,800 --> 01:22:30,880
previous level and some to a somewhat
2412
01:22:28,639 --> 01:22:33,120
below the previous level
2413
01:22:30,880 --> 01:22:35,520
so it seems to us there was a general
2414
01:22:33,120 --> 01:22:36,960
drop in emergency department utilization
2415
01:22:35,520 --> 01:22:39,040
there was a drop in mental health
2416
01:22:36,960 --> 01:22:40,400
utilization and the question in our
2417
01:22:39,040 --> 01:22:42,080
minds was
2418
01:22:40,400 --> 01:22:45,120
how can we say
2419
01:22:42,080 --> 01:22:48,960
whether mental health visits decreased
2420
01:22:45,120 --> 01:22:50,719
more or less than would be expected
2421
01:22:48,960 --> 01:22:53,679
and what we started to search around for
2422
01:22:50,719 --> 01:22:55,360
was what's the comparison condition
2423
01:22:53,679 --> 01:22:57,360
what's a type of visitation to the
2424
01:22:55,360 --> 01:22:59,199
emergency department that would not have
2425
01:22:57,360 --> 01:23:01,040
been affected by the pandemic that we
2426
01:22:59,199 --> 01:23:03,199
could use for sort of a difference in
2427
01:23:01,040 --> 01:23:06,000
difference design and to say what's our
2428
01:23:03,199 --> 01:23:07,440
sort of control or comparison group the
2429
01:23:06,000 --> 01:23:10,239
challenge was we really couldn't come up
2430
01:23:07,440 --> 01:23:12,080
with any when we looked we saw that uh
2431
01:23:10,239 --> 01:23:14,000
all visits to emergency departments
2432
01:23:12,080 --> 01:23:16,159
dramatically decreased during spring
2433
01:23:14,000 --> 01:23:18,320
2020 if we looked at visits for
2434
01:23:16,159 --> 01:23:19,600
accidents those dramatically decreased
2435
01:23:18,320 --> 01:23:21,120
some of that may have been people were
2436
01:23:19,600 --> 01:23:22,320
avoiding the emergency room or some of
2437
01:23:21,120 --> 01:23:24,560
that may have been people were driving
2438
01:23:22,320 --> 01:23:25,840
their cars less or going out less
2439
01:23:24,560 --> 01:23:27,440
and as many of you know even if we
2440
01:23:25,840 --> 01:23:29,920
looked at so-called serious medical
2441
01:23:27,440 --> 01:23:31,600
emergencies strokes and heart attacks
2442
01:23:29,920 --> 01:23:34,320
we don't think the pandemic probably
2443
01:23:31,600 --> 01:23:35,679
much decreased the true rate of strokes
2444
01:23:34,320 --> 01:23:37,760
and heart attacks but emergency
2445
01:23:35,679 --> 01:23:40,560
department visits decreased
2446
01:23:37,760 --> 01:23:42,560
so our conclusion was we really don't
2447
01:23:40,560 --> 01:23:44,480
think we can use data from emergency
2448
01:23:42,560 --> 01:23:47,120
department visits to say anything about
2449
01:23:44,480 --> 01:23:49,120
the true rate of mental health crises
2450
01:23:47,120 --> 01:23:50,960
that is the the health care data exhaust
2451
01:23:49,120 --> 01:23:52,159
don't really tell us about the true
2452
01:23:50,960 --> 01:23:53,920
health state
2453
01:23:52,159 --> 01:23:55,600
and this is a follow-up report from the
2454
01:23:53,920 --> 01:23:57,199
people at the cdc
2455
01:23:55,600 --> 01:23:58,560
showing essentially the same picture we
2456
01:23:57,199 --> 01:24:00,400
saw that if you look at emergency
2457
01:23:58,560 --> 01:24:03,760
department visits with various specific
2458
01:24:00,400 --> 01:24:05,679
mental health diagnoses throughout 2020
2459
01:24:03,760 --> 01:24:08,080
big drop in the spring
2460
01:24:05,679 --> 01:24:10,000
partial to full recovery but possibly
2461
01:24:08,080 --> 01:24:12,400
continuing at a somewhat lower rate
2462
01:24:10,000 --> 01:24:14,719
possibly reflecting or to my mind more
2463
01:24:12,400 --> 01:24:17,679
likely reflecting still avoidance of
2464
01:24:14,719 --> 01:24:19,520
emergency departments during the sort of
2465
01:24:17,679 --> 01:24:22,639
increases in the pandemic that happened
2466
01:24:19,520 --> 01:24:24,400
later in 2020
2467
01:24:22,639 --> 01:24:26,000
so in this case we look back here and
2468
01:24:24,400 --> 01:24:28,000
say this is where we think there was a
2469
01:24:26,000 --> 01:24:30,239
problem or an issue with our measurement
2470
01:24:28,000 --> 01:24:31,760
system that people were less likely to
2471
01:24:30,239 --> 01:24:34,159
present to the health care system
2472
01:24:31,760 --> 01:24:35,520
regardless so we really cannot use data
2473
01:24:34,159 --> 01:24:38,000
regarding emergency department
2474
01:24:35,520 --> 01:24:39,440
visitations there on the right hand side
2475
01:24:38,000 --> 01:24:41,440
to tell us anything about the true
2476
01:24:39,440 --> 01:24:43,040
health state or the actual rate of
2477
01:24:41,440 --> 01:24:44,880
mental health crises that people
2478
01:24:43,040 --> 01:24:46,560
experienced
2479
01:24:44,880 --> 01:24:47,520
the third question
2480
01:24:46,560 --> 01:24:50,400
about
2481
01:24:47,520 --> 01:24:52,000
overall rates of general psychological
2482
01:24:50,400 --> 01:24:53,280
distress because there's been a lot of
2483
01:24:52,000 --> 01:24:55,360
concern about the effects of the
2484
01:24:53,280 --> 01:24:56,800
pandemic on on sort of it's the general
2485
01:24:55,360 --> 01:24:58,719
mental health state of the american
2486
01:24:56,800 --> 01:24:59,920
public and maybe more especially in
2487
01:24:58,719 --> 01:25:01,120
teens
2488
01:24:59,920 --> 01:25:02,880
what happens if we look at various
2489
01:25:01,120 --> 01:25:05,120
indicators across our health systems
2490
01:25:02,880 --> 01:25:06,960
about mental health conditions
2491
01:25:05,120 --> 01:25:10,239
interestingly we see here rates of
2492
01:25:06,960 --> 01:25:11,760
depression diagnoses during 19 2019
2493
01:25:10,239 --> 01:25:13,760
through 2020.
2494
01:25:11,760 --> 01:25:15,199
what you see here is there is a dip
2495
01:25:13,760 --> 01:25:17,520
actually in rates of depression
2496
01:25:15,199 --> 01:25:19,440
diagnosis in spring of 2020 which
2497
01:25:17,520 --> 01:25:21,520
probably to my mind reflects more people
2498
01:25:19,440 --> 01:25:23,360
avoiding outpatient visits
2499
01:25:21,520 --> 01:25:25,440
interestingly that dip you know is
2500
01:25:23,360 --> 01:25:27,679
relatively small compared to the spike
2501
01:25:25,440 --> 01:25:29,520
at the end of 2019
2502
01:25:27,679 --> 01:25:31,440
once again here you need to be familiar
2503
01:25:29,520 --> 01:25:32,719
with sort of the the technical and to be
2504
01:25:31,440 --> 01:25:34,719
honest with you the financial
2505
01:25:32,719 --> 01:25:36,239
environment of health care which is you
2506
01:25:34,719 --> 01:25:38,320
typically see a big spike in the
2507
01:25:36,239 --> 01:25:40,159
recording of chronic condition diagnoses
2508
01:25:38,320 --> 01:25:42,000
and at the end of the year to maximize
2509
01:25:40,159 --> 01:25:44,560
medicare reimbursement we can talk more
2510
01:25:42,000 --> 01:25:46,000
about that if people want to
2511
01:25:44,560 --> 01:25:47,600
we look here at antidepressant
2512
01:25:46,000 --> 01:25:49,360
prescriptions and say could we use
2513
01:25:47,600 --> 01:25:51,920
antidepressant prescriptions as some
2514
01:25:49,360 --> 01:25:54,080
indicator we do see a blip in filling
2515
01:25:51,920 --> 01:25:56,560
antidepressant prescriptions right in
2516
01:25:54,080 --> 01:25:58,159
the spring there of 2020 but it turns
2517
01:25:56,560 --> 01:26:00,400
out what this is about when we look more
2518
01:25:58,159 --> 01:26:02,159
deeply is as you may remember in the
2519
01:26:00,400 --> 01:26:03,840
early weeks of the pandemic people were
2520
01:26:02,159 --> 01:26:05,760
concerned that pharmacies would close
2521
01:26:03,840 --> 01:26:07,440
down so people were actually instructed
2522
01:26:05,760 --> 01:26:09,920
to fill an extra month so they have a
2523
01:26:07,440 --> 01:26:11,760
supply on hand so this was sort of
2524
01:26:09,920 --> 01:26:13,520
hoarding maybe the wrong term to use
2525
01:26:11,760 --> 01:26:15,199
because that has a negative connotation
2526
01:26:13,520 --> 01:26:17,280
but this maybe have been appropriate
2527
01:26:15,199 --> 01:26:19,040
medication stockpiling and actually
2528
01:26:17,280 --> 01:26:20,480
following some fairly common advice
2529
01:26:19,040 --> 01:26:22,320
about what to do about your chronic
2530
01:26:20,480 --> 01:26:24,080
medications
2531
01:26:22,320 --> 01:26:26,320
if we look at psychotherapy visits we
2532
01:26:24,080 --> 01:26:28,480
see that those dropped
2533
01:26:26,320 --> 01:26:30,639
and had a partial recovery but the
2534
01:26:28,480 --> 01:26:32,639
question is is this really a disruption
2535
01:26:30,639 --> 01:26:34,639
in care people not getting care or is
2536
01:26:32,639 --> 01:26:36,639
this really a coding problem
2537
01:26:34,639 --> 01:26:39,040
when we dig deeper into this this is
2538
01:26:36,639 --> 01:26:41,520
data from kp washington only what we see
2539
01:26:39,040 --> 01:26:43,440
is you know a pretty dramatic decrease
2540
01:26:41,520 --> 01:26:46,320
in in-person psychotherapy visits there
2541
01:26:43,440 --> 01:26:48,159
in march april of 2020 pretty rapidly
2542
01:26:46,320 --> 01:26:49,679
replaced by telephone and video
2543
01:26:48,159 --> 01:26:52,080
encounters and actually going up to a
2544
01:26:49,679 --> 01:26:53,760
somewhat higher level
2545
01:26:52,080 --> 01:26:55,679
when we look across all the health
2546
01:26:53,760 --> 01:26:57,840
systems in our network we find that the
2547
01:26:55,679 --> 01:26:59,760
overall rates of mental health
2548
01:26:57,840 --> 01:27:02,639
utilization when we consider all visit
2549
01:26:59,760 --> 01:27:04,960
types remain fairly stable but one
2550
01:27:02,639 --> 01:27:07,040
interesting part of the story here is
2551
01:27:04,960 --> 01:27:08,800
that when we're monitoring visit rates
2552
01:27:07,040 --> 01:27:10,400
as an indicator of people's mental
2553
01:27:08,800 --> 01:27:11,520
health condition
2554
01:27:10,400 --> 01:27:12,560
it's important to recognize they're
2555
01:27:11,520 --> 01:27:13,920
important they're things we're not
2556
01:27:12,560 --> 01:27:16,400
measuring
2557
01:27:13,920 --> 01:27:17,920
if we um look take a cast a broader view
2558
01:27:16,400 --> 01:27:19,679
and say how often were these health
2559
01:27:17,920 --> 01:27:21,600
systems receiving new requests for
2560
01:27:19,679 --> 01:27:23,360
mental health services people saying i
2561
01:27:21,600 --> 01:27:25,600
need to see a doctor about mental health
2562
01:27:23,360 --> 01:27:27,600
problems i need to see a therapist
2563
01:27:25,600 --> 01:27:30,000
those actually increased quite a bit
2564
01:27:27,600 --> 01:27:32,080
during 2020 increased by 50 and in some
2565
01:27:30,000 --> 01:27:34,159
cases almost 100
2566
01:27:32,080 --> 01:27:35,280
we saw increased wait times and as many
2567
01:27:34,159 --> 01:27:36,960
of you know there's sort of been a
2568
01:27:35,280 --> 01:27:38,960
crisis in access to mental health
2569
01:27:36,960 --> 01:27:40,960
services across the country which
2570
01:27:38,960 --> 01:27:42,159
persists now even two years into the
2571
01:27:40,960 --> 01:27:45,679
pandemic
2572
01:27:42,159 --> 01:27:48,800
and my my point here is that if we had
2573
01:27:45,679 --> 01:27:51,440
been using use of mental health care as
2574
01:27:48,800 --> 01:27:53,840
a as a valid indicator of mental health
2575
01:27:51,440 --> 01:27:56,080
need what we would be ignoring is the
2576
01:27:53,840 --> 01:27:58,719
fact that the supply of mental health
2577
01:27:56,080 --> 01:28:00,400
visits is actually relatively fixed
2578
01:27:58,719 --> 01:28:02,159
even at the health system level
2579
01:28:00,400 --> 01:28:04,239
certainly say in one region of kaiser
2580
01:28:02,159 --> 01:28:05,840
permanente but even in the broader sense
2581
01:28:04,239 --> 01:28:07,679
at the national level there are only so
2582
01:28:05,840 --> 01:28:09,600
many providers they're only working so
2583
01:28:07,679 --> 01:28:11,360
many hours a week there are only so many
2584
01:28:09,600 --> 01:28:14,239
mental health visits that can possibly
2585
01:28:11,360 --> 01:28:17,440
occur so if a system is at or even above
2586
01:28:14,239 --> 01:28:19,920
capacity utilization is really not an
2587
01:28:17,440 --> 01:28:22,159
adequate measure of need or demand so
2588
01:28:19,920 --> 01:28:24,080
this is another example where
2589
01:28:22,159 --> 01:28:26,880
the presentation to the health care
2590
01:28:24,080 --> 01:28:28,960
system was a bottleneck and prevented us
2591
01:28:26,880 --> 01:28:30,880
we were just using data on visit rates
2592
01:28:28,960 --> 01:28:32,880
from observing an increase in need for
2593
01:28:30,880 --> 01:28:34,719
mental health services so we might have
2594
01:28:32,880 --> 01:28:36,719
been misled
2595
01:28:34,719 --> 01:28:38,560
so those are just three examples we may
2596
01:28:36,719 --> 01:28:41,120
have time to talk in the question period
2597
01:28:38,560 --> 01:28:43,920
more about those but you know as a as a
2598
01:28:41,120 --> 01:28:46,239
last word you know when when people try
2599
01:28:43,920 --> 01:28:47,920
to oversimplify you know you either can
2600
01:28:46,239 --> 01:28:49,600
or can't trust data that come from
2601
01:28:47,920 --> 01:28:51,199
electronic health records or insurance
2602
01:28:49,600 --> 01:28:53,280
claims to me that's that's
2603
01:28:51,199 --> 01:28:55,280
oversimplified the question is not can
2604
01:28:53,280 --> 01:28:57,840
we trust real world data the question is
2605
01:28:55,280 --> 01:28:59,600
when can we trust real world data and my
2606
01:28:57,840 --> 01:29:02,480
answer is it depends and it depends on
2607
01:28:59,600 --> 01:29:04,800
some really specific things so my advice
2608
01:29:02,480 --> 01:29:07,040
is when you're thinking about using you
2609
01:29:04,800 --> 01:29:08,159
know data from some data warehouse to to
2610
01:29:07,040 --> 01:29:10,000
actually give you an accurate
2611
01:29:08,159 --> 01:29:11,520
representation of a health state you
2612
01:29:10,000 --> 01:29:12,719
need to ask yourself
2613
01:29:11,520 --> 01:29:15,120
questions about each of those
2614
01:29:12,719 --> 01:29:17,199
intermediate steps along the way
2615
01:29:15,120 --> 01:29:19,199
so i will stop there so we can get on to
2616
01:29:17,199 --> 01:29:21,920
our other presentations and i'll look in
2617
01:29:19,199 --> 01:29:24,000
the chat for your questions thanks
2618
01:29:21,920 --> 01:29:27,040
thanks greg that was great um i have a
2619
01:29:24,000 --> 01:29:29,440
lot of questions about them for the end
2620
01:29:27,040 --> 01:29:31,840
and now i'll turn it over to dr deana
2621
01:29:29,440 --> 01:29:31,840
chisholm
2622
01:29:34,080 --> 01:29:38,880
i'm going to talk about
2623
01:29:36,960 --> 01:29:40,080
electronic medical record used in
2624
01:29:38,880 --> 01:29:42,639
research from a little different
2625
01:29:40,080 --> 01:29:45,920
perspective um i
2626
01:29:42,639 --> 01:29:49,120
do a lot of work in the space of health
2627
01:29:45,920 --> 01:29:52,800
equity and within that space think a lot
2628
01:29:49,120 --> 01:29:55,600
about the interactions between social
2629
01:29:52,800 --> 01:29:57,199
factors and health factors including
2630
01:29:55,600 --> 01:29:58,800
health services utilization and
2631
01:29:57,199 --> 01:29:59,679
including outcomes including substance
2632
01:29:58,800 --> 01:30:00,800
use
2633
01:29:59,679 --> 01:30:02,400
so what i
2634
01:30:00,800 --> 01:30:04,480
want to talk a little bit about is some
2635
01:30:02,400 --> 01:30:06,480
work that has tried to
2636
01:30:04,480 --> 01:30:09,440
look at how we get all of those pieces
2637
01:30:06,480 --> 01:30:11,120
of information inside and
2638
01:30:09,440 --> 01:30:12,719
and ehr
2639
01:30:11,120 --> 01:30:14,960
so
2640
01:30:12,719 --> 01:30:16,639
starting with that um
2641
01:30:14,960 --> 01:30:19,679
we at nationwide children's hospital
2642
01:30:16,639 --> 01:30:21,440
decided around 2018 that we needed to
2643
01:30:19,679 --> 01:30:24,400
think really hard about integrating
2644
01:30:21,440 --> 01:30:26,800
social determinants of health into our
2645
01:30:24,400 --> 01:30:28,320
electronic health record we use epic
2646
01:30:26,800 --> 01:30:30,719
which is of course one of the more
2647
01:30:28,320 --> 01:30:33,840
commonly used systems um and at the time
2648
01:30:30,719 --> 01:30:35,280
we did it epic did not have a module for
2649
01:30:33,840 --> 01:30:36,800
social determinants of health that was
2650
01:30:35,280 --> 01:30:38,400
broadly in use
2651
01:30:36,800 --> 01:30:40,639
so we designed one
2652
01:30:38,400 --> 01:30:42,880
put together a team that included
2653
01:30:40,639 --> 01:30:44,960
clinicians and social workers and
2654
01:30:42,880 --> 01:30:47,040
members of the community and researchers
2655
01:30:44,960 --> 01:30:49,040
and pulled questions out of a bunch of
2656
01:30:47,040 --> 01:30:50,639
different tools because nobody loved any
2657
01:30:49,040 --> 01:30:51,760
one tool that existed on the market at
2658
01:30:50,639 --> 01:30:54,000
the time
2659
01:30:51,760 --> 01:30:54,880
and came up with basically a four item
2660
01:30:54,000 --> 01:30:56,960
screen
2661
01:30:54,880 --> 01:30:58,960
which focused on
2662
01:30:56,960 --> 01:31:01,199
housing food
2663
01:30:58,960 --> 01:31:03,440
transportation and utilities four
2664
01:31:01,199 --> 01:31:05,760
questions one on each of those topics
2665
01:31:03,440 --> 01:31:08,239
and then if you answered yes on any of
2666
01:31:05,760 --> 01:31:10,719
those topics you got a
2667
01:31:08,239 --> 01:31:13,120
follow-on question that basically asked
2668
01:31:10,719 --> 01:31:14,880
is this a quest problem today so the
2669
01:31:13,120 --> 01:31:17,199
questions were the general questions
2670
01:31:14,880 --> 01:31:19,280
looked over 12 month period but then if
2671
01:31:17,199 --> 01:31:21,840
you said yes over the 12 month period
2672
01:31:19,280 --> 01:31:24,159
you got a detailed question that says is
2673
01:31:21,840 --> 01:31:26,159
this a problem right now and that
2674
01:31:24,159 --> 01:31:29,520
question really determined how we
2675
01:31:26,159 --> 01:31:30,880
responded to the data there was a talk
2676
01:31:29,520 --> 01:31:33,760
about you know how do you collect this
2677
01:31:30,880 --> 01:31:36,639
data this was collected uh at the time
2678
01:31:33,760 --> 01:31:39,600
primarily in uh outpatient ambulatory
2679
01:31:36,639 --> 01:31:41,840
clinic settings primary care um and done
2680
01:31:39,600 --> 01:31:43,679
on tablets
2681
01:31:41,840 --> 01:31:45,600
that either the parent or the teen could
2682
01:31:43,679 --> 01:31:47,199
do because some of these questions like
2683
01:31:45,600 --> 01:31:49,840
you know are you worried about being
2684
01:31:47,199 --> 01:31:51,840
evicted your teen may or may not know is
2685
01:31:49,840 --> 01:31:55,040
actually a rationale to have parents
2686
01:31:51,840 --> 01:31:56,400
collect some of this information
2687
01:31:55,040 --> 01:31:59,360
so
2688
01:31:56,400 --> 01:32:02,960
when you look at what the rates we were
2689
01:31:59,360 --> 01:32:06,239
getting of these uh questions were
2690
01:32:02,960 --> 01:32:08,960
we saw that about 12 percent said they
2691
01:32:06,239 --> 01:32:10,719
had within the past 12 months
2692
01:32:08,960 --> 01:32:12,639
at least one of those problems and you
2693
01:32:10,719 --> 01:32:14,080
can see that food insecurity was the
2694
01:32:12,639 --> 01:32:16,080
most commonly
2695
01:32:14,080 --> 01:32:17,679
uh espoused need
2696
01:32:16,080 --> 01:32:19,199
and then of those who said they had a
2697
01:32:17,679 --> 01:32:21,199
general need what percentage of them
2698
01:32:19,199 --> 01:32:23,040
said they had a need today
2699
01:32:21,199 --> 01:32:24,880
about 28
2700
01:32:23,040 --> 01:32:26,480
and again you can see that food was the
2701
01:32:24,880 --> 01:32:29,280
one that was the most
2702
01:32:26,480 --> 01:32:31,040
likely to have an immediate need this is
2703
01:32:29,280 --> 01:32:33,679
data from june
2704
01:32:31,040 --> 01:32:35,840
2018 to 2019. we have the
2705
01:32:33,679 --> 01:32:37,040
um more recent data but i pulled this
2706
01:32:35,840 --> 01:32:38,560
out of a paper that i'm going to share
2707
01:32:37,040 --> 01:32:42,480
some other numbers from so i want to
2708
01:32:38,560 --> 01:32:44,480
stay consistent in the period
2709
01:32:42,480 --> 01:32:47,360
so when i said the response to the
2710
01:32:44,480 --> 01:32:50,080
urgency question determined what we did
2711
01:32:47,360 --> 01:32:52,480
i say that because if they said yes to
2712
01:32:50,080 --> 01:32:54,400
an urgent to a general need so i've had
2713
01:32:52,480 --> 01:32:57,280
a need in the past 12 months they got a
2714
01:32:54,400 --> 01:32:59,360
research a resource sheet that was
2715
01:32:57,280 --> 01:33:01,600
generated directly out of the ehr
2716
01:32:59,360 --> 01:33:04,000
directly in the after visit summary
2717
01:33:01,600 --> 01:33:06,159
process so anybody who had yes checked
2718
01:33:04,000 --> 01:33:08,159
on any of those four questions got a
2719
01:33:06,159 --> 01:33:10,239
resource needs sheep printed out that
2720
01:33:08,159 --> 01:33:12,080
was specific to
2721
01:33:10,239 --> 01:33:14,400
the part of town they lived in or the
2722
01:33:12,080 --> 01:33:15,840
city that they lived in and to their
2723
01:33:14,400 --> 01:33:18,239
language
2724
01:33:15,840 --> 01:33:19,280
for the four languages that we generated
2725
01:33:18,239 --> 01:33:21,120
these in
2726
01:33:19,280 --> 01:33:23,199
we also were able to do translations for
2727
01:33:21,120 --> 01:33:26,239
other languages but we picked top four
2728
01:33:23,199 --> 01:33:27,679
which was more than 80 of our population
2729
01:33:26,239 --> 01:33:29,120
to
2730
01:33:27,679 --> 01:33:31,360
give these needs to
2731
01:33:29,120 --> 01:33:32,800
if they said they had an urgent need
2732
01:33:31,360 --> 01:33:34,880
they got the resource sheet but they
2733
01:33:32,800 --> 01:33:38,320
also got a referral to
2734
01:33:34,880 --> 01:33:39,520
social work to have somebody either talk
2735
01:33:38,320 --> 01:33:41,679
to them on the phone while they were
2736
01:33:39,520 --> 01:33:43,520
there in that visit or if they couldn't
2737
01:33:41,679 --> 01:33:44,719
talk to them on the phone it's also like
2738
01:33:43,520 --> 01:33:46,880
physically there to come and talk to
2739
01:33:44,719 --> 01:33:48,560
them physically there or to schedule a
2740
01:33:46,880 --> 01:33:50,880
time to have a follow-up call within the
2741
01:33:48,560 --> 01:33:52,239
next three days about their needs so
2742
01:33:50,880 --> 01:33:53,360
this got
2743
01:33:52,239 --> 01:33:56,400
really
2744
01:33:53,360 --> 01:33:58,719
um embedded in the clinical
2745
01:33:56,400 --> 01:34:01,040
processes but of course i'm a health
2746
01:33:58,719 --> 01:34:02,320
services researcher so as much as i was
2747
01:34:01,040 --> 01:34:04,719
excited about it being part of our
2748
01:34:02,320 --> 01:34:06,080
clinical processes i wanted to see how
2749
01:34:04,719 --> 01:34:08,320
it could help us understand what was
2750
01:34:06,080 --> 01:34:12,239
going on in our
2751
01:34:08,320 --> 01:34:14,080
population from a analytic perspective
2752
01:34:12,239 --> 01:34:16,400
so one of the papers that we did out of
2753
01:34:14,080 --> 01:34:18,320
this work was looking at social needs
2754
01:34:16,400 --> 01:34:20,080
data and looking at how it was
2755
01:34:18,320 --> 01:34:22,239
associated with
2756
01:34:20,080 --> 01:34:23,040
use of healthcare
2757
01:34:22,239 --> 01:34:24,639
so
2758
01:34:23,040 --> 01:34:26,800
over that time period that i presented
2759
01:34:24,639 --> 01:34:30,480
those numbers from at the beginning that
2760
01:34:26,800 --> 01:34:31,360
was just under 60 000 screens
2761
01:34:30,480 --> 01:34:33,679
and
2762
01:34:31,360 --> 01:34:35,440
that represented the fact that even
2763
01:34:33,679 --> 01:34:37,520
though that was a little over 12 months
2764
01:34:35,440 --> 01:34:39,120
there was a roll in so the first couple
2765
01:34:37,520 --> 01:34:41,199
of months it was just one or two clinics
2766
01:34:39,120 --> 01:34:42,719
and then three or four clinics so this
2767
01:34:41,199 --> 01:34:45,440
is a little smaller than the number of
2768
01:34:42,719 --> 01:34:48,400
patients with a period but again wanted
2769
01:34:45,440 --> 01:34:50,800
to be consistent with the data i shared
2770
01:34:48,400 --> 01:34:52,159
so we removed the patients who were out
2771
01:34:50,800 --> 01:34:53,280
of state because we figured if they
2772
01:34:52,159 --> 01:34:54,800
needed more care they were probably
2773
01:34:53,280 --> 01:34:56,400
going to get it at home
2774
01:34:54,800 --> 01:34:58,719
we removed ones where we didn't have
2775
01:34:56,400 --> 01:35:00,719
enough demographic information we
2776
01:34:58,719 --> 01:35:03,199
removed foster care because
2777
01:35:00,719 --> 01:35:05,199
it's unclear whether their social needs
2778
01:35:03,199 --> 01:35:06,880
were associated with their primary
2779
01:35:05,199 --> 01:35:09,440
parent or their foster parent and how
2780
01:35:06,880 --> 01:35:10,800
that might be changing frequently and
2781
01:35:09,440 --> 01:35:13,199
then we did
2782
01:35:10,800 --> 01:35:15,360
uh removed a few for just trying to make
2783
01:35:13,199 --> 01:35:17,520
sure we didn't incidentally identify any
2784
01:35:15,360 --> 01:35:18,480
patients based on their pair so we ended
2785
01:35:17,520 --> 01:35:20,080
up with about
2786
01:35:18,480 --> 01:35:22,639
56 000
2787
01:35:20,080 --> 01:35:24,239
youth in our analyses
2788
01:35:22,639 --> 01:35:25,760
and what we saw was if we said we
2789
01:35:24,239 --> 01:35:29,280
started with the index visit where we
2790
01:35:25,760 --> 01:35:31,760
did a screener we did that once a year
2791
01:35:29,280 --> 01:35:34,880
and we looked at their healthcare
2792
01:35:31,760 --> 01:35:37,520
utilization in the six months following
2793
01:35:34,880 --> 01:35:40,080
that index visit what we saw was the
2794
01:35:37,520 --> 01:35:42,639
youth with social needs were
2795
01:35:40,080 --> 01:35:44,480
more likely to have an ed visit in six
2796
01:35:42,639 --> 01:35:47,840
months following that visit and more
2797
01:35:44,480 --> 01:35:50,400
likely to be admitted inpatient in the
2798
01:35:47,840 --> 01:35:52,320
six months post that visit so that tells
2799
01:35:50,400 --> 01:35:54,320
us that collecting that information
2800
01:35:52,320 --> 01:35:57,360
while valuable for
2801
01:35:54,320 --> 01:35:59,280
um supporting uh
2802
01:35:57,360 --> 01:36:02,719
social assistance
2803
01:35:59,280 --> 01:36:05,600
uh is also a predictor for understanding
2804
01:36:02,719 --> 01:36:07,840
populations that need more support in
2805
01:36:05,600 --> 01:36:10,080
more ways to reduce healthcare
2806
01:36:07,840 --> 01:36:11,840
utilization that is not the most
2807
01:36:10,080 --> 01:36:14,000
efficient or effective way to provide
2808
01:36:11,840 --> 01:36:16,880
care
2809
01:36:14,000 --> 01:36:18,960
similarly when we looked at well child
2810
01:36:16,880 --> 01:36:20,880
visits what we saw was those with a
2811
01:36:18,960 --> 01:36:23,440
social need were significantly less
2812
01:36:20,880 --> 01:36:26,000
likely to
2813
01:36:23,440 --> 01:36:28,159
have a well child visit in the 12 month
2814
01:36:26,000 --> 01:36:30,000
in the six months following now since
2815
01:36:28,159 --> 01:36:31,520
most of these were done at primary care
2816
01:36:30,000 --> 01:36:33,360
visits you could say well they probably
2817
01:36:31,520 --> 01:36:34,880
didn't need another visit since this is
2818
01:36:33,360 --> 01:36:36,639
six months later
2819
01:36:34,880 --> 01:36:39,119
but we believe that these are children
2820
01:36:36,639 --> 01:36:40,560
who have needs so it shouldn't be a
2821
01:36:39,119 --> 01:36:41,600
surprise that they would come back in
2822
01:36:40,560 --> 01:36:43,920
six months
2823
01:36:41,600 --> 01:36:46,239
what we saw though is that that number
2824
01:36:43,920 --> 01:36:47,840
is lower which means we need to be doing
2825
01:36:46,239 --> 01:36:49,840
continuing to do a better job of
2826
01:36:47,840 --> 01:36:51,760
identifying needs at those index visits
2827
01:36:49,840 --> 01:36:54,400
because we're going to be less likely to
2828
01:36:51,760 --> 01:36:56,320
see them quickly
2829
01:36:54,400 --> 01:36:57,600
so this helped us to start and think
2830
01:36:56,320 --> 01:36:58,800
about
2831
01:36:57,600 --> 01:37:01,440
why
2832
01:36:58,800 --> 01:37:03,520
embedding social factors in the
2833
01:37:01,440 --> 01:37:06,320
electronic health record with the
2834
01:37:03,520 --> 01:37:08,000
healthcare utilization data has value it
2835
01:37:06,320 --> 01:37:11,600
has value for
2836
01:37:08,000 --> 01:37:13,760
care delivery and it has value for
2837
01:37:11,600 --> 01:37:16,080
intervention development and it has
2838
01:37:13,760 --> 01:37:19,199
value for predictive health services
2839
01:37:16,080 --> 01:37:22,320
research type stuff
2840
01:37:19,199 --> 01:37:25,040
now we have since uh
2841
01:37:22,320 --> 01:37:28,320
switched to using the epic foundation
2842
01:37:25,040 --> 01:37:31,360
screening questions uh these are
2843
01:37:28,320 --> 01:37:32,960
um embedded in the standard epic module
2844
01:37:31,360 --> 01:37:34,639
they're different than our questions we
2845
01:37:32,960 --> 01:37:36,159
don't necessarily love them as much as
2846
01:37:34,639 --> 01:37:39,280
we loved our questions that's because we
2847
01:37:36,159 --> 01:37:42,400
didn't lovingly create them ourselves um
2848
01:37:39,280 --> 01:37:44,400
the value of them though is that many
2849
01:37:42,400 --> 01:37:46,800
organizations that are doing this type
2850
01:37:44,400 --> 01:37:48,719
of screening are going to be using these
2851
01:37:46,800 --> 01:37:50,880
specific sets of questions so now we get
2852
01:37:48,719 --> 01:37:53,520
a chance to not just be stuck doing
2853
01:37:50,880 --> 01:37:55,199
single site emr studies
2854
01:37:53,520 --> 01:37:58,239
but really being able to look at
2855
01:37:55,199 --> 01:38:00,480
harmonization across data that will
2856
01:37:58,239 --> 01:38:02,960
allow us to do
2857
01:38:00,480 --> 01:38:06,239
larger studies that will allow us to
2858
01:38:02,960 --> 01:38:09,159
either identify rarer behaviors
2859
01:38:06,239 --> 01:38:11,600
or to be able to do better analysis in
2860
01:38:09,159 --> 01:38:13,840
subpopulations that we don't have large
2861
01:38:11,600 --> 01:38:15,920
numbers of in any single site which is
2862
01:38:13,840 --> 01:38:18,480
really important to an equity researcher
2863
01:38:15,920 --> 01:38:20,960
who hates the fact that we frequently
2864
01:38:18,480 --> 01:38:23,280
can't look at specific racial ethnic
2865
01:38:20,960 --> 01:38:24,320
populations because no one site has a
2866
01:38:23,280 --> 01:38:25,920
sufficient
2867
01:38:24,320 --> 01:38:27,280
sample size
2868
01:38:25,920 --> 01:38:31,199
another thing that's interesting about
2869
01:38:27,280 --> 01:38:34,239
this is that this built into epic
2870
01:38:31,199 --> 01:38:36,639
um and every time a clinician opens the
2871
01:38:34,239 --> 01:38:38,960
landing page for a patient their social
2872
01:38:36,639 --> 01:38:41,199
determinants data appears
2873
01:38:38,960 --> 01:38:44,400
and they see this big circle that says
2874
01:38:41,199 --> 01:38:46,960
what their social needs are so if a
2875
01:38:44,400 --> 01:38:48,480
child has serious social needs lots of
2876
01:38:46,960 --> 01:38:49,920
social needs are going to see a big red
2877
01:38:48,480 --> 01:38:51,360
circle
2878
01:38:49,920 --> 01:38:52,719
what does that mean
2879
01:38:51,360 --> 01:38:54,719
does that mean the doc's going to spend
2880
01:38:52,719 --> 01:38:56,159
some extra time with that patient does
2881
01:38:54,719 --> 01:38:57,920
that mean they're going to make sure
2882
01:38:56,159 --> 01:38:59,920
there's a social worker available when
2883
01:38:57,920 --> 01:39:01,920
that patient comes in doesn't mean
2884
01:38:59,920 --> 01:39:04,239
they're going to
2885
01:39:01,920 --> 01:39:06,000
sigh and be annoyed that this is going
2886
01:39:04,239 --> 01:39:08,000
to be a longer visit than they want are
2887
01:39:06,000 --> 01:39:09,600
they going to start with negative
2888
01:39:08,000 --> 01:39:12,159
expectations about this patient and
2889
01:39:09,600 --> 01:39:14,320
their needs there's two sides to that
2890
01:39:12,159 --> 01:39:16,480
coin and it's a researchable question
2891
01:39:14,320 --> 01:39:18,159
that um we'll certainly need to look at
2892
01:39:16,480 --> 01:39:19,679
in the future
2893
01:39:18,159 --> 01:39:22,239
so i want to talk real quickly about
2894
01:39:19,679 --> 01:39:23,679
another social determinant that is less
2895
01:39:22,239 --> 01:39:25,600
likely to be asked about you know those
2896
01:39:23,679 --> 01:39:28,000
for transportation housing food
2897
01:39:25,600 --> 01:39:30,800
utilities are pretty standard types of
2898
01:39:28,000 --> 01:39:30,800
social determinants
2899
01:39:31,040 --> 01:39:36,560
the
2900
01:39:32,639 --> 01:39:38,480
issue of mass incarceration of high
2901
01:39:36,560 --> 01:39:40,320
levels of justice involvement in
2902
01:39:38,480 --> 01:39:42,239
children particularly children in racial
2903
01:39:40,320 --> 01:39:43,920
ethnic minority populations
2904
01:39:42,239 --> 01:39:45,760
has
2905
01:39:43,920 --> 01:39:47,360
a meaningful impact on health but it's
2906
01:39:45,760 --> 01:39:49,840
really hard to study because nobody has
2907
01:39:47,360 --> 01:39:52,639
the numbers so what we wanted to see is
2908
01:39:49,840 --> 01:39:54,400
can we figure this out using an emr
2909
01:39:52,639 --> 01:39:56,000
so what we wanted to know was how many
2910
01:39:54,400 --> 01:39:58,080
children seen in our institution have a
2911
01:39:56,000 --> 01:40:00,320
history of an incarcerated parent is
2912
01:39:58,080 --> 01:40:02,480
that number changing over time
2913
01:40:00,320 --> 01:40:04,320
and what health challenges do these
2914
01:40:02,480 --> 01:40:06,840
youth face
2915
01:40:04,320 --> 01:40:09,520
so what we did
2916
01:40:06,840 --> 01:40:12,239
was use the
2917
01:40:09,520 --> 01:40:13,840
emr but not using the coded fields that
2918
01:40:12,239 --> 01:40:15,760
we created because we hadn't decided
2919
01:40:13,840 --> 01:40:18,239
that that was one of our questions but
2920
01:40:15,760 --> 01:40:21,360
using natural language processing
2921
01:40:18,239 --> 01:40:25,360
through the clinical notes to identify
2922
01:40:21,360 --> 01:40:27,040
key words that might be associated with
2923
01:40:25,360 --> 01:40:29,199
experiences with the justice system
2924
01:40:27,040 --> 01:40:32,239
whether self or whether an incarcerated
2925
01:40:29,199 --> 01:40:35,440
parent or a guardian
2926
01:40:32,239 --> 01:40:37,679
so we developed a set of keywords and
2927
01:40:35,440 --> 01:40:41,199
used a natural language processor to run
2928
01:40:37,679 --> 01:40:43,360
through our epic system between 2006 and
2929
01:40:41,199 --> 01:40:46,159
2020
2930
01:40:43,360 --> 01:40:49,679
and what you can see is just looking at
2931
01:40:46,159 --> 01:40:51,920
the probability of a word associated
2932
01:40:49,679 --> 01:40:55,600
with incarceration showing up in our
2933
01:40:51,920 --> 01:40:57,840
records it has shot up dramatically um
2934
01:40:55,600 --> 01:40:59,360
over the past 15 years
2935
01:40:57,840 --> 01:41:01,360
so you know that's something that we
2936
01:40:59,360 --> 01:41:02,719
wouldn't have otherwise known
2937
01:41:01,360 --> 01:41:04,159
maybe there might be some anecdotal
2938
01:41:02,719 --> 01:41:06,239
thoughts but this is some data that says
2939
01:41:04,159 --> 01:41:08,000
hey there's really something going on
2940
01:41:06,239 --> 01:41:09,600
here does that mean the docs are more
2941
01:41:08,000 --> 01:41:10,800
likely to be talking about that today
2942
01:41:09,600 --> 01:41:13,679
than they were
2943
01:41:10,800 --> 01:41:16,480
10 15 years ago maybe so we can't really
2944
01:41:13,679 --> 01:41:18,159
tease that out but we can tease out that
2945
01:41:16,480 --> 01:41:20,719
there's more than a little bit of it
2946
01:41:18,159 --> 01:41:20,719
going on
2947
01:41:20,880 --> 01:41:27,840
when we linked that data from the nlp
2948
01:41:23,760 --> 01:41:30,239
to the data in the medical record
2949
01:41:27,840 --> 01:41:32,639
for utilization what we saw kind of
2950
01:41:30,239 --> 01:41:34,239
dropped our jaws a little bit
2951
01:41:32,639 --> 01:41:35,199
and i know this might be a little small
2952
01:41:34,239 --> 01:41:37,440
to see
2953
01:41:35,199 --> 01:41:40,080
but when you look at for example
2954
01:41:37,440 --> 01:41:41,679
youth with alcohol disorder related
2955
01:41:40,080 --> 01:41:43,840
diagnoses
2956
01:41:41,679 --> 01:41:46,480
within the
2957
01:41:43,840 --> 01:41:50,400
children who had a correctional word in
2958
01:41:46,480 --> 01:41:52,080
their ehr about 0.37 percent had
2959
01:41:50,400 --> 01:41:55,920
alcohol disorder
2960
01:41:52,080 --> 01:41:58,800
across all the patients in that
2961
01:41:55,920 --> 01:42:00,639
set of records it was about 0.02
2962
01:41:58,800 --> 01:42:02,560
and to understand what that means is
2963
01:42:00,639 --> 01:42:04,639
that 43
2964
01:42:02,560 --> 01:42:06,800
of the children over that time period
2965
01:42:04,639 --> 01:42:08,159
that had an alcohol disorder related
2966
01:42:06,800 --> 01:42:10,719
diagnosis
2967
01:42:08,159 --> 01:42:11,760
in their record had a correctional
2968
01:42:10,719 --> 01:42:12,840
keyword
2969
01:42:11,760 --> 01:42:15,840
in their
2970
01:42:12,840 --> 01:42:18,000
diagnosis so that 42 if you look at
2971
01:42:15,840 --> 01:42:20,880
cannabis 66
2972
01:42:18,000 --> 01:42:22,960
if you look at broader substance abuse
2973
01:42:20,880 --> 01:42:26,239
diagnosis 54
2974
01:42:22,960 --> 01:42:27,440
so this small group of
2975
01:42:26,239 --> 01:42:29,679
children
2976
01:42:27,440 --> 01:42:32,000
making up a huge percentage of our youth
2977
01:42:29,679 --> 01:42:33,440
who had substance abuse
2978
01:42:32,000 --> 01:42:36,000
issues
2979
01:42:33,440 --> 01:42:37,679
um and i haven't highlighted and read
2980
01:42:36,000 --> 01:42:39,360
post-traumatic stress because seeing
2981
01:42:37,679 --> 01:42:41,040
your parent arrested having a parent
2982
01:42:39,360 --> 01:42:43,040
taken out of your house being arrested
2983
01:42:41,040 --> 01:42:44,239
yourself is a traumatic experience
2984
01:42:43,040 --> 01:42:46,159
um so
2985
01:42:44,239 --> 01:42:48,480
not surprisingly
2986
01:42:46,159 --> 01:42:50,480
um you know almost 50 percent of our
2987
01:42:48,480 --> 01:42:53,520
youth with post-traumatic stress
2988
01:42:50,480 --> 01:42:56,719
diagnosis were also um had a
2989
01:42:53,520 --> 01:42:58,239
correctional keyword in their record
2990
01:42:56,719 --> 01:42:59,600
now you might say well what does that
2991
01:42:58,239 --> 01:43:01,440
mean correctional keyword probably
2992
01:42:59,600 --> 01:43:03,040
doesn't mean anything at all
2993
01:43:01,440 --> 01:43:05,920
we did a thousand records we went
2994
01:43:03,040 --> 01:43:09,119
through them read them by hand
2995
01:43:05,920 --> 01:43:11,440
and saw that the misclassification
2996
01:43:09,119 --> 01:43:15,199
was around 17
2997
01:43:11,440 --> 01:43:17,280
so of that 1000 about 17
2998
01:43:15,199 --> 01:43:18,880
about 173
2999
01:43:17,280 --> 01:43:20,800
did not have any evidence so these are
3000
01:43:18,880 --> 01:43:22,239
people who might have said something
3001
01:43:20,800 --> 01:43:25,600
like they were afraid of being
3002
01:43:22,239 --> 01:43:27,840
incarcerated a few of them were
3003
01:43:25,600 --> 01:43:29,760
like a car incarcerated appendix or
3004
01:43:27,840 --> 01:43:31,280
something like that so
3005
01:43:29,760 --> 01:43:33,520
those got
3006
01:43:31,280 --> 01:43:35,920
pulled out but even just using keywords
3007
01:43:33,520 --> 01:43:38,800
we were able to have
3008
01:43:35,920 --> 01:43:41,119
about 83
3009
01:43:38,800 --> 01:43:43,760
or 87 rather
3010
01:43:41,119 --> 01:43:45,119
validity we took the next level
3011
01:43:43,760 --> 01:43:48,400
and we took
3012
01:43:45,119 --> 01:43:50,800
7 500 records and did all of them coded
3013
01:43:48,400 --> 01:43:53,040
out by reading them by hand and used
3014
01:43:50,800 --> 01:43:56,320
those to train a
3015
01:43:53,040 --> 01:43:59,440
uh machine learning predictive model uh
3016
01:43:56,320 --> 01:44:02,400
to identify um and what you can see
3017
01:43:59,440 --> 01:44:03,360
on here is that we went from our model
3018
01:44:02,400 --> 01:44:06,400
having
3019
01:44:03,360 --> 01:44:08,480
this level of predictiveness using this
3020
01:44:06,400 --> 01:44:10,880
approach similar to an roc curve i won't
3021
01:44:08,480 --> 01:44:12,880
go into a bunch of detail about it uh
3022
01:44:10,880 --> 01:44:16,000
but moving up to
3023
01:44:12,880 --> 01:44:18,639
a really high level of predictive value
3024
01:44:16,000 --> 01:44:20,800
so this is a way without even training
3025
01:44:18,639 --> 01:44:22,239
everybody on doing something new
3026
01:44:20,800 --> 01:44:23,440
without adding questions and going
3027
01:44:22,239 --> 01:44:24,960
through the whole process that we go
3028
01:44:23,440 --> 01:44:27,119
through to add questions to say we can
3029
01:44:24,960 --> 01:44:28,560
use the data that's already there in a
3030
01:44:27,119 --> 01:44:31,440
way that predicts
3031
01:44:28,560 --> 01:44:33,360
a outcome that predicts health
3032
01:44:31,440 --> 01:44:34,719
and helps us to identify people who we
3033
01:44:33,360 --> 01:44:37,199
would want to
3034
01:44:34,719 --> 01:44:39,760
catch early and intervene with before it
3035
01:44:37,199 --> 01:44:42,159
gets to that point
3036
01:44:39,760 --> 01:44:44,159
so i'd say that the
3037
01:44:42,159 --> 01:44:46,880
electronic medical record has to be part
3038
01:44:44,159 --> 01:44:49,600
of how we think about not just
3039
01:44:46,880 --> 01:44:51,840
outcomes research or
3040
01:44:49,600 --> 01:44:53,520
utilization research but really the
3041
01:44:51,840 --> 01:44:55,119
kinds of social research that allow us
3042
01:44:53,520 --> 01:44:56,560
to think about health at a population
3043
01:44:55,119 --> 01:44:58,560
level
3044
01:44:56,560 --> 01:45:00,719
ehrs are increasingly being used to
3045
01:44:58,560 --> 01:45:03,119
capture social determinants of health we
3046
01:45:00,719 --> 01:45:05,920
believe that that data can be used to
3047
01:45:03,119 --> 01:45:08,480
guide care and to study predictors and
3048
01:45:05,920 --> 01:45:10,560
outcomes and that even when that data is
3049
01:45:08,480 --> 01:45:12,639
not collected in coded fields natural
3050
01:45:10,560 --> 01:45:15,280
language processing can help to find
3051
01:45:12,639 --> 01:45:16,560
information that matters in text-based
3052
01:45:15,280 --> 01:45:19,040
notes
3053
01:45:16,560 --> 01:45:21,679
so i will close with that just want to
3054
01:45:19,040 --> 01:45:22,719
thank an amazing group of colleagues who
3055
01:45:21,679 --> 01:45:26,000
have been
3056
01:45:22,719 --> 01:45:28,320
uh part of this work um specifically
3057
01:45:26,000 --> 01:45:30,320
shout out to samantha buck the paper
3058
01:45:28,320 --> 01:45:33,760
that we that i showed at the end with
3059
01:45:30,320 --> 01:45:34,560
the roc curve was published today
3060
01:45:33,760 --> 01:45:36,320
and
3061
01:45:34,560 --> 01:45:38,400
she's the first author on that a former
3062
01:45:36,320 --> 01:45:41,440
postdoc at nationwide children's now at
3063
01:45:38,400 --> 01:45:43,520
university cinematic um and also to rose
3064
01:45:41,440 --> 01:45:45,840
hardy a former postdoc who was the first
3065
01:45:43,520 --> 01:45:49,440
author on the utilization paper
3066
01:45:45,840 --> 01:45:49,440
so i will stop there thank you
3067
01:45:49,920 --> 01:45:53,440
great thank you and congratulations on
3068
01:45:51,920 --> 01:45:56,760
that publication i look forward to
3069
01:45:53,440 --> 01:45:56,760
reading it
3070
01:45:58,400 --> 01:46:02,880
oop dr cece sperling will be our next
3071
01:46:01,440 --> 01:46:05,360
speaker
3072
01:46:02,880 --> 01:46:05,360
i'm sorry
3073
01:46:05,840 --> 01:46:10,080
great okay
3074
01:46:07,440 --> 01:46:12,400
uh well thank you and i'm gonna share
3075
01:46:10,080 --> 01:46:15,280
some of the you know a few examples
3076
01:46:12,400 --> 01:46:18,159
of how we have used the ehr at kaiser
3077
01:46:15,280 --> 01:46:21,040
permanente northern california to
3078
01:46:18,159 --> 01:46:23,360
create tools to help further the
3079
01:46:21,040 --> 01:46:26,159
integration of prevention and early
3080
01:46:23,360 --> 01:46:28,560
intervention efforts and then some of
3081
01:46:26,159 --> 01:46:31,199
the ways that we have been able to study
3082
01:46:28,560 --> 01:46:31,199
these efforts
3083
01:46:32,080 --> 01:46:35,840
so a little bit of context this is
3084
01:46:33,920 --> 01:46:37,920
kaiser permanente northern california
3085
01:46:35,840 --> 01:46:41,840
and we're a large integrated healthcare
3086
01:46:37,920 --> 01:46:44,480
delivery system we have many members
3087
01:46:41,840 --> 01:46:47,360
4.5 million about a third of the
3088
01:46:44,480 --> 01:46:49,600
northern california region's population
3089
01:46:47,360 --> 01:46:52,400
it's a very diverse membership
3090
01:46:49,600 --> 01:46:54,960
in many different ways
3091
01:46:52,400 --> 01:46:57,199
it's an integrated system so we have
3092
01:46:54,960 --> 01:46:59,199
carved in mental health psychiatry and
3093
01:46:57,199 --> 01:47:02,719
specialty addiction medicine
3094
01:46:59,199 --> 01:47:03,920
treatment programs um and i think uh
3095
01:47:02,719 --> 01:47:06,639
important
3096
01:47:03,920 --> 01:47:10,960
to our conversation today a very mature
3097
01:47:06,639 --> 01:47:12,880
robust ehr and embedded research with
3098
01:47:10,960 --> 01:47:15,600
robust database
3099
01:47:12,880 --> 01:47:15,600
infrastructure
3100
01:47:17,119 --> 01:47:20,320
so the first project that i'm going to
3101
01:47:18,880 --> 01:47:22,320
be talking about today is one where
3102
01:47:20,320 --> 01:47:24,480
we've used machine learning and
3103
01:47:22,320 --> 01:47:26,719
electronic health record data to develop
3104
01:47:24,480 --> 01:47:30,320
a predictive model of adolescent
3105
01:47:26,719 --> 01:47:30,320
substance use development
3106
01:47:30,639 --> 01:47:34,800
and this was a study funded by the
3107
01:47:32,400 --> 01:47:37,280
conrad and hilton foundations adolescent
3108
01:47:34,800 --> 01:47:39,760
early intervention initiative and our
3109
01:47:37,280 --> 01:47:41,760
aim was to develop and validate a
3110
01:47:39,760 --> 01:47:44,080
predictive model of adolescent substance
3111
01:47:41,760 --> 01:47:47,360
use problem development and we
3112
01:47:44,080 --> 01:47:48,320
collaborated with teams from three other
3113
01:47:47,360 --> 01:47:50,719
very
3114
01:47:48,320 --> 01:47:52,960
geographically diverse health care
3115
01:47:50,719 --> 01:47:54,719
systems you see those here kaiser
3116
01:47:52,960 --> 01:47:56,960
permanente hawaii
3117
01:47:54,719 --> 01:47:58,800
kaiser permanente i am
3118
01:47:56,960 --> 01:48:01,440
northern california of course geisinger
3119
01:47:58,800 --> 01:48:03,679
health system in rural pennsylvania and
3120
01:48:01,440 --> 01:48:05,280
henry ford health system in metropolitan
3121
01:48:03,679 --> 01:48:08,400
detroit
3122
01:48:05,280 --> 01:48:10,000
and we identified over 40 000 birth
3123
01:48:08,400 --> 01:48:13,199
cohorts where we had both the
3124
01:48:10,000 --> 01:48:15,679
adolescents and their mothers data and
3125
01:48:13,199 --> 01:48:18,679
who had continuous membership since
3126
01:48:15,679 --> 01:48:18,679
birth
3127
01:48:19,520 --> 01:48:24,000
and working with a variety of clinical
3128
01:48:22,000 --> 01:48:25,840
experts in our systems such as
3129
01:48:24,000 --> 01:48:28,239
developmental pediatricians and
3130
01:48:25,840 --> 01:48:30,880
psychologists we identified a large
3131
01:48:28,239 --> 01:48:33,840
group of potential candidate variables
3132
01:48:30,880 --> 01:48:36,480
to look at
3133
01:48:33,840 --> 01:48:39,360
we used cox regression models for
3134
01:48:36,480 --> 01:48:41,520
survival analyses and we built the
3135
01:48:39,360 --> 01:48:44,480
models using kaiser permanente northern
3136
01:48:41,520 --> 01:48:47,119
california data and then evaluated them
3137
01:48:44,480 --> 01:48:49,520
using data from the other health systems
3138
01:48:47,119 --> 01:48:52,239
and we created two sets of models a
3139
01:48:49,520 --> 01:48:54,159
baseline model that examined factors
3140
01:48:52,239 --> 01:48:55,760
occurring in childhood prior to
3141
01:48:54,159 --> 01:48:56,880
adolescent
3142
01:48:55,760 --> 01:48:59,440
and then
3143
01:48:56,880 --> 01:49:02,000
maternal factors occurring before
3144
01:48:59,440 --> 01:49:04,239
age 12 and then we created models that
3145
01:49:02,000 --> 01:49:07,280
really took into account time varying
3146
01:49:04,239 --> 01:49:09,840
predictors occurring between 12 and 18
3147
01:49:07,280 --> 01:49:11,199
because of course exposures that may
3148
01:49:09,840 --> 01:49:12,560
influence
3149
01:49:11,199 --> 01:49:14,960
the development of substance use
3150
01:49:12,560 --> 01:49:18,400
problems you know continue to occur
3151
01:49:14,960 --> 01:49:18,400
occur throughout adelaide
3152
01:49:20,000 --> 01:49:25,360
so we created the baseline model here
3153
01:49:22,320 --> 01:49:28,080
you can see some of the child and mother
3154
01:49:25,360 --> 01:49:30,880
level factors occurring before age 12
3155
01:49:28,080 --> 01:49:34,800
that we found to increase the risk of
3156
01:49:30,880 --> 01:49:34,800
developing a substance use problem
3157
01:49:35,119 --> 01:49:39,599
and then informed by
3158
01:49:37,440 --> 01:49:41,840
that baseline
3159
01:49:39,599 --> 01:49:43,760
model we developed time varying models
3160
01:49:41,840 --> 01:49:46,000
examining predictors significant in the
3161
01:49:43,760 --> 01:49:48,560
baseline model and also factors
3162
01:49:46,000 --> 01:49:51,199
occurring throughout adolescence and the
3163
01:49:48,560 --> 01:49:53,679
scope and duration of the ehr data we
3164
01:49:51,199 --> 01:49:56,239
had from these birth cohorts really
3165
01:49:53,679 --> 01:49:59,679
allowed us to examine the chronology of
3166
01:49:56,239 --> 01:50:02,159
risk exposure and problem development so
3167
01:49:59,679 --> 01:50:05,760
we looked at having the impact of each
3168
01:50:02,159 --> 01:50:08,239
of these risk factors prior to age 12
3169
01:50:05,760 --> 01:50:09,599
after age 12 and then an incident
3170
01:50:08,239 --> 01:50:12,159
diagnosis
3171
01:50:09,599 --> 01:50:16,320
only in the three months prior to
3172
01:50:12,159 --> 01:50:16,320
their substance use problem diagnosis
3173
01:50:17,760 --> 01:50:23,760
and we created categories of exposures
3174
01:50:21,119 --> 01:50:26,880
based on when they occurred and whether
3175
01:50:23,760 --> 01:50:28,719
they persisted over time so early
3176
01:50:26,880 --> 01:50:29,760
early persistent
3177
01:50:28,719 --> 01:50:32,320
late
3178
01:50:29,760 --> 01:50:34,800
early persistent and recent and late and
3179
01:50:32,320 --> 01:50:34,800
recent
3180
01:50:36,400 --> 01:50:40,639
and we identified a number of
3181
01:50:38,320 --> 01:50:42,239
significant predictors at both the child
3182
01:50:40,639 --> 01:50:44,239
and maternal level
3183
01:50:42,239 --> 01:50:45,119
um looking at these
3184
01:50:44,239 --> 01:50:47,199
as
3185
01:50:45,119 --> 01:50:48,159
researchers or clinicians in this field
3186
01:50:47,199 --> 01:50:50,639
they
3187
01:50:48,159 --> 01:50:53,280
may seem intuitive but it's been nice to
3188
01:50:50,639 --> 01:50:56,080
be able to add some empirical support to
3189
01:50:53,280 --> 01:50:58,800
what we see clinically and anecdotally
3190
01:50:56,080 --> 01:51:01,360
and hopefully provide some evidence that
3191
01:50:58,800 --> 01:51:05,400
can be useful for clinicians working on
3192
01:51:01,360 --> 01:51:05,400
the pediatric front lines
3193
01:51:06,159 --> 01:51:11,360
and we've now taken these findings from
3194
01:51:09,040 --> 01:51:13,280
this predictive modeling work and
3195
01:51:11,360 --> 01:51:15,840
working in collaboration with the team
3196
01:51:13,280 --> 01:51:18,239
from the partnership to end addiction we
3197
01:51:15,840 --> 01:51:20,800
conducted focus groups around the
3198
01:51:18,239 --> 01:51:22,960
country with groups of parents and
3199
01:51:20,800 --> 01:51:26,320
groups of pediatricians to really get
3200
01:51:22,960 --> 01:51:27,920
their perspectives on how our findings
3201
01:51:26,320 --> 01:51:30,800
from the predictive modeling work could
3202
01:51:27,920 --> 01:51:32,400
best help them with their prevention and
3203
01:51:30,800 --> 01:51:34,800
early intervention
3204
01:51:32,400 --> 01:51:38,000
with the teens that they work with or
3205
01:51:34,800 --> 01:51:38,000
that their children
3206
01:51:38,320 --> 01:51:44,320
um this work is ongoing and we're in the
3207
01:51:41,920 --> 01:51:46,480
process of dissemination and developing
3208
01:51:44,320 --> 01:51:49,760
additional tools but one of the products
3209
01:51:46,480 --> 01:51:52,719
so far has been the creation of a free
3210
01:51:49,760 --> 01:51:55,199
accessible online substance use problem
3211
01:51:52,719 --> 01:51:58,880
risk assessment tool on the partnership
3212
01:51:55,199 --> 01:52:00,960
to win addiction website
3213
01:51:58,880 --> 01:52:03,040
and the questions in the tool are
3214
01:52:00,960 --> 01:52:07,679
informed by the predictive modeling
3215
01:52:03,040 --> 01:52:07,679
study and the larger literature
3216
01:52:08,320 --> 01:52:12,880
and they're really intended to provide
3217
01:52:10,320 --> 01:52:15,040
some additional empirically supported
3218
01:52:12,880 --> 01:52:17,440
information to help parents and
3219
01:52:15,040 --> 01:52:19,440
pediatricians and other clinicians who
3220
01:52:17,440 --> 01:52:21,520
are concerned and wanting to figure out
3221
01:52:19,440 --> 01:52:24,239
if their child might be at heightened
3222
01:52:21,520 --> 01:52:26,800
risk of developing a problem
3223
01:52:24,239 --> 01:52:30,320
and this is the kind of tool that can be
3224
01:52:26,800 --> 01:52:32,000
employed in an ehr again and so for
3225
01:52:30,320 --> 01:52:34,480
example pediatricians and other
3226
01:52:32,000 --> 01:52:37,360
clinicians could embed
3227
01:52:34,480 --> 01:52:39,119
um this you know the link to this
3228
01:52:37,360 --> 01:52:41,920
risk assessment tool in their
3229
01:52:39,119 --> 01:52:45,040
patient-facing pages or push it out to
3230
01:52:41,920 --> 01:52:47,599
families at visit time or in after visit
3231
01:52:45,040 --> 01:52:47,599
summaries
3232
01:52:49,599 --> 01:52:53,760
so the second set of projects i'm going
3233
01:52:51,119 --> 01:52:55,840
to show are based on our adult and
3234
01:52:53,760 --> 01:53:00,159
adolescent screening brief intervention
3235
01:52:55,840 --> 01:53:00,159
and referral to treatment or expert work
3236
01:53:01,280 --> 01:53:05,199
so we have in kaiser permanente northern
3237
01:53:03,520 --> 01:53:06,800
california we
3238
01:53:05,199 --> 01:53:09,840
have implemented
3239
01:53:06,800 --> 01:53:11,440
a comprehensive alcohol expert
3240
01:53:09,840 --> 01:53:14,719
initiative
3241
01:53:11,440 --> 01:53:17,040
in adult primary care and this was
3242
01:53:14,719 --> 01:53:20,080
based on a cluster randomized
3243
01:53:17,040 --> 01:53:21,840
implementation trial that used the ehr a
3244
01:53:20,080 --> 01:53:24,080
completely pragmatic trial where we
3245
01:53:21,840 --> 01:53:24,880
looked at outcomes
3246
01:53:24,080 --> 01:53:27,920
in
3247
01:53:24,880 --> 01:53:28,719
using ehr data and that was a study of
3248
01:53:27,920 --> 01:53:31,119
the
3249
01:53:28,719 --> 01:53:33,199
best most effective modalities for
3250
01:53:31,119 --> 01:53:35,760
delivering espert
3251
01:53:33,199 --> 01:53:38,480
and the health system took the findings
3252
01:53:35,760 --> 01:53:40,320
from that trial and implemented a
3253
01:53:38,480 --> 01:53:42,960
region-wide
3254
01:53:40,320 --> 01:53:44,080
alcohol expert program in adult primary
3255
01:53:42,960 --> 01:53:46,000
care
3256
01:53:44,080 --> 01:53:48,000
where medical assistants do the
3257
01:53:46,000 --> 01:53:51,599
screening for unhealthy alcohol use as
3258
01:53:48,000 --> 01:53:54,480
part of the rooming process alongside
3259
01:53:51,599 --> 01:53:57,040
blood pressure tobacco and exercise and
3260
01:53:54,480 --> 01:53:59,199
then primary care physicians deliver the
3261
01:53:57,040 --> 01:54:01,440
brief advice or brief intervention and
3262
01:53:59,199 --> 01:54:03,840
referral to specialty treatment as
3263
01:54:01,440 --> 01:54:03,840
needed
3264
01:54:04,560 --> 01:54:10,080
and this has been a very successful
3265
01:54:06,719 --> 01:54:11,599
program since its inception in 2013
3266
01:54:10,080 --> 01:54:14,880
we've conducted
3267
01:54:11,599 --> 01:54:15,840
over 15 million total alcohol screenings
3268
01:54:14,880 --> 01:54:19,280
of
3269
01:54:15,840 --> 01:54:22,080
over 4.5 million unique adults we have
3270
01:54:19,280 --> 01:54:23,590
very high screening rate
3271
01:54:22,080 --> 01:54:24,719
and a very
3272
01:54:23,590 --> 01:54:26,880
[Music]
3273
01:54:24,719 --> 01:54:29,440
you know healthy brief intervention rate
3274
01:54:26,880 --> 01:54:32,639
among those people who screen positive
3275
01:54:29,440 --> 01:54:32,639
for unhealthy drinking
3276
01:54:33,920 --> 01:54:38,159
so these next few slides are screen
3277
01:54:36,080 --> 01:54:40,880
shots of some of the decision support
3278
01:54:38,159 --> 01:54:41,840
tools that we were able to get embedded
3279
01:54:40,880 --> 01:54:44,960
into
3280
01:54:41,840 --> 01:54:46,719
the ehr so this one here is what pops up
3281
01:54:44,960 --> 01:54:49,920
when the medical assistant is rooming
3282
01:54:46,719 --> 01:54:53,040
the patient to remind them to ask the
3283
01:54:49,920 --> 01:54:53,040
screening questions
3284
01:54:54,080 --> 01:54:59,679
the these are the screening questions
3285
01:54:56,000 --> 01:55:01,840
these are a modified version of the nia
3286
01:54:59,679 --> 01:55:05,280
single items
3287
01:55:01,840 --> 01:55:08,480
binge drinking question tailored to the
3288
01:55:05,280 --> 01:55:10,800
age and gender of the patient and then
3289
01:55:08,480 --> 01:55:13,760
that follow up with daily and weekly
3290
01:55:10,800 --> 01:55:18,280
frequency and then a calculated weekly
3291
01:55:13,760 --> 01:55:18,280
quantity of of drinks
3292
01:55:19,360 --> 01:55:24,159
and then based on that this is the best
3293
01:55:21,840 --> 01:55:26,800
practice alert that informs the primary
3294
01:55:24,159 --> 01:55:28,560
care clinician of the patient's
3295
01:55:26,800 --> 01:55:31,360
screening responses
3296
01:55:28,560 --> 01:55:33,679
it provides prompts for next steps so
3297
01:55:31,360 --> 01:55:36,719
suggesting you know this person
3298
01:55:33,679 --> 01:55:38,639
has endorsed unhealthy drinking
3299
01:55:36,719 --> 01:55:40,320
we suggest that you deliver a brief
3300
01:55:38,639 --> 01:55:42,239
intervention
3301
01:55:40,320 --> 01:55:44,000
and then provides them with some
3302
01:55:42,239 --> 01:55:46,480
additional dependence risk questions
3303
01:55:44,000 --> 01:55:48,320
that they can use for further assessment
3304
01:55:46,480 --> 01:55:50,159
if they want to help them
3305
01:55:48,320 --> 01:55:54,320
in their decision making about a
3306
01:55:50,159 --> 01:55:54,320
referral to specialty care
3307
01:55:56,080 --> 01:55:58,960
here in this
3308
01:55:57,599 --> 01:56:02,239
flow sheet
3309
01:55:58,960 --> 01:56:06,239
the physicians are able to see patients
3310
01:56:02,239 --> 01:56:08,560
alcohol use over time across visits
3311
01:56:06,239 --> 01:56:12,320
in order to stimulate conversations with
3312
01:56:08,560 --> 01:56:12,320
patients about how they're doing
3313
01:56:12,800 --> 01:56:18,560
and then this is a
3314
01:56:15,440 --> 01:56:21,119
referral documentation screen that
3315
01:56:18,560 --> 01:56:22,960
clinicians can use to easily refer
3316
01:56:21,119 --> 01:56:25,360
patients to specialty addiction
3317
01:56:22,960 --> 01:56:25,360
treatment
3318
01:56:26,880 --> 01:56:32,159
so because of all of these tools and
3319
01:56:29,920 --> 01:56:33,440
combined with the comprehensive medical
3320
01:56:32,159 --> 01:56:36,960
and mental health and services
3321
01:56:33,440 --> 01:56:39,599
utilization data that we have in the ehr
3322
01:56:36,960 --> 01:56:41,679
we've been able to examine you know
3323
01:56:39,599 --> 01:56:44,239
different ways of the you know the
3324
01:56:41,679 --> 01:56:46,159
effectiveness of you know different ways
3325
01:56:44,239 --> 01:56:48,080
of delivering espert
3326
01:56:46,159 --> 01:56:50,960
uh we've been able to look at the
3327
01:56:48,080 --> 01:56:54,400
effects on something like blood pressure
3328
01:56:50,960 --> 01:56:57,040
of receiving a brief intervention
3329
01:56:54,400 --> 01:57:00,080
and then we've been able to look at the
3330
01:56:57,040 --> 01:57:04,400
associations between different levels of
3331
01:57:00,080 --> 01:57:05,280
and patterns of unhealthy drinking on um
3332
01:57:04,400 --> 01:57:07,360
with
3333
01:57:05,280 --> 01:57:10,080
different medical conditions psychiatric
3334
01:57:07,360 --> 01:57:12,719
disorders and with other substance use
3335
01:57:10,080 --> 01:57:12,719
disorders
3336
01:57:17,199 --> 01:57:23,840
we are also using
3337
01:57:20,639 --> 01:57:25,599
the ehr data to study factors associated
3338
01:57:23,840 --> 01:57:28,080
with successful implementation and
3339
01:57:25,599 --> 01:57:30,000
sustainment of expert
3340
01:57:28,080 --> 01:57:31,840
and looking at the fidelity and quality
3341
01:57:30,000 --> 01:57:33,760
of brief interventions using an
3342
01:57:31,840 --> 01:57:37,239
implementation
3343
01:57:33,760 --> 01:57:37,239
science framework
3344
01:57:38,560 --> 01:57:43,280
so similar to the adult
3345
01:57:41,119 --> 01:57:46,719
alcohol screening work we've been able
3346
01:57:43,280 --> 01:57:48,800
to study expert and prevention and early
3347
01:57:46,719 --> 01:57:51,280
intervention in adolescence using the
3348
01:57:48,800 --> 01:57:54,239
tools that were already in place in the
3349
01:57:51,280 --> 01:57:56,960
systems ehr as part of
3350
01:57:54,239 --> 01:57:58,880
the well visit template so you know kids
3351
01:57:56,960 --> 01:58:01,199
fill out a comprehensive
3352
01:57:58,880 --> 01:58:04,639
screening questionnaire
3353
01:58:01,199 --> 01:58:06,560
as they're sitting and waiting for
3354
01:58:04,639 --> 01:58:09,840
for their well visit and part of the
3355
01:58:06,560 --> 01:58:13,440
those of course are alcohol and drug and
3356
01:58:09,840 --> 01:58:13,440
mood and other questions
3357
01:58:13,599 --> 01:58:21,679
uh we've also been able to we were able
3358
01:58:16,320 --> 01:58:22,639
to get the craft um embedded in the ehr
3359
01:58:21,679 --> 01:58:26,560
and
3360
01:58:22,639 --> 01:58:29,920
some other alcohol and drug questions
3361
01:58:26,560 --> 01:58:34,159
that clinicians can use to assess
3362
01:58:29,920 --> 01:58:35,920
severity and use patterns
3363
01:58:34,159 --> 01:58:39,119
and then similar to what i showed you
3364
01:58:35,920 --> 01:58:41,599
with the adults you're we're able to um
3365
01:58:39,119 --> 01:58:44,400
show in this flow sheet you know
3366
01:58:41,599 --> 01:58:47,040
kids response over time so that doctors
3367
01:58:44,400 --> 01:58:50,239
can sort of see how they're doing you
3368
01:58:47,040 --> 01:58:50,239
know from visit to visit
3369
01:58:52,000 --> 01:58:58,560
and again using these tools and other
3370
01:58:55,520 --> 01:59:01,520
ehr data we've been able to conduct
3371
01:58:58,560 --> 01:59:03,520
pragmatic trials to examine
3372
01:59:01,520 --> 01:59:05,360
you know what works in terms of
3373
01:59:03,520 --> 01:59:08,400
implementation of screening brief
3374
01:59:05,360 --> 01:59:10,800
intervention and referral to treatment
3375
01:59:08,400 --> 01:59:14,080
being able to look at specialty
3376
01:59:10,800 --> 01:59:16,719
treatment initiation and engagement
3377
01:59:14,080 --> 01:59:19,920
as a result of expert
3378
01:59:16,719 --> 01:59:21,920
able to look at patient outcomes like
3379
01:59:19,920 --> 01:59:23,440
substance use outcomes and depression
3380
01:59:21,920 --> 01:59:27,199
outcomes
3381
01:59:23,440 --> 01:59:30,239
and then uh because of the the scope and
3382
01:59:27,199 --> 01:59:33,119
the the you know the stable membership
3383
01:59:30,239 --> 01:59:37,199
we're able to look at long-term outcomes
3384
01:59:33,119 --> 01:59:39,360
from espert over time so uh looking at
3385
01:59:37,199 --> 01:59:41,840
three-year outcomes and now we're uh we
3386
01:59:39,360 --> 01:59:43,599
have a paper coming out soon looking at
3387
01:59:41,840 --> 01:59:47,199
seven-year outcomes
3388
01:59:43,599 --> 01:59:47,199
over time from esper
3389
01:59:49,119 --> 01:59:51,440
so
3390
01:59:50,080 --> 01:59:54,320
you know we've seen a number of the
3391
01:59:51,440 --> 01:59:57,520
different ways that ehr data can be used
3392
01:59:54,320 --> 01:59:59,639
for studying and delivering prevention
3393
01:59:57,520 --> 02:00:01,679
activities obviously
3394
01:59:59,639 --> 02:00:03,360
epidemiological data
3395
02:00:01,679 --> 02:00:05,760
the kind of machine learning and
3396
02:00:03,360 --> 02:00:08,480
predictive modeling that i talked about
3397
02:00:05,760 --> 02:00:10,080
pragmatic trials clinical decision
3398
02:00:08,480 --> 02:00:12,159
support tools
3399
02:00:10,080 --> 02:00:14,239
the sort of patient reported outcomes
3400
02:00:12,159 --> 02:00:16,400
and symptoms and functioning that can be
3401
02:00:14,239 --> 02:00:18,159
used both for research and for quality
3402
02:00:16,400 --> 02:00:20,800
improvement
3403
02:00:18,159 --> 02:00:22,239
as we just heard from dr chisholm we're
3404
02:00:20,800 --> 02:00:24,840
increasingly
3405
02:00:22,239 --> 02:00:27,119
assessing social determinants of health
3406
02:00:24,840 --> 02:00:29,679
uh including things like adverse
3407
02:00:27,119 --> 02:00:32,960
childhood experiences
3408
02:00:29,679 --> 02:00:35,760
food housing and transportation
3409
02:00:32,960 --> 02:00:38,239
other sorts of critical outcomes beyond
3410
02:00:35,760 --> 02:00:40,880
just substance use so medical and mental
3411
02:00:38,239 --> 02:00:42,400
health and services utilization pharmacy
3412
02:00:40,880 --> 02:00:44,560
utilization
3413
02:00:42,400 --> 02:00:47,280
pharmacotherapy
3414
02:00:44,560 --> 02:00:48,239
and then really able to look at numbers
3415
02:00:47,280 --> 02:00:51,040
and
3416
02:00:48,239 --> 02:00:53,599
having the ability to look at the reach
3417
02:00:51,040 --> 02:00:56,719
of intervention so you know in a regular
3418
02:00:53,599 --> 02:00:59,119
clinical trial looking at you know um
3419
02:00:56,719 --> 02:01:01,679
outcomes it's great when you you know
3420
02:00:59,119 --> 02:01:04,000
but you may have a sample of only
3421
02:01:01,679 --> 02:01:06,960
um you know hundreds of people but being
3422
02:01:04,000 --> 02:01:09,360
able to look at this over thousands or
3423
02:01:06,960 --> 02:01:11,199
or millions of people
3424
02:01:09,360 --> 02:01:12,960
you know is something that ehr data
3425
02:01:11,199 --> 02:01:16,000
really enables so
3426
02:01:12,960 --> 02:01:17,520
and looking at outcomes over time so i
3427
02:01:16,000 --> 02:01:20,239
will stop there
3428
02:01:17,520 --> 02:01:20,239
and thank you
3429
02:01:21,119 --> 02:01:28,480
great thank you for that and now i will
3430
02:01:23,199 --> 02:01:28,480
turn to our final presenter hello
3431
02:01:28,560 --> 02:01:33,440
um yeah so i'm excited to kind of close
3432
02:01:30,800 --> 02:01:35,840
this out and we'll try to get us
3433
02:01:33,440 --> 02:01:38,639
uh by some of our time back because i
3434
02:01:35,840 --> 02:01:41,760
would love to have some time for a q a
3435
02:01:38,639 --> 02:01:43,280
so let me just um okay i'm sharing the
3436
02:01:41,760 --> 02:01:45,599
right one
3437
02:01:43,280 --> 02:01:47,440
and we'll get started so i'm going to
3438
02:01:45,599 --> 02:01:48,239
talk uh today about
3439
02:01:47,440 --> 02:01:51,040
um
3440
02:01:48,239 --> 02:01:53,760
how we leverage the va electronic health
3441
02:01:51,040 --> 02:01:56,080
record data to improve care um and i'm
3442
02:01:53,760 --> 02:01:57,520
going to use storm as an exemplar so i
3443
02:01:56,080 --> 02:01:59,760
was super excited that in the first
3444
02:01:57,520 --> 02:02:03,440
session there were some opioid related
3445
02:01:59,760 --> 02:02:05,679
examples shared from arc or ahrq so
3446
02:02:03,440 --> 02:02:06,960
again we'll hopefully uh
3447
02:02:05,679 --> 02:02:09,040
have some nice
3448
02:02:06,960 --> 02:02:11,360
info that will help
3449
02:02:09,040 --> 02:02:13,760
piggyback on some of that so
3450
02:02:11,360 --> 02:02:15,760
in va we have a lot of data so we just
3451
02:02:13,760 --> 02:02:17,440
wanted to make it very clear
3452
02:02:15,760 --> 02:02:19,520
you know we have this is a little bit
3453
02:02:17,440 --> 02:02:21,440
older so we're up to 24 million patients
3454
02:02:19,520 --> 02:02:24,320
but the point being you can see the bees
3455
02:02:21,440 --> 02:02:27,440
on the right hand side about um how many
3456
02:02:24,320 --> 02:02:29,280
billion uh records we have uh regarding
3457
02:02:27,440 --> 02:02:32,239
all sorts of things clinical notes labs
3458
02:02:29,280 --> 02:02:35,280
and and whatnot so we have a lot of data
3459
02:02:32,239 --> 02:02:37,199
and it's organized um in regions and so
3460
02:02:35,280 --> 02:02:40,000
hopefully that just gives a quick
3461
02:02:37,199 --> 02:02:41,520
uh background on on what types of data
3462
02:02:40,000 --> 02:02:43,040
we do have and
3463
02:02:41,520 --> 02:02:45,679
the amount as
3464
02:02:43,040 --> 02:02:47,679
really the us's national only national
3465
02:02:45,679 --> 02:02:48,560
healthcare system so one thing in the
3466
02:02:47,679 --> 02:02:50,880
opioid
3467
02:02:48,560 --> 02:02:53,360
related space we did use our corporate
3468
02:02:50,880 --> 02:02:55,679
data warehouse for is looking at
3469
02:02:53,360 --> 02:02:57,440
overdose and suicide mortality among
3470
02:02:55,679 --> 02:02:59,840
patients
3471
02:02:57,440 --> 02:03:02,480
that were prescribed opioids and this
3472
02:02:59,840 --> 02:03:06,239
was an earlier analysis we did so it's a
3473
02:03:02,480 --> 02:03:08,560
little bit older data looking at fy 2013
3474
02:03:06,239 --> 02:03:10,560
overdose and suicide mortality and what
3475
02:03:08,560 --> 02:03:13,440
we found given that this is a naida
3476
02:03:10,560 --> 02:03:16,239
webinar is a good chunk of those who end
3477
02:03:13,440 --> 02:03:18,239
up dying this was this analysis was done
3478
02:03:16,239 --> 02:03:21,599
when there was a huge focus on morphine
3479
02:03:18,239 --> 02:03:23,760
equivalent daily dose um limits and what
3480
02:03:21,599 --> 02:03:25,760
we found is again you know 20 percent of
3481
02:03:23,760 --> 02:03:28,159
people people who died were above you
3482
02:03:25,760 --> 02:03:30,639
know that you know cut off that a lot of
3483
02:03:28,159 --> 02:03:32,719
people were focused on and a good 80 of
3484
02:03:30,639 --> 02:03:34,800
people who died um
3485
02:03:32,719 --> 02:03:36,800
were below that but moreover four out of
3486
02:03:34,800 --> 02:03:38,400
every five patients who died from an
3487
02:03:36,800 --> 02:03:40,480
overdose or suicide were again
3488
02:03:38,400 --> 02:03:42,080
prescribed below 90 and three out of
3489
02:03:40,480 --> 02:03:45,119
four had a mental health or stud
3490
02:03:42,080 --> 02:03:46,800
diagnosis so again really it really
3491
02:03:45,119 --> 02:03:47,840
emphasized to us that we need to
3492
02:03:46,800 --> 02:03:51,119
consider
3493
02:03:47,840 --> 02:03:52,719
um a number of other factors given that
3494
02:03:51,119 --> 02:03:54,880
those at greatest risk of overdose or
3495
02:03:52,719 --> 02:03:56,320
suicide do we know tend to be complete
3496
02:03:54,880 --> 02:03:58,639
complex patients with multiple
3497
02:03:56,320 --> 02:04:00,560
comorbidities and again you know that
3498
02:03:58,639 --> 02:04:02,560
opioid that small little red dot even if
3499
02:04:00,560 --> 02:04:04,480
you take that away risk for adverse
3500
02:04:02,560 --> 02:04:06,239
events related to pain mental health
3501
02:04:04,480 --> 02:04:08,639
medical conditions are all really
3502
02:04:06,239 --> 02:04:11,360
important and so really thinking through
3503
02:04:08,639 --> 02:04:13,119
how can we support patient-centered risk
3504
02:04:11,360 --> 02:04:15,280
mitigation addressing all the
3505
02:04:13,119 --> 02:04:18,000
co-morbidities we know to be associated
3506
02:04:15,280 --> 02:04:19,920
with adverse outcomes like overdose and
3507
02:04:18,000 --> 02:04:22,400
suicide among patients prescribed
3508
02:04:19,920 --> 02:04:25,119
opioids so that's where storm enters in
3509
02:04:22,400 --> 02:04:26,079
so what is storm it's a
3510
02:04:25,119 --> 02:04:29,119
a
3511
02:04:26,079 --> 02:04:31,679
we leverage the ehr data um and we
3512
02:04:29,119 --> 02:04:35,119
predict risk of overdose or suicide from
3513
02:04:31,679 --> 02:04:37,520
that data and we look at prediction in
3514
02:04:35,119 --> 02:04:39,199
the next year of an overdose or suicide
3515
02:04:37,520 --> 02:04:41,920
event and it generates a patient
3516
02:04:39,199 --> 02:04:45,119
specific score and so these
3517
02:04:41,920 --> 02:04:47,840
parameters are applied on real-time data
3518
02:04:45,119 --> 02:04:50,159
and updated nightly so every night these
3519
02:04:47,840 --> 02:04:53,199
data are updated to create individual
3520
02:04:50,159 --> 02:04:55,840
risk estimates for overdose or suicide
3521
02:04:53,199 --> 02:04:57,760
among all patients in the va so not just
3522
02:04:55,840 --> 02:04:59,599
those prescribed opioids but we also
3523
02:04:57,760 --> 02:05:01,199
have what we call a hypothetical score
3524
02:04:59,599 --> 02:05:04,000
so if a patient was going to be
3525
02:05:01,199 --> 02:05:04,960
introduced um or started on opioids what
3526
02:05:04,000 --> 02:05:06,960
their
3527
02:05:04,960 --> 02:05:09,920
risk would be and so this has been
3528
02:05:06,960 --> 02:05:11,679
translated into other ehrs we've worked
3529
02:05:09,920 --> 02:05:15,280
on getting the department of defense a
3530
02:05:11,679 --> 02:05:16,880
tri-storm um example as well as uh we're
3531
02:05:15,280 --> 02:05:19,280
currently working with cerner to
3532
02:05:16,880 --> 02:05:21,599
integrate that into the ehr as well and
3533
02:05:19,280 --> 02:05:23,520
so some of the key cohorts are those
3534
02:05:21,599 --> 02:05:25,360
patients prescribed opioids again
3535
02:05:23,520 --> 02:05:27,360
actively prescribed and we have some
3536
02:05:25,360 --> 02:05:29,679
data that we've um done showing that
3537
02:05:27,360 --> 02:05:31,520
recent discontinuation also puts people
3538
02:05:29,679 --> 02:05:33,679
at high risk particularly those who've
3539
02:05:31,520 --> 02:05:35,599
been on for longer periods of time so we
3540
02:05:33,679 --> 02:05:37,360
do include that as a cohort and storm
3541
02:05:35,599 --> 02:05:39,520
which i'll show you a little bit later
3542
02:05:37,360 --> 02:05:41,599
and again we do include patients with an
3543
02:05:39,520 --> 02:05:43,440
opiate use disorder just in general on
3544
02:05:41,599 --> 02:05:45,119
the site because we do know those are
3545
02:05:43,440 --> 02:05:47,280
very high risk patients and again as i
3546
02:05:45,119 --> 02:05:49,520
mentioned those considering opioid
3547
02:05:47,280 --> 02:05:51,199
therapy as well as patients with an
3548
02:05:49,520 --> 02:05:53,199
overdose we have some very compelling
3549
02:05:51,199 --> 02:05:55,280
data that uh you know patients who
3550
02:05:53,199 --> 02:05:56,560
overdose are obviously at a higher risk
3551
02:05:55,280 --> 02:05:58,000
for um
3552
02:05:56,560 --> 02:06:00,239
overdose or suicide in the following
3553
02:05:58,000 --> 02:06:02,239
year so we also track those patients so
3554
02:06:00,239 --> 02:06:04,079
we have a lot of information um on how
3555
02:06:02,239 --> 02:06:05,599
we developed our risk model and we are
3556
02:06:04,079 --> 02:06:09,280
actually doing a randomized program
3557
02:06:05,599 --> 02:06:11,440
evaluation of actually mandating um
3558
02:06:09,280 --> 02:06:14,079
interdisciplinary reviews of these
3559
02:06:11,440 --> 02:06:16,159
patients um who are identified as very
3560
02:06:14,079 --> 02:06:19,520
high risk in storm which i'll talk about
3561
02:06:16,159 --> 02:06:21,360
and so ahrq has noted this as a an
3562
02:06:19,520 --> 02:06:22,880
innovation and posted on their patient
3563
02:06:21,360 --> 02:06:25,679
safety network so you can also learn
3564
02:06:22,880 --> 02:06:28,239
more about that um via the web that
3565
02:06:25,679 --> 02:06:31,360
website so the big thing with regards to
3566
02:06:28,239 --> 02:06:33,440
our predictive model and we have over uh
3567
02:06:31,360 --> 02:06:35,760
you know 50 variables but i'm just kind
3568
02:06:33,440 --> 02:06:38,719
of showing you some examples of some of
3569
02:06:35,760 --> 02:06:40,560
the key domains and again we have again
3570
02:06:38,719 --> 02:06:42,400
medical comorbidities we know increased
3571
02:06:40,560 --> 02:06:44,400
risk as well as psychiatric substance
3572
02:06:42,400 --> 02:06:46,320
use and healthcare utilization again the
3573
02:06:44,400 --> 02:06:48,480
best predictor of future behaviors past
3574
02:06:46,320 --> 02:06:50,960
behavior so we do see very very high
3575
02:06:48,480 --> 02:06:53,440
odds ratios for those events in there uh
3576
02:06:50,960 --> 02:06:54,719
interestingly again with the focus
3577
02:06:53,440 --> 02:06:58,320
previously on
3578
02:06:54,719 --> 02:07:00,880
medd levels 120 medd would increase
3579
02:06:58,320 --> 02:07:02,960
modeled risk by about as much as a ptsd
3580
02:07:00,880 --> 02:07:05,119
or aud diagnosis
3581
02:07:02,960 --> 02:07:06,800
so really you know letting folks know
3582
02:07:05,119 --> 02:07:09,360
that as much effort as you're putting
3583
02:07:06,800 --> 02:07:10,639
into addressing mdd we should be
3584
02:07:09,360 --> 02:07:12,480
thinking about putting those efforts
3585
02:07:10,639 --> 02:07:15,280
into addressing these mental health and
3586
02:07:12,480 --> 02:07:18,719
substance use disorder comorbidities
3587
02:07:15,280 --> 02:07:21,520
moreover what our paper did also show is
3588
02:07:18,719 --> 02:07:24,159
that there are high odds ratios for
3589
02:07:21,520 --> 02:07:26,159
other evidence-based sedating pain meds
3590
02:07:24,159 --> 02:07:27,840
so there has been a lot of focus on uh
3591
02:07:26,159 --> 02:07:30,159
benzodiazepines or sedatives for
3592
02:07:27,840 --> 02:07:31,520
instance and you can see actually if you
3593
02:07:30,159 --> 02:07:33,119
have um
3594
02:07:31,520 --> 02:07:35,520
an opioid sedative
3595
02:07:33,119 --> 02:07:37,920
your increa your risk increases you know
3596
02:07:35,520 --> 02:07:39,679
1.4 times but if you have an opioid plus
3597
02:07:37,920 --> 02:07:42,400
one of these other evidence-based but
3598
02:07:39,679 --> 02:07:45,360
sedating pain meds tcas snris
3599
02:07:42,400 --> 02:07:48,000
anticonvulsants you see a gradient right
3600
02:07:45,360 --> 02:07:49,920
with the more you have on the greater
3601
02:07:48,000 --> 02:07:52,960
the risk for an overdose or suicide
3602
02:07:49,920 --> 02:07:55,199
event even much so more than the
3603
02:07:52,960 --> 02:07:57,920
sedatives so just really orienting the
3604
02:07:55,199 --> 02:07:59,760
field and uh and folks and providers to
3605
02:07:57,920 --> 02:08:02,480
this you know it's not just about benzos
3606
02:07:59,760 --> 02:08:05,119
it's about other sedating meds as well
3607
02:08:02,480 --> 02:08:08,560
so this is what storm looks like um we
3608
02:08:05,119 --> 02:08:10,800
have again the big thing from a provider
3609
02:08:08,560 --> 02:08:13,119
perspective right is and we're
3610
02:08:10,800 --> 02:08:14,639
incorporating again the predictive model
3611
02:08:13,119 --> 02:08:17,040
you have the predictive model risk on
3612
02:08:14,639 --> 02:08:19,520
the left hand side so we classify them
3613
02:08:17,040 --> 02:08:22,000
as very high high medium or low risk so
3614
02:08:19,520 --> 02:08:25,360
it gives you um that in the red their
3615
02:08:22,000 --> 02:08:26,960
risk level um strata and then we also
3616
02:08:25,360 --> 02:08:28,639
have resort for those who are of you or
3617
02:08:26,960 --> 02:08:31,040
who are in this space resource another
3618
02:08:28,639 --> 02:08:32,880
way of um stratifying patients so we
3619
02:08:31,040 --> 02:08:35,360
have that their risk scores and resort
3620
02:08:32,880 --> 02:08:37,199
also embedded in there um and then you
3621
02:08:35,360 --> 02:08:39,599
have what factors contribute to my
3622
02:08:37,199 --> 02:08:41,679
patient's risk so of those 50 or so
3623
02:08:39,599 --> 02:08:43,520
variables what are the ones that
3624
02:08:41,679 --> 02:08:44,880
contribute to this patient's risk and it
3625
02:08:43,520 --> 02:08:47,840
lists them so you have mental health
3626
02:08:44,880 --> 02:08:49,040
medical comorbidities adverse events
3627
02:08:47,840 --> 02:08:50,880
moreover what are the relevant
3628
02:08:49,040 --> 02:08:52,320
medications this patient's taking that
3629
02:08:50,880 --> 02:08:54,560
may also be
3630
02:08:52,320 --> 02:08:55,760
putting them at risk and the biggest
3631
02:08:54,560 --> 02:08:58,719
thing again where the rubber meets the
3632
02:08:55,760 --> 02:09:01,599
road is clinically how to do i better
3633
02:08:58,719 --> 02:09:03,440
manage my patients risks so these risk
3634
02:09:01,599 --> 02:09:05,920
mitigation strategies are based on
3635
02:09:03,440 --> 02:09:07,520
clinical practice guidelines and so we
3636
02:09:05,920 --> 02:09:09,840
integrate those clinical practice
3637
02:09:07,520 --> 02:09:12,800
guideline recommended interventions and
3638
02:09:09,840 --> 02:09:14,560
treatments on like within this system
3639
02:09:12,800 --> 02:09:16,639
and we include the dates in which any of
3640
02:09:14,560 --> 02:09:18,560
them were done and then on you see on
3641
02:09:16,639 --> 02:09:20,639
the right hand side also when they have
3642
02:09:18,560 --> 02:09:22,000
recent they've had recent and upcoming
3643
02:09:20,639 --> 02:09:24,320
appointments and who their care
3644
02:09:22,000 --> 02:09:27,199
providers are interestingly we color
3645
02:09:24,320 --> 02:09:28,560
code all of this so that um
3646
02:09:27,199 --> 02:09:31,199
things done at one facility are a
3647
02:09:28,560 --> 02:09:33,440
certain color so this also gives a sense
3648
02:09:31,199 --> 02:09:35,040
of how much potentially uncoordinated
3649
02:09:33,440 --> 02:09:36,480
uncoordinated care might be happening if
3650
02:09:35,040 --> 02:09:38,880
a patient's for instance being seen at
3651
02:09:36,480 --> 02:09:40,480
multiple facilities it really emphasizes
3652
02:09:38,880 --> 02:09:42,639
the need to um get them that care
3653
02:09:40,480 --> 02:09:44,159
coordination so again one of the big
3654
02:09:42,639 --> 02:09:45,679
things i love as well is that we also
3655
02:09:44,159 --> 02:09:46,639
include non-pharmacological pain
3656
02:09:45,679 --> 02:09:48,079
treatments
3657
02:09:46,639 --> 02:09:49,599
and when
3658
02:09:48,079 --> 02:09:50,560
patients have received them as well so
3659
02:09:49,599 --> 02:09:53,920
again
3660
02:09:50,560 --> 02:09:55,280
it really in one single click gives
3661
02:09:53,920 --> 02:09:59,040
providers
3662
02:09:55,280 --> 02:10:01,840
a real-time view of what their patient's
3663
02:09:59,040 --> 02:10:03,760
risk is and what puts them at risk and
3664
02:10:01,840 --> 02:10:05,599
what they can do about it which again is
3665
02:10:03,760 --> 02:10:07,119
actionable information
3666
02:10:05,599 --> 02:10:10,239
so we have a randomized program
3667
02:10:07,119 --> 02:10:12,000
evaluation um that again and this has
3668
02:10:10,239 --> 02:10:13,840
been embedded in a decision support
3669
02:10:12,000 --> 02:10:16,159
system to encourage guideline-based risk
3670
02:10:13,840 --> 02:10:18,000
mitigation and so there was a policy
3671
02:10:16,159 --> 02:10:20,480
that we released to national uh
3672
02:10:18,000 --> 02:10:22,239
randomized program evaluation and it
3673
02:10:20,480 --> 02:10:24,079
required interdisciplinary team review
3674
02:10:22,239 --> 02:10:26,400
of patients again estimated at a very
3675
02:10:24,079 --> 02:10:29,679
high risk and we randomized facilities
3676
02:10:26,400 --> 02:10:31,679
um to having an action planning uh
3677
02:10:29,679 --> 02:10:34,239
element or not having it and then we
3678
02:10:31,679 --> 02:10:37,679
monitored it uh via metrics so we
3679
02:10:34,239 --> 02:10:39,599
expanded uh storm from one percent to
3680
02:10:37,679 --> 02:10:41,679
the top five percent as part of a step
3681
02:10:39,599 --> 02:10:43,199
wedge design and i'll kind of show you
3682
02:10:41,679 --> 02:10:45,280
what that looks like but this was a
3683
02:10:43,199 --> 02:10:46,400
policy that we put out
3684
02:10:45,280 --> 02:10:48,400
to
3685
02:10:46,400 --> 02:10:50,239
have folks oriented to the fact that
3686
02:10:48,400 --> 02:10:52,800
very high-risk patients needed to have a
3687
02:10:50,239 --> 02:10:56,400
risk review completed and that we would
3688
02:10:52,800 --> 02:10:59,280
be monitoring and if they didn't uh meet
3689
02:10:56,400 --> 02:11:02,239
uh the uh meet the metrics that they
3690
02:10:59,280 --> 02:11:03,760
would be um given some action planning
3691
02:11:02,239 --> 02:11:05,920
so this is a trial design this is what
3692
02:11:03,760 --> 02:11:07,840
the stepwidge design looked like again
3693
02:11:05,920 --> 02:11:09,599
we expanded from the top one percent to
3694
02:11:07,840 --> 02:11:12,239
the top five percent
3695
02:11:09,599 --> 02:11:14,560
um and the biggest thing for us that was
3696
02:11:12,239 --> 02:11:16,480
really exciting was the fact that when
3697
02:11:14,560 --> 02:11:18,719
you actually expanded um
3698
02:11:16,480 --> 02:11:20,719
interdisciplinary reviews from the top
3699
02:11:18,719 --> 02:11:24,320
one uh to five percent in the step wedge
3700
02:11:20,719 --> 02:11:26,719
design we found a 22 percent reduction
3701
02:11:24,320 --> 02:11:28,880
in all cause mortality in the subsequent
3702
02:11:26,719 --> 02:11:32,560
four months approximately 180 lives
3703
02:11:28,880 --> 02:11:35,360
saved again these are um you know rates
3704
02:11:32,560 --> 02:11:37,040
on par with what you see in medication
3705
02:11:35,360 --> 02:11:38,960
related interventions
3706
02:11:37,040 --> 02:11:40,239
moreover we think that the mechanism was
3707
02:11:38,960 --> 02:11:42,880
these case reviews these
3708
02:11:40,239 --> 02:11:45,280
interdisciplinary reviews um in that uh
3709
02:11:42,880 --> 02:11:47,040
folks were more five times more likely
3710
02:11:45,280 --> 02:11:49,199
um to receive a case review when they
3711
02:11:47,040 --> 02:11:51,119
were listed as very high risk on storm
3712
02:11:49,199 --> 02:11:54,480
than uh than those
3713
02:11:51,119 --> 02:11:56,320
controls so again um we think that this
3714
02:11:54,480 --> 02:11:58,400
may have actually underestimated the
3715
02:11:56,320 --> 02:12:00,639
full benefits given that only 30 of
3716
02:11:58,400 --> 02:12:02,000
those um in the top one to five percent
3717
02:12:00,639 --> 02:12:03,920
received a full case review but we're
3718
02:12:02,000 --> 02:12:06,800
still seeing these significant um
3719
02:12:03,920 --> 02:12:07,599
decreases in mortality based on that
3720
02:12:06,800 --> 02:12:08,960
so
3721
02:12:07,599 --> 02:12:10,800
tauronologis is the first study to
3722
02:12:08,960 --> 02:12:13,119
evaluate the impact of a predictive
3723
02:12:10,800 --> 02:12:16,079
model targeted prevention program in
3724
02:12:13,119 --> 02:12:18,800
reducing adverse outcomes on high-risk
3725
02:12:16,079 --> 02:12:21,760
patients prescribed opioids specifically
3726
02:12:18,800 --> 02:12:23,280
by providing a case review and this is a
3727
02:12:21,760 --> 02:12:26,000
definitely a way we have leveraged the
3728
02:12:23,280 --> 02:12:27,679
ehr to combine risk identification with
3729
02:12:26,000 --> 02:12:29,360
predictive modeling
3730
02:12:27,679 --> 02:12:31,440
and interdisciplinary case review to
3731
02:12:29,360 --> 02:12:33,520
improve patient safety this again is
3732
02:12:31,440 --> 02:12:35,440
just one of many ways va leverages the
3733
02:12:33,520 --> 02:12:37,119
ehr we have lots of different other
3734
02:12:35,440 --> 02:12:38,000
examples but just wanted to use one for
3735
02:12:37,119 --> 02:12:39,199
now
3736
02:12:38,000 --> 02:12:41,199
and we do
3737
02:12:39,199 --> 02:12:43,119
suggest that this shows that combining
3738
02:12:41,199 --> 02:12:45,599
data systems like our corporate data
3739
02:12:43,119 --> 02:12:47,440
warehouse with policy enables
3740
02:12:45,599 --> 02:12:49,360
implementation designs that do a lot
3741
02:12:47,440 --> 02:12:51,920
allow for a strong evaluation of
3742
02:12:49,360 --> 02:12:55,199
outcomes so um here are some references
3743
02:12:51,920 --> 02:12:57,599
and i will stop sharing and pause uh for
3744
02:12:55,199 --> 02:12:59,679
for questions
3745
02:12:57,599 --> 02:13:01,599
all right thank you i think we have
3746
02:12:59,679 --> 02:13:03,280
about five minutes available for
3747
02:13:01,599 --> 02:13:05,199
questions um before we're going to go on
3748
02:13:03,280 --> 02:13:06,400
another brief break and i know that
3749
02:13:05,199 --> 02:13:08,639
there's been some that have been
3750
02:13:06,400 --> 02:13:10,239
floating up in the chat so i invite our
3751
02:13:08,639 --> 02:13:12,239
discussions especially the questions
3752
02:13:10,239 --> 02:13:14,079
that are a little bit more clarifying
3753
02:13:12,239 --> 02:13:15,280
to peek in the chat and see
3754
02:13:14,079 --> 02:13:17,440
um
3755
02:13:15,280 --> 02:13:19,520
i guess i'll ask a sort of a broad
3756
02:13:17,440 --> 02:13:20,960
question that can go in a couple
3757
02:13:19,520 --> 02:13:23,040
different directions so i'll put all the
3758
02:13:20,960 --> 02:13:24,880
directions out and let our presenters
3759
02:13:23,040 --> 02:13:26,480
decide which way to go in it but one
3760
02:13:24,880 --> 02:13:29,280
thing that was touched on a little bit
3761
02:13:26,480 --> 02:13:32,159
when we think about the ehr data
3762
02:13:29,280 --> 02:13:34,639
is the free text data versus like what's
3763
02:13:32,159 --> 02:13:36,880
in a field and a click box
3764
02:13:34,639 --> 02:13:38,800
um and in listening to everybody talk i
3765
02:13:36,880 --> 02:13:41,040
can sort of understand how a research in
3766
02:13:38,800 --> 02:13:42,800
a research design you can use natural
3767
02:13:41,040 --> 02:13:44,320
language processing to pull out some of
3768
02:13:42,800 --> 02:13:46,400
that free text data and then integrate
3769
02:13:44,320 --> 02:13:48,239
it in an algorithm to either predict you
3770
02:13:46,400 --> 02:13:50,320
or combine with some of the field date
3771
02:13:48,239 --> 02:13:51,599
the kind of field
3772
02:13:50,320 --> 02:13:53,280
i don't know what to call it but the
3773
02:13:51,599 --> 02:13:54,639
click box kind of data
3774
02:13:53,280 --> 02:13:56,639
i'm wondering one like how that
3775
02:13:54,639 --> 02:13:58,960
translates into practice if you want to
3776
02:13:56,639 --> 02:14:00,320
build algorithms that are predictive
3777
02:13:58,960 --> 02:14:02,560
um two
3778
02:14:00,320 --> 02:14:04,639
i'm wondering your thoughts on the issue
3779
02:14:02,560 --> 02:14:06,560
of provider variability
3780
02:14:04,639 --> 02:14:08,320
and how that factors into your research
3781
02:14:06,560 --> 02:14:10,000
you know in terms of providers who are
3782
02:14:08,320 --> 02:14:11,440
more likely to click boxes versus
3783
02:14:10,000 --> 02:14:12,800
providers more likely to put all their
3784
02:14:11,440 --> 02:14:15,119
notes in a free text and how you
3785
02:14:12,800 --> 02:14:16,800
potentially change that behavior
3786
02:14:15,119 --> 02:14:19,280
and then the third direction i could go
3787
02:14:16,800 --> 02:14:21,599
in with this question is you know we all
3788
02:14:19,280 --> 02:14:23,760
have our pet area and our priority area
3789
02:14:21,599 --> 02:14:25,679
where we'd love to get that question in
3790
02:14:23,760 --> 02:14:27,679
you know or those items in an electronic
3791
02:14:25,679 --> 02:14:30,000
health record and how do we do that
3792
02:14:27,679 --> 02:14:31,679
without contributing to physician burden
3793
02:14:30,000 --> 02:14:34,000
and adding to the hours that physicians
3794
02:14:31,679 --> 02:14:37,000
spend just documenting things in health
3795
02:14:34,000 --> 02:14:37,000
records
3796
02:14:40,800 --> 02:14:43,679
um
3797
02:14:41,840 --> 02:14:45,840
this is jody trafton i can try to take
3798
02:14:43,679 --> 02:14:48,079
that a little bit for va i mean most of
3799
02:14:45,840 --> 02:14:49,840
our work to date has been using
3800
02:14:48,079 --> 02:14:51,280
structured data because it's so much
3801
02:14:49,840 --> 02:14:54,480
easier to use and so much more
3802
02:14:51,280 --> 02:14:57,040
accessible um but we are uh right now
3803
02:14:54,480 --> 02:14:59,599
starting to implement um
3804
02:14:57,040 --> 02:15:01,920
nlp algorithms for so free text note
3805
02:14:59,599 --> 02:15:04,400
searches in our nightly updated decision
3806
02:15:01,920 --> 02:15:07,040
support in clinical practice um it took
3807
02:15:04,400 --> 02:15:09,599
a lot of technical work to
3808
02:15:07,040 --> 02:15:11,440
to set up um high performance computing
3809
02:15:09,599 --> 02:15:13,920
capabilities that
3810
02:15:11,440 --> 02:15:15,760
that allow us to go through we get 1.74
3811
02:15:13,920 --> 02:15:18,159
million notes a day
3812
02:15:15,760 --> 02:15:19,760
um which is just a lot of text to go
3813
02:15:18,159 --> 02:15:21,599
through but i think some of the other
3814
02:15:19,760 --> 02:15:23,599
pieces that that we struggle with a
3815
02:15:21,599 --> 02:15:24,560
little bit are um
3816
02:15:23,599 --> 02:15:26,320
just
3817
02:15:24,560 --> 02:15:28,400
getting
3818
02:15:26,320 --> 02:15:30,239
it would be so much easier to implement
3819
02:15:28,400 --> 02:15:32,560
things from research into practice if
3820
02:15:30,239 --> 02:15:34,480
the researchers would work with
3821
02:15:32,560 --> 02:15:36,480
your clinical uh
3822
02:15:34,480 --> 02:15:38,159
with your your informatics folks from
3823
02:15:36,480 --> 02:15:39,599
the start because it's really hard to
3824
02:15:38,159 --> 02:15:41,840
take somebody's
3825
02:15:39,599 --> 02:15:43,679
pre-built research algorithm and
3826
02:15:41,840 --> 02:15:46,239
implement it kind of have to go back and
3827
02:15:43,679 --> 02:15:47,760
start over again not completely but but
3828
02:15:46,239 --> 02:15:49,440
you have to do a lot of additional
3829
02:15:47,760 --> 02:15:51,840
revalidation that you wouldn't have to
3830
02:15:49,440 --> 02:15:53,679
do necessarily if if it was done as a
3831
02:15:51,840 --> 02:15:55,599
partnership so i would just highly
3832
02:15:53,679 --> 02:15:57,119
encourage people to work
3833
02:15:55,599 --> 02:15:58,880
you know within and
3834
02:15:57,119 --> 02:16:01,679
with your informatics specialists in
3835
02:15:58,880 --> 02:16:01,679
your health care system
3836
02:16:02,320 --> 02:16:08,639
i would add on to that um
3837
02:16:05,440 --> 02:16:12,719
i think the structure field data
3838
02:16:08,639 --> 02:16:15,840
is much more well suited to
3839
02:16:12,719 --> 02:16:18,159
uh clinical decision support um to
3840
02:16:15,840 --> 02:16:20,880
making decisions about you know brief
3841
02:16:18,159 --> 02:16:24,320
intervention or referrals during a visit
3842
02:16:20,880 --> 02:16:26,480
i think the nlp and the algorithms that
3843
02:16:24,320 --> 02:16:28,800
you can build with that are more
3844
02:16:26,480 --> 02:16:31,599
back-end things that you might do as
3845
02:16:28,800 --> 02:16:34,000
predictors outside of a visit that you
3846
02:16:31,599 --> 02:16:35,920
might use for doing targeted outreach
3847
02:16:34,000 --> 02:16:38,319
and that sort of thing just because the
3848
02:16:35,920 --> 02:16:40,160
real timeness of it just doesn't work
3849
02:16:38,319 --> 02:16:42,559
quite as well so i think that they both
3850
02:16:40,160 --> 02:16:45,200
have strengths and weaknesses i think
3851
02:16:42,559 --> 02:16:47,840
they both have a lot of embedded biases
3852
02:16:45,200 --> 02:16:49,359
um i think that we know you know even
3853
02:16:47,840 --> 02:16:50,319
our work with children of incarcerated
3854
02:16:49,359 --> 02:16:52,639
parents
3855
02:16:50,319 --> 02:16:54,639
we are pretty sure that docs are talking
3856
02:16:52,639 --> 02:16:56,160
about incarcerated parents with some
3857
02:16:54,639 --> 02:16:57,840
types of patients more than they're
3858
02:16:56,160 --> 02:16:59,599
talking about incarcerated parents with
3859
02:16:57,840 --> 02:17:02,319
other types of patients therefore we're
3860
02:16:59,599 --> 02:17:03,599
more likely to recognize it um in
3861
02:17:02,319 --> 02:17:05,359
patients of color who they're more
3862
02:17:03,599 --> 02:17:06,399
likely to be asking that question or
3863
02:17:05,359 --> 02:17:08,800
have been patients or they're more
3864
02:17:06,399 --> 02:17:10,000
likely to be having that discussion so
3865
02:17:08,800 --> 02:17:12,240
we sort of
3866
02:17:10,000 --> 02:17:12,240
um
3867
02:17:12,960 --> 02:17:19,200
reinforce existing biases by using data
3868
02:17:16,960 --> 02:17:21,120
that was biased when we collected it so
3869
02:17:19,200 --> 02:17:23,200
you know part of it is just recognizing
3870
02:17:21,120 --> 02:17:26,240
that at the time and starting to figure
3871
02:17:23,200 --> 02:17:28,160
out how you can standardize but we know
3872
02:17:26,240 --> 02:17:29,840
even when you have a quick box the
3873
02:17:28,160 --> 02:17:31,840
decision about whether or not to ask the
3874
02:17:29,840 --> 02:17:33,920
question versus whether or not to guess
3875
02:17:31,840 --> 02:17:35,760
whether to say you haven't your parents
3876
02:17:33,920 --> 02:17:37,519
haven't been in jail yet have they
3877
02:17:35,760 --> 02:17:39,920
versus um
3878
02:17:37,519 --> 02:17:41,920
are your parents in jail um
3879
02:17:39,920 --> 02:17:44,399
get you different responses so we know
3880
02:17:41,920 --> 02:17:46,240
that we get biased results whether we go
3881
02:17:44,399 --> 02:17:49,359
with the natural language processes or
3882
02:17:46,240 --> 02:17:51,359
whether we go with the structure fields
3883
02:17:49,359 --> 02:17:54,319
so a lot of that is just training and a
3884
02:17:51,359 --> 02:17:56,880
lot of that is
3885
02:17:54,319 --> 02:17:58,000
you know figuring out how we best
3886
02:17:56,880 --> 02:18:00,960
validate
3887
02:17:58,000 --> 02:18:02,559
um and how we best weigh the value of
3888
02:18:00,960 --> 02:18:05,200
that data when we're making decisions
3889
02:18:02,559 --> 02:18:05,200
based on it
3890
02:18:08,080 --> 02:18:11,439
yeah i was gonna say the only thing i'd
3891
02:18:09,920 --> 02:18:13,599
add you know the low hanging fruit here
3892
02:18:11,439 --> 02:18:15,040
i think is you know when people and this
3893
02:18:13,599 --> 02:18:16,960
is often happens you know when people
3894
02:18:15,040 --> 02:18:18,719
are recording discrete information as
3895
02:18:16,960 --> 02:18:20,160
text you know to which you want to say
3896
02:18:18,719 --> 02:18:22,240
don't do that
3897
02:18:20,160 --> 02:18:24,479
you know record discrete information as
3898
02:18:22,240 --> 02:18:26,399
discrete data there's a lot about health
3899
02:18:24,479 --> 02:18:27,519
and health care that is not discrete you
3900
02:18:26,399 --> 02:18:28,960
know there's a lot about health and
3901
02:18:27,519 --> 02:18:31,040
health care that's complicated and
3902
02:18:28,960 --> 02:18:33,200
continuous and cannot be reduced to
3903
02:18:31,040 --> 02:18:34,559
discrete data but there's still plenty
3904
02:18:33,200 --> 02:18:36,399
of health care where people are
3905
02:18:34,559 --> 02:18:38,559
recording things that are discrete data
3906
02:18:36,399 --> 02:18:40,559
by typing them in as text and that's
3907
02:18:38,559 --> 02:18:42,080
just a loss for everybody it's a loss in
3908
02:18:40,559 --> 02:18:44,479
terms of efficient practice for the
3909
02:18:42,080 --> 02:18:46,240
clinicians it's a loss in terms of you
3910
02:18:44,479 --> 02:18:47,840
know being able to improve care it's a
3911
02:18:46,240 --> 02:18:49,280
loss for research it's just a loss all
3912
02:18:47,840 --> 02:18:51,519
around so that's the low-hanging one i
3913
02:18:49,280 --> 02:18:51,519
think
3914
02:18:51,599 --> 02:18:55,200
i guess there's a follow-up thought to
3915
02:18:53,200 --> 02:18:57,040
something that jody said you know
3916
02:18:55,200 --> 02:18:58,639
our ehr is the kind of thing where you
3917
02:18:57,040 --> 02:18:59,760
know you've seen one ehr you've seen one
3918
02:18:58,639 --> 02:19:02,160
ehr
3919
02:18:59,760 --> 02:19:04,240
you know how generalizable
3920
02:19:02,160 --> 02:19:06,319
are some of these algorithms that you
3921
02:19:04,240 --> 02:19:08,800
all are working on so taking it from one
3922
02:19:06,319 --> 02:19:11,439
healthcare system to moving it out to
3923
02:19:08,800 --> 02:19:12,880
another one or nationally or broadly you
3924
02:19:11,439 --> 02:19:14,719
know how much work would have to be done
3925
02:19:12,880 --> 02:19:16,240
in translation for something developed
3926
02:19:14,719 --> 02:19:17,519
in one healthcare system to move it out
3927
02:19:16,240 --> 02:19:20,240
to another
3928
02:19:17,519 --> 02:19:22,479
there's a lot of translation so we have
3929
02:19:20,240 --> 02:19:25,280
for example this for this storm model we
3930
02:19:22,479 --> 02:19:29,359
have translated to the dod medical
3931
02:19:25,280 --> 02:19:32,240
record system um as well as to cerner
3932
02:19:29,359 --> 02:19:33,280
um and and i will say um
3933
02:19:32,240 --> 02:19:35,760
we
3934
02:19:33,280 --> 02:19:37,840
i think it's not just a medical record
3935
02:19:35,760 --> 02:19:40,719
system issue but also
3936
02:19:37,840 --> 02:19:42,000
you need you can't just it depends on
3937
02:19:40,719 --> 02:19:44,639
the patient populations that you're
3938
02:19:42,000 --> 02:19:47,040
seeing right so you can't take a model
3939
02:19:44,639 --> 02:19:48,640
or a decision support platform that you
3940
02:19:47,040 --> 02:19:50,720
built within
3941
02:19:48,640 --> 02:19:52,640
for use in one population and just
3942
02:19:50,720 --> 02:19:55,600
assume that it's going to work just fine
3943
02:19:52,640 --> 02:19:57,920
on another population a lot of the
3944
02:19:55,600 --> 02:20:00,800
that you're working on
3945
02:19:57,920 --> 02:20:02,399
most of your predictors are based upon
3946
02:20:00,800 --> 02:20:06,240
the way that the healthcare
3947
02:20:02,399 --> 02:20:08,080
record is used and in practice and if
3948
02:20:06,240 --> 02:20:09,920
you have differences in that or
3949
02:20:08,080 --> 02:20:11,680
differences in the populations being
3950
02:20:09,920 --> 02:20:13,359
treated the patterns that you're going
3951
02:20:11,680 --> 02:20:15,200
to see in the data could be very very
3952
02:20:13,359 --> 02:20:17,120
different and the interpretations can be
3953
02:20:15,200 --> 02:20:20,880
very very different as well so it's
3954
02:20:17,120 --> 02:20:24,000
really important i think to revalidate
3955
02:20:20,880 --> 02:20:25,920
and and ideally build your platforms and
3956
02:20:24,000 --> 02:20:28,640
adapt them with the groups that you're
3957
02:20:25,920 --> 02:20:31,120
in right i would i would not recommend
3958
02:20:28,640 --> 02:20:33,280
just kind of plug and playing like we we
3959
02:20:31,120 --> 02:20:35,280
worry a lot people are constantly trying
3960
02:20:33,280 --> 02:20:37,840
to sell va um
3961
02:20:35,280 --> 02:20:40,000
outside built systems that they claim
3962
02:20:37,840 --> 02:20:41,600
will do all sorts of things and they
3963
02:20:40,000 --> 02:20:44,080
kind of terrify us because they're black
3964
02:20:41,600 --> 02:20:45,760
boxes we have no idea way to validate
3965
02:20:44,080 --> 02:20:48,160
them we have no idea how well they're
3966
02:20:45,760 --> 02:20:49,760
working um and
3967
02:20:48,160 --> 02:20:52,479
and we have no way to fix them if we
3968
02:20:49,760 --> 02:20:53,200
find problems with them right so i i do
3969
02:20:52,479 --> 02:20:55,760
think
3970
02:20:53,200 --> 02:20:57,680
it's really important to consider these
3971
02:20:55,760 --> 02:21:00,080
tools part of
3972
02:20:57,680 --> 02:21:02,319
the health system that you're working in
3973
02:21:00,080 --> 02:21:04,399
and adapt it just the same way that you
3974
02:21:02,319 --> 02:21:06,479
would any clinical practice pattern
3975
02:21:04,399 --> 02:21:09,120
within that system
3976
02:21:06,479 --> 02:21:10,560
i would just add on to that
3977
02:21:09,120 --> 02:21:14,000
i agree with everything you said
3978
02:21:10,560 --> 02:21:14,960
particularly in the clinical delivery
3979
02:21:14,000 --> 02:21:19,040
setting
3980
02:21:14,960 --> 02:21:21,359
for the research setting i think we can
3981
02:21:19,040 --> 02:21:23,280
find ways of harmonizing data across
3982
02:21:21,359 --> 02:21:24,399
systems to be able to do larger scale
3983
02:21:23,280 --> 02:21:26,399
research
3984
02:21:24,399 --> 02:21:29,520
i think groups like peedsnet which i'm
3985
02:21:26,399 --> 02:21:32,319
engaged with is doing that work it is
3986
02:21:29,520 --> 02:21:35,040
very expensive it's very time consuming
3987
02:21:32,319 --> 02:21:36,560
and it's not always easy to get federal
3988
02:21:35,040 --> 02:21:38,560
grants that want to fund that kind of
3989
02:21:36,560 --> 02:21:41,040
work so i'll put in a plug
3990
02:21:38,560 --> 02:21:43,520
for funding those harmonization
3991
02:21:41,040 --> 02:21:46,000
processes that allow us to do
3992
02:21:43,520 --> 02:21:48,319
large-scale harmonization across
3993
02:21:46,000 --> 02:21:50,720
uh systems i mean even if everybody uses
3994
02:21:48,319 --> 02:21:52,560
epic they still don't match so there's
3995
02:21:50,720 --> 02:21:54,640
still a lot of work that has to be done
3996
02:21:52,560 --> 02:21:56,240
and we can't just do things under one
3997
02:21:54,640 --> 02:21:59,280
vendor so
3998
02:21:56,240 --> 02:22:00,640
i we have to do the work but it is work
3999
02:21:59,280 --> 02:22:03,200
and it's time consuming and it's
4000
02:22:00,640 --> 02:22:03,200
expensive
4001
02:22:04,640 --> 02:22:09,040
okay well thank you for a really
4002
02:22:06,960 --> 02:22:10,880
interesting and thought-provoking
4003
02:22:09,040 --> 02:22:12,800
panel there are several questions in the
4004
02:22:10,880 --> 02:22:14,720
chat that we didn't really have time for
4005
02:22:12,800 --> 02:22:15,920
because our presentations just took up a
4006
02:22:14,720 --> 02:22:18,160
lot of time which was great because they
4007
02:22:15,920 --> 02:22:19,600
were so interesting um so feel free to
4008
02:22:18,160 --> 02:22:21,600
kind of continue discussion in the chat
4009
02:22:19,600 --> 02:22:24,880
we're going to go on a five minute break
4010
02:22:21,600 --> 02:22:24,880
and we'll see you all back in a few
4011
02:22:25,040 --> 02:22:30,880
welcome back everyone um
4012
02:22:27,680 --> 02:22:30,880
thanks for hanging with us
4013
02:22:31,040 --> 02:22:34,399
and we have
4014
02:22:32,640 --> 02:22:35,680
our last session
4015
02:22:34,399 --> 02:22:38,160
starting now
4016
02:22:35,680 --> 02:22:40,000
and we're going to be hearing from two
4017
02:22:38,160 --> 02:22:42,800
nida projects that are using the ehr
4018
02:22:40,000 --> 02:22:44,160
data to meet their aims so
4019
02:22:42,800 --> 02:22:45,760
our the first project that we're going
4020
02:22:44,160 --> 02:22:48,080
to hear from is one of our heel
4021
02:22:45,760 --> 02:22:51,359
prevention projects and we have both dr
4022
02:22:48,080 --> 02:22:54,319
amy ewell and dr vinod rao with us to
4023
02:22:51,359 --> 02:22:57,040
discuss their project dr amy yule is a
4024
02:22:54,319 --> 02:22:58,800
board certified in adult child and
4025
02:22:57,040 --> 02:23:00,160
addiction psychiatry
4026
02:22:58,800 --> 02:23:02,160
she is the director of adolescent
4027
02:23:00,160 --> 02:23:03,920
addiction psychiatry at boston medical
4028
02:23:02,160 --> 02:23:05,920
center and an assistant professor at the
4029
02:23:03,920 --> 02:23:08,080
brown university school of boston
4030
02:23:05,920 --> 02:23:10,080
university school of medicine sorry
4031
02:23:08,080 --> 02:23:12,479
and dr rao is an addiction psychiatrist
4032
02:23:10,080 --> 02:23:14,800
the medical director of massachusetts uh
4033
02:23:12,479 --> 02:23:16,319
general hospital's west end clinic
4034
02:23:14,800 --> 02:23:18,960
and is also an instructor at harvard
4035
02:23:16,319 --> 02:23:21,520
medical school he also works as a
4036
02:23:18,960 --> 02:23:23,040
physician informaticist for
4037
02:23:21,520 --> 02:23:24,399
mgh
4038
02:23:23,040 --> 02:23:27,680
and then um
4039
02:23:24,399 --> 02:23:30,640
after doctors yule and rao we'll turn
4040
02:23:27,680 --> 02:23:34,240
the um i'll turn it over to
4041
02:23:30,640 --> 02:23:36,160
dr sarah beale dr dr beal is a dev
4042
02:23:34,240 --> 02:23:37,200
developmental psychologist at cincinnati
4043
02:23:36,160 --> 02:23:40,479
children's
4044
02:23:37,200 --> 02:23:42,319
um scientific director of the child welf
4045
02:23:40,479 --> 02:23:43,439
child welfare research lab and associate
4046
02:23:42,319 --> 02:23:46,479
professor at the university of
4047
02:23:43,439 --> 02:23:47,920
cincinnati department of pediatrics
4048
02:23:46,479 --> 02:23:50,240
so thank you
4049
02:23:47,920 --> 02:23:52,399
to both of your teams for joining us and
4050
02:23:50,240 --> 02:23:55,439
i will turn it over
4051
02:23:52,399 --> 02:23:55,439
to amy and vinod
4052
02:23:56,880 --> 02:24:00,319
thanks sarah
4053
02:23:58,319 --> 02:24:01,920
so i'm excited to be here today to talk
4054
02:24:00,319 --> 02:24:04,080
about how we're using data from the
4055
02:24:01,920 --> 02:24:05,840
electronic health record for a project
4056
02:24:04,080 --> 02:24:08,000
treat and identify psychopathology and
4057
02:24:05,840 --> 02:24:09,040
substance use disorders and as sarah
4058
02:24:08,000 --> 02:24:10,800
noted this is part of the heal
4059
02:24:09,040 --> 02:24:14,880
prevention cooperative and i'm the mpi
4060
02:24:10,800 --> 02:24:16,399
along with dr timothy williams next line
4061
02:24:14,880 --> 02:24:18,880
and so as we go on to discuss how we're
4062
02:24:16,399 --> 02:24:20,319
using data from the ehr for our project
4063
02:24:18,880 --> 02:24:22,640
we wanted to first describe our study
4064
02:24:20,319 --> 02:24:24,080
aims and the project itself and to start
4065
02:24:22,640 --> 02:24:26,080
with um i wanted to note that our
4066
02:24:24,080 --> 02:24:28,000
projects taking place within outpatient
4067
02:24:26,080 --> 02:24:30,160
behavioral health within the outpatient
4068
02:24:28,000 --> 02:24:31,359
behavioral setting and we chose the
4069
02:24:30,160 --> 02:24:33,120
setting because because we know that
4070
02:24:31,359 --> 02:24:34,560
mental health conditions are associated
4071
02:24:33,120 --> 02:24:36,880
with increased risk for early substance
4072
02:24:34,560 --> 02:24:40,800
use including opiate misuse and
4073
02:24:36,880 --> 02:24:40,800
substance use disorders next slide
4074
02:24:40,880 --> 02:24:44,479
in our first study aim was to implement
4075
02:24:42,640 --> 02:24:46,319
measurement-based care in the behavioral
4076
02:24:44,479 --> 02:24:47,680
health setting using patient-reported
4077
02:24:46,319 --> 02:24:49,760
outcome measures that are linked to the
4078
02:24:47,680 --> 02:24:50,960
electronic health record and our goal
4079
02:24:49,760 --> 02:24:52,640
with this was really to support
4080
02:24:50,960 --> 02:24:55,120
systematic screening and monitoring of
4081
02:24:52,640 --> 02:24:57,439
substance use and psychopathology with a
4082
02:24:55,120 --> 02:24:59,680
focus on depression and anxiety in the
4083
02:24:57,439 --> 02:25:01,600
behavioral health setting
4084
02:24:59,680 --> 02:25:03,439
as part of this we really focused on
4085
02:25:01,600 --> 02:25:05,040
four clinics at mass general hospital
4086
02:25:03,439 --> 02:25:06,319
and then two clinics at boston medical
4087
02:25:05,040 --> 02:25:08,560
center
4088
02:25:06,319 --> 02:25:10,880
within these four clinics at mgh two of
4089
02:25:08,560 --> 02:25:12,880
these are a child and adult behavioral
4090
02:25:10,880 --> 02:25:14,479
health clinic and then two are
4091
02:25:12,880 --> 02:25:16,000
substance use disorder clinics that are
4092
02:25:14,479 --> 02:25:17,920
within the department of psychiatry
4093
02:25:16,000 --> 02:25:20,080
focused on care for youth and then
4094
02:25:17,920 --> 02:25:22,319
another one on care for adults next
4095
02:25:20,080 --> 02:25:22,319
slide
4096
02:25:22,840 --> 02:25:26,399
next
4097
02:25:24,640 --> 02:25:28,080
and then our second study aim is really
4098
02:25:26,399 --> 02:25:30,240
to be assessing the impact of treatment
4099
02:25:28,080 --> 02:25:32,000
of psychopathology on the development of
4100
02:25:30,240 --> 02:25:34,240
an opiate use disorder substance use
4101
02:25:32,000 --> 02:25:36,800
disorder and nicotine use disorder in
4102
02:25:34,240 --> 02:25:38,479
young people 16 to 30 years of age who
4103
02:25:36,800 --> 02:25:40,960
are engaged in behavioral health
4104
02:25:38,479 --> 02:25:42,640
treatment and we're really doing this
4105
02:25:40,960 --> 02:25:45,200
through two different ways one is a
4106
02:25:42,640 --> 02:25:46,800
de-identified pull of longitudinal data
4107
02:25:45,200 --> 02:25:49,760
from the ehr within our larger
4108
02:25:46,800 --> 02:25:51,600
healthcare system of 16 to 30 year olds
4109
02:25:49,760 --> 02:25:53,200
and then secondly we're doing
4110
02:25:51,600 --> 02:25:55,520
we're recruiting from the six clinics
4111
02:25:53,200 --> 02:25:57,359
that i mentioned before um patients to
4112
02:25:55,520 --> 02:25:59,680
participate in a naturalistic
4113
02:25:57,359 --> 02:26:01,359
longitudinal study that involves self
4114
02:25:59,680 --> 02:26:04,080
self assessments that are done every six
4115
02:26:01,359 --> 02:26:06,399
months and then data pulled from the ehr
4116
02:26:04,080 --> 02:26:08,720
next slide
4117
02:26:06,399 --> 02:26:10,240
and as we think about our the second aim
4118
02:26:08,720 --> 02:26:11,920
you know really evaluating the impact of
4119
02:26:10,240 --> 02:26:13,680
treating psychopathology on the
4120
02:26:11,920 --> 02:26:15,040
development of an opiate use disorder
4121
02:26:13,680 --> 02:26:16,720
there's a lot of information that's
4122
02:26:15,040 --> 02:26:18,479
within the hr that can help answer our
4123
02:26:16,720 --> 02:26:20,960
research questions and we've talked
4124
02:26:18,479 --> 02:26:23,120
about these types of data um kind of
4125
02:26:20,960 --> 02:26:25,280
earlier on in the presentations and and
4126
02:26:23,120 --> 02:26:27,200
so i'm going to really focus um for my
4127
02:26:25,280 --> 02:26:29,120
small section a little bit on patient
4128
02:26:27,200 --> 02:26:30,479
reported outcome measures which are one
4129
02:26:29,120 --> 02:26:32,720
way that we can really get at severity
4130
02:26:30,479 --> 02:26:34,160
of illness which may may be a really
4131
02:26:32,720 --> 02:26:36,240
important factor as we think about the
4132
02:26:34,160 --> 02:26:38,800
impact of treatment on someone's risk of
4133
02:26:36,240 --> 02:26:40,880
developing an opiate use disorder um and
4134
02:26:38,800 --> 02:26:42,479
as we noted before you know the free
4135
02:26:40,880 --> 02:26:44,240
text data that's available in the
4136
02:26:42,479 --> 02:26:46,960
clinical note there's often a lot of
4137
02:26:44,240 --> 02:26:49,600
rich data in the clinical note um but
4138
02:26:46,960 --> 02:26:51,680
it's hard to um to make that systematic
4139
02:26:49,600 --> 02:26:53,439
or to quantify it and that's where
4140
02:26:51,680 --> 02:26:56,560
future reported outcome measures have a
4141
02:26:53,439 --> 02:26:58,399
lot of promise next slide
4142
02:26:56,560 --> 02:27:00,399
so that being said these reported
4143
02:26:58,399 --> 02:27:01,520
outcome measures don't end up in the ehr
4144
02:27:00,399 --> 02:27:03,200
magically
4145
02:27:01,520 --> 02:27:05,040
it's really they're part of a process of
4146
02:27:03,200 --> 02:27:06,640
measurement-based care and the idea with
4147
02:27:05,040 --> 02:27:08,000
measurement based here is that we're
4148
02:27:06,640 --> 02:27:10,000
routinely
4149
02:27:08,000 --> 02:27:11,840
and systematically administering a
4150
02:27:10,000 --> 02:27:13,920
patient-reported outcome as your tool to
4151
02:27:11,840 --> 02:27:16,080
assess patient symptoms and that the
4152
02:27:13,920 --> 02:27:18,080
patients receiving the tool completing
4153
02:27:16,080 --> 02:27:19,520
the tool and then the information from
4154
02:27:18,080 --> 02:27:20,640
this questionnaire is getting into the
4155
02:27:19,520 --> 02:27:22,560
hr
4156
02:27:20,640 --> 02:27:24,880
and then within the hr the provider has
4157
02:27:22,560 --> 02:27:27,760
to find this information and then review
4158
02:27:24,880 --> 02:27:29,359
it and then review it with the patient
4159
02:27:27,760 --> 02:27:31,600
it's really this process of the provider
4160
02:27:29,359 --> 02:27:34,080
and patient reviewing the data together
4161
02:27:31,600 --> 02:27:35,600
that has an impact on care and they can
4162
02:27:34,080 --> 02:27:36,960
use this data to think about the
4163
02:27:35,600 --> 02:27:38,960
treatment plan
4164
02:27:36,960 --> 02:27:40,399
and next steps within treatment
4165
02:27:38,960 --> 02:27:42,640
and what we really know from previous
4166
02:27:40,399 --> 02:27:43,920
research is that to be successful in
4167
02:27:42,640 --> 02:27:46,000
collecting patient-reported outcome
4168
02:27:43,920 --> 02:27:47,760
measures over time
4169
02:27:46,000 --> 02:27:49,680
this really has to be integrated into
4170
02:27:47,760 --> 02:27:51,760
clinical care in a meaningful way for
4171
02:27:49,680 --> 02:27:53,840
both patients and for
4172
02:27:51,760 --> 02:27:55,520
for the clinician so if the patient
4173
02:27:53,840 --> 02:27:57,280
completes the outcome measure and the
4174
02:27:55,520 --> 02:27:59,760
clinician ever reviews it they're going
4175
02:27:57,280 --> 02:28:01,359
to stop completing this outcome measure
4176
02:27:59,760 --> 02:28:04,080
and if the patient the provider can't
4177
02:28:01,359 --> 02:28:05,840
find the information within the ehr or
4178
02:28:04,080 --> 02:28:07,439
you know doesn't view the information to
4179
02:28:05,840 --> 02:28:08,960
be helpful for the the clinical
4180
02:28:07,439 --> 02:28:12,800
encounter they're going to also stop
4181
02:28:08,960 --> 02:28:13,920
using it as well so next slide
4182
02:28:12,800 --> 02:28:15,280
so as we think about kind of
4183
02:28:13,920 --> 02:28:16,640
measurement-based care implementation
4184
02:28:15,280 --> 02:28:18,560
which we've been working on over the
4185
02:28:16,640 --> 02:28:19,920
past um two to three years there you
4186
02:28:18,560 --> 02:28:22,160
know are many opportunities and
4187
02:28:19,920 --> 02:28:23,840
challenges and um and so as we think
4188
02:28:22,160 --> 02:28:25,760
about the behavioral health setting you
4189
02:28:23,840 --> 02:28:27,439
know one challenge is that we don't have
4190
02:28:25,760 --> 02:28:28,960
ancillary supports you know we don't
4191
02:28:27,439 --> 02:28:30,640
have a medical assistant who's checking
4192
02:28:28,960 --> 02:28:32,479
in patients and getting vital signs and
4193
02:28:30,640 --> 02:28:34,560
also looking at you know did a patient
4194
02:28:32,479 --> 02:28:37,359
complete this outcome measure um
4195
02:28:34,560 --> 02:28:38,720
completely and and kind of um correctly
4196
02:28:37,359 --> 02:28:40,640
and then you know helping to put the
4197
02:28:38,720 --> 02:28:42,479
information into the ehr
4198
02:28:40,640 --> 02:28:45,120
and so at mgh with a larger
4199
02:28:42,479 --> 02:28:46,880
infrastructure support pre-covered um
4200
02:28:45,120 --> 02:28:48,319
did have patients completing these
4201
02:28:46,880 --> 02:28:50,880
questionnaires on tablets that were
4202
02:28:48,319 --> 02:28:53,280
automatically synced to the ehr
4203
02:28:50,880 --> 02:28:55,040
and then with kovid had this opportunity
4204
02:28:53,280 --> 02:28:57,920
and challenge where for everything
4205
02:28:55,040 --> 02:28:59,920
switched to being done over telehealth
4206
02:28:57,920 --> 02:29:01,760
and so at mgh most of these visits were
4207
02:28:59,920 --> 02:29:03,920
done through a patient portal um and
4208
02:29:01,760 --> 02:29:06,000
there was because these um patient
4209
02:29:03,920 --> 02:29:08,000
report outcome measures were already um
4210
02:29:06,000 --> 02:29:09,840
built into the patient portal it was
4211
02:29:08,000 --> 02:29:11,359
fairly seamless to transition to
4212
02:29:09,840 --> 02:29:13,040
completing these questionnaires as part
4213
02:29:11,359 --> 02:29:15,040
of telehealth visits
4214
02:29:13,040 --> 02:29:16,800
um that was not the case at boston
4215
02:29:15,040 --> 02:29:18,880
medical center so boston medical center
4216
02:29:16,800 --> 02:29:20,399
is only two miles away from mgh but it's
4217
02:29:18,880 --> 02:29:22,479
a very different patient population
4218
02:29:20,399 --> 02:29:24,880
where we have a much larger
4219
02:29:22,479 --> 02:29:26,880
medicaid population um with different
4220
02:29:24,880 --> 02:29:29,120
infusions with um that are often
4221
02:29:26,880 --> 02:29:30,880
multi-level and so as we think about
4222
02:29:29,120 --> 02:29:32,399
patient population this is also really
4223
02:29:30,880 --> 02:29:34,319
important and particularly as we think
4224
02:29:32,399 --> 02:29:35,760
about administering administering
4225
02:29:34,319 --> 02:29:38,080
patient-reported outcome measures
4226
02:29:35,760 --> 02:29:40,640
through patient portals um
4227
02:29:38,080 --> 02:29:42,560
since we saw as we switched to doing
4228
02:29:40,640 --> 02:29:45,040
telehealth within behavioral health at
4229
02:29:42,560 --> 02:29:47,280
both institutions we saw significantly
4230
02:29:45,040 --> 02:29:49,200
less engagement with the patient portal
4231
02:29:47,280 --> 02:29:51,920
among behavioral health patients at
4232
02:29:49,200 --> 02:29:53,920
boston medical center so only 65 of
4233
02:29:51,920 --> 02:29:55,280
patients um you know kind of at the
4234
02:29:53,920 --> 02:29:57,920
beginning of the pandemic and then kind
4235
02:29:55,280 --> 02:30:00,640
of throughout within behavioral health
4236
02:29:57,920 --> 02:30:02,080
have an active patient portal
4237
02:30:00,640 --> 02:30:04,479
the other factor is thinking about
4238
02:30:02,080 --> 02:30:06,000
language are these measures um
4239
02:30:04,479 --> 02:30:07,439
translated into different languages and
4240
02:30:06,000 --> 02:30:09,520
available in different languages through
4241
02:30:07,439 --> 02:30:11,040
the ehr and then the patient portals
4242
02:30:09,520 --> 02:30:12,240
themselves are often
4243
02:30:11,040 --> 02:30:14,000
generally
4244
02:30:12,240 --> 02:30:15,840
more routinely available in english so
4245
02:30:14,000 --> 02:30:18,319
they're not they're not all translated
4246
02:30:15,840 --> 02:30:19,840
or easily translated um and so i think
4247
02:30:18,319 --> 02:30:22,319
another thing to be thinking about as we
4248
02:30:19,840 --> 02:30:25,359
think about equitable screening um is
4249
02:30:22,319 --> 02:30:27,280
that um the kind of administering these
4250
02:30:25,359 --> 02:30:29,120
problems through the patient portal and
4251
02:30:27,280 --> 02:30:31,280
this came up within the the master
4252
02:30:29,120 --> 02:30:33,600
general hospital system the larger
4253
02:30:31,280 --> 02:30:35,520
system where they saw that when they
4254
02:30:33,600 --> 02:30:37,520
looked at race and ethnicity there were
4255
02:30:35,520 --> 02:30:39,359
no differences in patient reported
4256
02:30:37,520 --> 02:30:41,760
outcome completion when done in the
4257
02:30:39,359 --> 02:30:43,359
office on these tablets but when they
4258
02:30:41,760 --> 02:30:45,200
switched to doing these patient reported
4259
02:30:43,359 --> 02:30:47,200
outcome measures across the whole system
4260
02:30:45,200 --> 02:30:50,080
in different departments um through the
4261
02:30:47,200 --> 02:30:52,399
patient portal saw a very steep decline
4262
02:30:50,080 --> 02:30:55,280
in um completion rates by individuals
4263
02:30:52,399 --> 02:30:57,200
who were black or hispanic latino um so
4264
02:30:55,280 --> 02:30:59,520
again thinking about equity is really
4265
02:30:57,200 --> 02:31:01,120
important as we're thinking about
4266
02:30:59,520 --> 02:31:03,040
implementing measurement-based care and
4267
02:31:01,120 --> 02:31:05,680
collecting this type of really important
4268
02:31:03,040 --> 02:31:07,359
data as we think about data available to
4269
02:31:05,680 --> 02:31:08,640
us through the ehr
4270
02:31:07,359 --> 02:31:10,080
and then lastly this has been talked
4271
02:31:08,640 --> 02:31:12,160
about quite a bit is just really
4272
02:31:10,080 --> 02:31:15,120
thinking about the ehr build so these
4273
02:31:12,160 --> 02:31:16,319
are not all the same ehr systems um i
4274
02:31:15,120 --> 02:31:18,240
think it's kind of like thinking about
4275
02:31:16,319 --> 02:31:19,840
like we all have a ford um and there are
4276
02:31:18,240 --> 02:31:21,600
many different types of models of fords
4277
02:31:19,840 --> 02:31:23,439
or different types of cars
4278
02:31:21,600 --> 02:31:26,080
and then also across systems when you're
4279
02:31:23,439 --> 02:31:28,240
outside of these really large systems um
4280
02:31:26,080 --> 02:31:30,080
the it infrastructure support is is
4281
02:31:28,240 --> 02:31:31,760
quite variable um and this can be a
4282
02:31:30,080 --> 02:31:34,560
really important factor to be thinking
4283
02:31:31,760 --> 02:31:36,319
about when we're trying to integrate um
4284
02:31:34,560 --> 02:31:37,600
these type of things into clinical care
4285
02:31:36,319 --> 02:31:40,160
into research
4286
02:31:37,600 --> 02:31:42,399
so next time i'm going to switch over to
4287
02:31:40,160 --> 02:31:45,280
now to dr rao
4288
02:31:42,399 --> 02:31:46,640
all right um sorry about that i will be
4289
02:31:45,280 --> 02:31:48,240
so um
4290
02:31:46,640 --> 02:31:51,200
thank you dr yul i will be discussing
4291
02:31:48,240 --> 02:31:53,520
some of the practical aspects of ehr
4292
02:31:51,200 --> 02:31:55,600
study design both generally and in the
4293
02:31:53,520 --> 02:31:57,359
process and the process in the context
4294
02:31:55,600 --> 02:31:58,880
of some of the projects that we have
4295
02:31:57,359 --> 02:32:00,000
been working on
4296
02:31:58,880 --> 02:32:02,000
so
4297
02:32:00,000 --> 02:32:03,680
um as you've heard um there are a couple
4298
02:32:02,000 --> 02:32:06,399
of different places where information
4299
02:32:03,680 --> 02:32:08,880
gets put into the ehr often times by
4300
02:32:06,399 --> 02:32:11,439
administrators non-clinical staff
4301
02:32:08,880 --> 02:32:12,880
um through
4302
02:32:11,439 --> 02:32:14,399
various opportunities to put information
4303
02:32:12,880 --> 02:32:16,000
into coded fields
4304
02:32:14,399 --> 02:32:18,080
and
4305
02:32:16,000 --> 02:32:21,840
in the context of measurement-based care
4306
02:32:18,080 --> 02:32:23,840
of patients to indirectly through these
4307
02:32:21,840 --> 02:32:25,680
questionnaires and then clinicians do
4308
02:32:23,840 --> 02:32:26,960
through these clinical notes and
4309
02:32:25,680 --> 02:32:29,040
what clinicians are interested in is
4310
02:32:26,960 --> 02:32:31,040
getting their work done accurately and
4311
02:32:29,040 --> 02:32:33,200
quickly um so they'll write these notes
4312
02:32:31,040 --> 02:32:36,800
for regulatory compliance for insurance
4313
02:32:33,200 --> 02:32:39,680
for colleagues in the era of open notes
4314
02:32:36,800 --> 02:32:39,930
for patients and what this means is that
4315
02:32:39,680 --> 02:32:42,160
we
4316
02:32:39,930 --> 02:32:44,000
[Music]
4317
02:32:42,160 --> 02:32:47,920
the clinical documentation does not
4318
02:32:44,000 --> 02:32:49,840
yield high fidelity data sets
4319
02:32:47,920 --> 02:32:52,000
and that's something that we need to
4320
02:32:49,840 --> 02:32:54,399
live with and keep in mind as we're
4321
02:32:52,000 --> 02:32:55,359
designing these studies so the variables
4322
02:32:54,399 --> 02:32:56,350
that we're
4323
02:32:55,359 --> 02:32:57,920
using
4324
02:32:56,350 --> 02:32:59,120
[Music]
4325
02:32:57,920 --> 02:33:01,280
need to
4326
02:32:59,120 --> 02:33:02,800
act to be appropriate
4327
02:33:01,280 --> 02:33:04,720
we'll need to actually capture the
4328
02:33:02,800 --> 02:33:07,120
concept of interest they have to be
4329
02:33:04,720 --> 02:33:10,000
available and reliable in order to
4330
02:33:07,120 --> 02:33:12,720
effectively build a model um to
4331
02:33:10,000 --> 02:33:15,120
assess or follow the clinical question
4332
02:33:12,720 --> 02:33:16,479
so these use so the features of a useful
4333
02:33:15,120 --> 02:33:17,439
variable
4334
02:33:16,479 --> 02:33:18,240
um
4335
02:33:17,439 --> 02:33:20,399
in
4336
02:33:18,240 --> 02:33:23,200
our preliminary experiences
4337
02:33:20,399 --> 02:33:25,359
living in coded fields
4338
02:33:23,200 --> 02:33:26,960
the value should be ideally discrete or
4339
02:33:25,359 --> 02:33:29,359
numerical
4340
02:33:26,960 --> 02:33:32,000
reliably updated by
4341
02:33:29,359 --> 02:33:33,200
clinicians or patients as soon as they
4342
02:33:32,000 --> 02:33:35,200
change
4343
02:33:33,200 --> 02:33:39,520
and should be carefully and accurately
4344
02:33:35,200 --> 02:33:39,520
described by everyone that's doing this
4345
02:33:41,600 --> 02:33:46,319
and so as a result of this not all
4346
02:33:44,000 --> 02:33:49,359
variables end up being encoded equally
4347
02:33:46,319 --> 02:33:51,760
some of them are pretty reliable age sex
4348
02:33:49,359 --> 02:33:53,439
is pretty straightforward race you would
4349
02:33:51,760 --> 02:33:55,439
think would be and often is but it
4350
02:33:53,439 --> 02:33:58,880
depends on the institution whether
4351
02:33:55,439 --> 02:34:00,800
um how accurately that might be captured
4352
02:33:58,880 --> 02:34:02,960
some employment information billing
4353
02:34:00,800 --> 02:34:05,040
codes visit diagnosis these are there
4354
02:34:02,960 --> 02:34:06,000
but may not map onto the concept you
4355
02:34:05,040 --> 02:34:07,680
care about
4356
02:34:06,000 --> 02:34:10,319
ed visits and hospitalizations are
4357
02:34:07,680 --> 02:34:12,960
reliable within that system and
4358
02:34:10,319 --> 02:34:15,359
insurance information is often accurate
4359
02:34:12,960 --> 02:34:17,760
other kinds of data are
4360
02:34:15,359 --> 02:34:19,760
are possible to
4361
02:34:17,760 --> 02:34:21,359
extract but require a little bit of
4362
02:34:19,760 --> 02:34:22,960
computation a little bit of work in
4363
02:34:21,359 --> 02:34:24,560
order to turn it into a useful variable
4364
02:34:22,960 --> 02:34:26,000
for your analysis
4365
02:34:24,560 --> 02:34:27,439
prompts questionnaires we'll see an
4366
02:34:26,000 --> 02:34:28,560
example in a moment
4367
02:34:27,439 --> 02:34:29,840
of
4368
02:34:28,560 --> 02:34:31,520
some of the work that needs to be done
4369
02:34:29,840 --> 02:34:34,640
in order to make use of questionnaire
4370
02:34:31,520 --> 02:34:36,000
data similarly toxicology screens sounds
4371
02:34:34,640 --> 02:34:38,080
straightforward but there are a lot of
4372
02:34:36,000 --> 02:34:39,280
talk screens you need to think about how
4373
02:34:38,080 --> 02:34:40,800
each one gets
4374
02:34:39,280 --> 02:34:42,960
interpreted
4375
02:34:40,800 --> 02:34:44,479
similarly with medications
4376
02:34:42,960 --> 02:34:47,359
it's not just the medication it's the
4377
02:34:44,479 --> 02:34:49,600
strength it's the um dosing instruction
4378
02:34:47,359 --> 02:34:52,399
it's when it was prescribed
4379
02:34:49,600 --> 02:34:54,000
um overdoses can be
4380
02:34:52,399 --> 02:34:56,160
can be extracted from the record but
4381
02:34:54,000 --> 02:34:57,680
maybe available in different places and
4382
02:34:56,160 --> 02:34:59,359
the comorbidities there may need to be
4383
02:34:57,680 --> 02:35:01,680
lumping of information
4384
02:34:59,359 --> 02:35:03,200
um in order to get uh
4385
02:35:01,680 --> 02:35:05,359
really diverse
4386
02:35:03,200 --> 02:35:07,120
diagnosis into something more tractable
4387
02:35:05,359 --> 02:35:08,960
for analysis
4388
02:35:07,120 --> 02:35:11,200
and then some information is
4389
02:35:08,960 --> 02:35:13,520
challenging education marital status
4390
02:35:11,200 --> 02:35:14,560
employment homelessness these are
4391
02:35:13,520 --> 02:35:16,880
pretty
4392
02:35:14,560 --> 02:35:19,760
basic concepts which are not necessarily
4393
02:35:16,880 --> 02:35:20,880
reliably updated or stored in coded
4394
02:35:19,760 --> 02:35:22,560
fields
4395
02:35:20,880 --> 02:35:24,080
remission status is extremely important
4396
02:35:22,560 --> 02:35:26,560
for substance use care
4397
02:35:24,080 --> 02:35:28,240
um and yet maybe embedded within the
4398
02:35:26,560 --> 02:35:30,560
note it may not always be reliably
4399
02:35:28,240 --> 02:35:32,000
updated in the physics diagnosis
4400
02:35:30,560 --> 02:35:34,240
similarly that some of the types of the
4401
02:35:32,000 --> 02:35:36,800
interventions especially psychotherapies
4402
02:35:34,240 --> 02:35:38,560
are not um reliably encoded in coded
4403
02:35:36,800 --> 02:35:41,200
fields
4404
02:35:38,560 --> 02:35:44,319
so with that said let's um walk through
4405
02:35:41,200 --> 02:35:46,160
what the process of um data in getting
4406
02:35:44,319 --> 02:35:48,080
putting data into the system and turning
4407
02:35:46,160 --> 02:35:48,880
it into analysis can look like
4408
02:35:48,080 --> 02:35:51,040
so
4409
02:35:48,880 --> 02:35:53,439
in this case dr young and i both exist
4410
02:35:51,040 --> 02:35:55,520
within epic ecosystems so when a
4411
02:35:53,439 --> 02:35:57,840
clinician or administrator puts
4412
02:35:55,520 --> 02:35:58,880
input into epic in real time it goes
4413
02:35:57,840 --> 02:36:01,439
into a
4414
02:35:58,880 --> 02:36:04,479
server called the epic calls chronicles
4415
02:36:01,439 --> 02:36:05,920
and at least in our system every night a
4416
02:36:04,479 --> 02:36:09,040
large amount of this
4417
02:36:05,920 --> 02:36:10,960
gets exported to a relational database
4418
02:36:09,040 --> 02:36:13,680
relational database called enterpr what
4419
02:36:10,960 --> 02:36:15,280
we call enterprise data warehouse and it
4420
02:36:13,680 --> 02:36:16,720
was sort of
4421
02:36:15,280 --> 02:36:19,200
inappropriate to represent this as a
4422
02:36:16,720 --> 02:36:21,120
spreadsheet but in reality it's a whole
4423
02:36:19,200 --> 02:36:22,160
bunch of tables
4424
02:36:21,120 --> 02:36:24,399
in
4425
02:36:22,160 --> 02:36:26,160
this fictional example there is
4426
02:36:24,399 --> 02:36:28,560
patient information
4427
02:36:26,160 --> 02:36:30,560
in one table medication information
4428
02:36:28,560 --> 02:36:31,600
another table appointment information
4429
02:36:30,560 --> 02:36:33,600
the third
4430
02:36:31,600 --> 02:36:35,520
and what allows people to connect
4431
02:36:33,600 --> 02:36:37,760
information across these tables is the
4432
02:36:35,520 --> 02:36:40,000
existence of these common columns
4433
02:36:37,760 --> 02:36:42,160
and because of that you might be able to
4434
02:36:40,000 --> 02:36:43,359
see that oh this patient martin
4435
02:36:42,160 --> 02:36:45,520
odergaard
4436
02:36:43,359 --> 02:36:47,680
had a
4437
02:36:45,520 --> 02:36:49,520
medication of listening to 10 milligrams
4438
02:36:47,680 --> 02:36:52,720
at some point and had an appointment on
4439
02:36:49,520 --> 02:36:54,359
january 11 2019.
4440
02:36:52,720 --> 02:36:56,399
now that's the drastic
4441
02:36:54,359 --> 02:36:58,560
oversimplification um
4442
02:36:56,399 --> 02:37:01,040
each institution may have
4443
02:36:58,560 --> 02:37:02,479
variants of this kind of data model and
4444
02:37:01,040 --> 02:37:04,960
this data model
4445
02:37:02,479 --> 02:37:07,280
may have not three but rather dozens if
4446
02:37:04,960 --> 02:37:10,720
not hundreds of tables and you need to
4447
02:37:07,280 --> 02:37:10,720
have a map to navigate these
4448
02:37:10,880 --> 02:37:14,880
in order to extract the data um from a
4449
02:37:13,280 --> 02:37:16,319
general relational database the most
4450
02:37:14,880 --> 02:37:18,960
common tool is something called
4451
02:37:16,319 --> 02:37:22,000
structured querying language
4452
02:37:18,960 --> 02:37:23,520
or institutions provide tools that
4453
02:37:22,000 --> 02:37:25,200
allow you to
4454
02:37:23,520 --> 02:37:26,800
extract this data
4455
02:37:25,200 --> 02:37:28,960
after navigating that then you can use
4456
02:37:26,800 --> 02:37:32,319
your analysis tool of choice
4457
02:37:28,960 --> 02:37:34,240
our status python to do your statistics
4458
02:37:32,319 --> 02:37:36,399
or visualizations
4459
02:37:34,240 --> 02:37:38,399
so let's look at an example
4460
02:37:36,399 --> 02:37:41,600
we were interested in
4461
02:37:38,399 --> 02:37:43,840
the clinical question does treating adhd
4462
02:37:41,600 --> 02:37:45,520
with medications improve retention in a
4463
02:37:43,840 --> 02:37:47,600
dual diagnosis clinic
4464
02:37:45,520 --> 02:37:50,560
let's talk about how we concept how we
4465
02:37:47,600 --> 02:37:53,760
operationalize some of these concepts
4466
02:37:50,560 --> 02:37:55,680
so the notion of a clinic we capture as
4467
02:37:53,760 --> 02:37:57,200
the appointment department id and it's
4468
02:37:55,680 --> 02:37:58,880
pretty straightforward to filter based
4469
02:37:57,200 --> 02:38:01,920
on
4470
02:37:58,880 --> 02:38:03,120
happy to jump in here and what uh vinod
4471
02:38:01,920 --> 02:38:04,640
was saying is
4472
02:38:03,120 --> 02:38:06,000
uh as we were
4473
02:38:04,640 --> 02:38:08,080
lining up to
4474
02:38:06,000 --> 02:38:09,600
just look at this issue this sort of
4475
02:38:08,080 --> 02:38:10,800
straightforward issue
4476
02:38:09,600 --> 02:38:13,040
we realized that there are certain
4477
02:38:10,800 --> 02:38:14,800
things that were relatively easy and
4478
02:38:13,040 --> 02:38:16,720
predictable and reliable
4479
02:38:14,800 --> 02:38:18,319
and this was a project that we did very
4480
02:38:16,720 --> 02:38:20,080
early because we hadn't gotten other
4481
02:38:18,319 --> 02:38:21,840
information yet because of the
4482
02:38:20,080 --> 02:38:22,960
implementation of the prompts that amy
4483
02:38:21,840 --> 02:38:24,640
discussed
4484
02:38:22,960 --> 02:38:26,960
and here you can see
4485
02:38:24,640 --> 02:38:30,479
the things i'm not going to repeat what
4486
02:38:26,960 --> 02:38:32,080
benad was saying but the bottom line is
4487
02:38:30,479 --> 02:38:34,080
we in here
4488
02:38:32,080 --> 02:38:35,600
looked at a thing such as medication
4489
02:38:34,080 --> 02:38:37,680
which was very important because we were
4490
02:38:35,600 --> 02:38:40,720
looking at the question of medication
4491
02:38:37,680 --> 02:38:42,479
for adhd and then we looked at the time
4492
02:38:40,720 --> 02:38:45,120
covariate about when did you get the
4493
02:38:42,479 --> 02:38:47,120
medication which became more complicated
4494
02:38:45,120 --> 02:38:49,120
we looked at medication
4495
02:38:47,120 --> 02:38:50,240
yes no and then we looked at medication
4496
02:38:49,120 --> 02:38:52,319
type and
4497
02:38:50,240 --> 02:38:54,000
we you know had to filter it by
4498
02:38:52,319 --> 02:38:56,399
stimulant yes no
4499
02:38:54,000 --> 02:38:57,680
or nonstimulant which was almost always
4500
02:38:56,399 --> 02:38:59,840
because this is an adult clinic
4501
02:38:57,680 --> 02:39:01,280
atomoxetine just to give people people
4502
02:38:59,840 --> 02:39:03,120
have clinical side
4503
02:39:01,280 --> 02:39:05,439
um and then the retention
4504
02:39:03,120 --> 02:39:07,200
uh was trying to we were modeling
4505
02:39:05,439 --> 02:39:08,720
survival curves to take a look at this
4506
02:39:07,200 --> 02:39:11,760
and we were looking at when they dropped
4507
02:39:08,720 --> 02:39:13,760
out and then had to uh looked at the
4508
02:39:11,760 --> 02:39:15,520
best of your ability and one of the
4509
02:39:13,760 --> 02:39:17,439
issues you run into if somebody drops
4510
02:39:15,520 --> 02:39:19,040
out and then comes back there's all
4511
02:39:17,439 --> 02:39:20,720
these rules you have to define when
4512
02:39:19,040 --> 02:39:24,760
you're coming up with this
4513
02:39:20,720 --> 02:39:24,760
um if you can go to the next
4514
02:39:26,720 --> 02:39:33,520
sorry about that so um the the
4515
02:39:30,479 --> 02:39:36,479
end result is when one goes through the
4516
02:39:33,520 --> 02:39:38,479
steps of um filtering the data as such
4517
02:39:36,479 --> 02:39:40,960
we can produce these survival analyses
4518
02:39:38,479 --> 02:39:43,120
um looking at when do patients
4519
02:39:40,960 --> 02:39:45,359
um drop out of the clinic
4520
02:39:43,120 --> 02:39:47,520
and as a function of whether they've
4521
02:39:45,359 --> 02:39:49,520
been prescribed medications to treat
4522
02:39:47,520 --> 02:39:51,200
adhd the
4523
02:39:49,520 --> 02:39:52,720
blue curve
4524
02:39:51,200 --> 02:39:53,760
indicates that the patient should have
4525
02:39:52,720 --> 02:39:56,240
had
4526
02:39:53,760 --> 02:39:57,840
medications for adhd and found that
4527
02:39:56,240 --> 02:39:59,200
there is uh that will be higher
4528
02:39:57,840 --> 02:40:01,520
retention and treatment
4529
02:39:59,200 --> 02:40:03,920
um for those patients unlike those who
4530
02:40:01,520 --> 02:40:05,680
do not receive um this data now note
4531
02:40:03,920 --> 02:40:06,880
this isn't really big data this is a
4532
02:40:05,680 --> 02:40:09,520
relatively
4533
02:40:06,880 --> 02:40:11,680
small sample size and one is able to
4534
02:40:09,520 --> 02:40:15,200
extract these
4535
02:40:11,680 --> 02:40:18,680
notable signals from this data
4536
02:40:15,200 --> 02:40:18,680
next slide please
4537
02:40:20,880 --> 02:40:24,880
so um
4538
02:40:23,120 --> 02:40:26,319
the
4539
02:40:24,880 --> 02:40:28,880
the next um
4540
02:40:26,319 --> 02:40:30,720
thing that i wanted to discuss was how
4541
02:40:28,880 --> 02:40:32,160
might um
4542
02:40:30,720 --> 02:40:35,680
measurement based care enriched data
4543
02:40:32,160 --> 02:40:37,439
from the ehr so as part of this we were
4544
02:40:35,680 --> 02:40:39,120
interested in asking the question are
4545
02:40:37,439 --> 02:40:41,520
people with depression more likely to
4546
02:40:39,120 --> 02:40:43,840
develop a substance use disorder
4547
02:40:41,520 --> 02:40:45,840
and we took a first crack at this um
4548
02:40:43,840 --> 02:40:49,760
which is sort of iconically
4549
02:40:45,840 --> 02:40:52,000
depicted on the right but our um
4550
02:40:49,760 --> 02:40:53,920
sense was that 23 of patients with
4551
02:40:52,000 --> 02:40:55,920
depression subsequently developed a
4552
02:40:53,920 --> 02:40:56,960
substance use disorder
4553
02:40:55,920 --> 02:40:58,880
and
4554
02:40:56,960 --> 02:41:01,920
while that was interesting these
4555
02:40:58,880 --> 02:41:04,160
diagnoses were based on basic diagnosis
4556
02:41:01,920 --> 02:41:05,359
but measurement based care allows us to
4557
02:41:04,160 --> 02:41:06,720
have a lot of information from
4558
02:41:05,359 --> 02:41:09,920
questionnaires
4559
02:41:06,720 --> 02:41:13,279
so how can that be incorporated into the
4560
02:41:09,920 --> 02:41:14,960
analysis next slide please
4561
02:41:13,279 --> 02:41:17,120
so here's what some of the challenges
4562
02:41:14,960 --> 02:41:19,120
come up when we try to do that um here's
4563
02:41:17,120 --> 02:41:22,160
a screenshot of um some of the
4564
02:41:19,120 --> 02:41:24,080
individual question questions that are
4565
02:41:22,160 --> 02:41:25,840
asked to the patient so if you look at
4566
02:41:24,080 --> 02:41:28,319
the third one how often do you have a
4567
02:41:25,840 --> 02:41:29,760
drink containing alcohol
4568
02:41:28,319 --> 02:41:31,600
many of you in these in this audience
4569
02:41:29,760 --> 02:41:34,640
will answer something non-zero just two
4570
02:41:31,600 --> 02:41:37,520
to three times per week um is not
4571
02:41:34,640 --> 02:41:39,520
necessarily indicative of a problem
4572
02:41:37,520 --> 02:41:41,200
however look at the first question how
4573
02:41:39,520 --> 02:41:42,960
many times in the past year have you
4574
02:41:41,200 --> 02:41:46,000
used an illegal drug or prescription
4575
02:41:42,960 --> 02:41:48,000
medication for non-medical reasons
4576
02:41:46,000 --> 02:41:49,840
answers that are different from xero may
4577
02:41:48,000 --> 02:41:51,600
actually uh
4578
02:41:49,840 --> 02:41:53,760
be recently interpreted as a problem and
4579
02:41:51,600 --> 02:41:55,600
should be considered as such
4580
02:41:53,760 --> 02:41:57,760
each question needs to have its own
4581
02:41:55,600 --> 02:41:59,359
threshold scent and we need sort of
4582
02:41:57,760 --> 02:42:01,520
clinical expertise in order to develop a
4583
02:41:59,359 --> 02:42:04,479
mapping in order to appropriately use
4584
02:42:01,520 --> 02:42:06,960
these questionnaire data um and use it
4585
02:42:04,479 --> 02:42:08,399
to help define an outcome that you want
4586
02:42:06,960 --> 02:42:10,640
to use in your
4587
02:42:08,399 --> 02:42:13,040
further analyses so this is some of what
4588
02:42:10,640 --> 02:42:14,399
needs to be worked out when using
4589
02:42:13,040 --> 02:42:16,479
problems data
4590
02:42:14,399 --> 02:42:18,800
with medical record
4591
02:42:16,479 --> 02:42:20,640
next slide please
4592
02:42:18,800 --> 02:42:22,960
so to end with opportunities and
4593
02:42:20,640 --> 02:42:24,720
challenges with these ehr studies they
4594
02:42:22,960 --> 02:42:26,640
have a because they're
4595
02:42:24,720 --> 02:42:27,840
fundamentally retrospective
4596
02:42:26,640 --> 02:42:28,720
and
4597
02:42:27,840 --> 02:42:30,560
they're
4598
02:42:28,720 --> 02:42:33,200
it's a real opportunity to pick up
4599
02:42:30,560 --> 02:42:36,160
subtle signals that are present
4600
02:42:33,200 --> 02:42:40,080
that can then be used to this
4601
02:42:36,160 --> 02:42:41,680
to define testable hypotheses which
4602
02:42:40,080 --> 02:42:43,040
future
4603
02:42:41,680 --> 02:42:44,640
randomized trials might be able to
4604
02:42:43,040 --> 02:42:46,319
better get at
4605
02:42:44,640 --> 02:42:48,800
next
4606
02:42:46,319 --> 02:42:50,560
and as we've talked about um there is a
4607
02:42:48,800 --> 02:42:52,479
real potential for integrating across
4608
02:42:50,560 --> 02:42:54,880
health care systems we've seen examples
4609
02:42:52,479 --> 02:42:56,000
of that in today's sessions what they
4610
02:42:54,880 --> 02:42:58,160
probably haven't gone through with all
4611
02:42:56,000 --> 02:43:01,120
the challenges they've dealt with um
4612
02:42:58,160 --> 02:43:04,240
merging across different ehrs even uh um
4613
02:43:01,120 --> 02:43:05,920
dr yule and i um are we both using epic
4614
02:43:04,240 --> 02:43:07,840
slightly different flavors of it and
4615
02:43:05,920 --> 02:43:08,960
there are challenges to navigate with
4616
02:43:07,840 --> 02:43:10,640
that
4617
02:43:08,960 --> 02:43:12,399
and one thing that needs to be kept in
4618
02:43:10,640 --> 02:43:14,880
mind um
4619
02:43:12,399 --> 02:43:15,920
with new nih rules regarding
4620
02:43:14,880 --> 02:43:18,160
um
4621
02:43:15,920 --> 02:43:19,040
sharing of data sets any information
4622
02:43:18,160 --> 02:43:20,800
that
4623
02:43:19,040 --> 02:43:23,520
you extract for
4624
02:43:20,800 --> 02:43:25,760
for an electronic health record-based
4625
02:43:23,520 --> 02:43:26,640
data set you need to be comfortable with
4626
02:43:25,760 --> 02:43:27,760
sharing
4627
02:43:26,640 --> 02:43:29,120
that information so that's just
4628
02:43:27,760 --> 02:43:32,160
something needs to be kept in mind
4629
02:43:29,120 --> 02:43:32,160
during study design
4630
02:43:32,800 --> 02:43:36,560
we've already seen examples of how
4631
02:43:34,640 --> 02:43:37,840
natural language processing can be used
4632
02:43:36,560 --> 02:43:40,640
to
4633
02:43:37,840 --> 02:43:41,760
enrich the available out measures um
4634
02:43:40,640 --> 02:43:44,000
that are
4635
02:43:41,760 --> 02:43:46,240
available in some situations that can be
4636
02:43:44,000 --> 02:43:47,600
done really well it's going to be a work
4637
02:43:46,240 --> 02:43:50,160
in progress to develop this we can
4638
02:43:47,600 --> 02:43:51,520
capture more ideas and then of course
4639
02:43:50,160 --> 02:43:54,000
things are happening in real time we've
4640
02:43:51,520 --> 02:43:55,840
seen examples today of how
4641
02:43:54,000 --> 02:43:57,600
information about the pandemic has been
4642
02:43:55,840 --> 02:43:58,800
captured and
4643
02:43:57,600 --> 02:44:01,680
identified
4644
02:43:58,800 --> 02:44:04,160
and as changes in policy change toxins
4645
02:44:01,680 --> 02:44:06,640
or environmental stressors
4646
02:44:04,160 --> 02:44:08,319
emerge these can better be tracked
4647
02:44:06,640 --> 02:44:11,040
and we can intervene better for our
4648
02:44:08,319 --> 02:44:13,439
patients so with that thank you for the
4649
02:44:11,040 --> 02:44:16,880
tolerating the technology interruptions
4650
02:44:13,439 --> 02:44:16,880
and we'll go on to the next talk
4651
02:44:18,560 --> 02:44:22,640
no problem
4652
02:44:19,920 --> 02:44:24,240
um sarah
4653
02:44:22,640 --> 02:44:26,960
are you
4654
02:44:24,240 --> 02:44:26,960
able to share
4655
02:44:27,359 --> 02:44:31,040
yes can everyone see
4656
02:44:29,200 --> 02:44:34,399
yes perfect
4657
02:44:31,040 --> 02:44:35,920
so i um want to thank everyone it is a
4658
02:44:34,399 --> 02:44:37,120
blessing that i get to go last if
4659
02:44:35,920 --> 02:44:38,560
there's a lot that i'm actually not
4660
02:44:37,120 --> 02:44:40,880
going to cover that i didn't initially
4661
02:44:38,560 --> 02:44:42,240
plan but i'm going to give the talk that
4662
02:44:40,880 --> 02:44:44,399
i want to give now
4663
02:44:42,240 --> 02:44:46,160
um having heard all of your talks which
4664
02:44:44,399 --> 02:44:47,840
really lay the foundation for some of
4665
02:44:46,160 --> 02:44:50,560
the work that's been done here and thank
4666
02:44:47,840 --> 02:44:51,840
you to nida for the continued support of
4667
02:44:50,560 --> 02:44:52,800
the research that i'm talking through
4668
02:44:51,840 --> 02:44:53,520
today
4669
02:44:52,800 --> 02:44:54,560
um
4670
02:44:53,520 --> 02:44:56,240
so
4671
02:44:54,560 --> 02:44:58,640
very briefly
4672
02:44:56,240 --> 02:44:59,680
um we know that substance use prevention
4673
02:44:58,640 --> 02:45:02,800
efforts
4674
02:44:59,680 --> 02:45:04,800
in adolescence typically rely on systems
4675
02:45:02,800 --> 02:45:07,359
so this can be the family system it's
4676
02:45:04,800 --> 02:45:08,720
also peers that are influencing
4677
02:45:07,359 --> 02:45:10,479
the experience that young people have in
4678
02:45:08,720 --> 02:45:12,160
their exposure to substance use as well
4679
02:45:10,479 --> 02:45:14,319
as schools
4680
02:45:12,160 --> 02:45:17,439
social norms and policies and all of
4681
02:45:14,319 --> 02:45:19,840
these factors um introduce opportunities
4682
02:45:17,439 --> 02:45:21,600
um for threat when we uh have young
4683
02:45:19,840 --> 02:45:24,080
people who are experiencing other social
4684
02:45:21,600 --> 02:45:25,760
vulnerability as dr chisholm laid out
4685
02:45:24,080 --> 02:45:28,000
and there's an opportunity as was
4686
02:45:25,760 --> 02:45:29,760
highlighted by dr jensen to also
4687
02:45:28,000 --> 02:45:31,760
consider the health care system as an
4688
02:45:29,760 --> 02:45:33,600
opportunity for prevention
4689
02:45:31,760 --> 02:45:35,200
um we know and i'm not going to go
4690
02:45:33,600 --> 02:45:37,040
through this in detail but we know that
4691
02:45:35,200 --> 02:45:38,720
families are relying on pediatricians
4692
02:45:37,040 --> 02:45:40,240
and are coming to pediatricians that
4693
02:45:38,720 --> 02:45:42,160
screening is normal we talked about
4694
02:45:40,240 --> 02:45:43,760
confidentiality earlier today as well
4695
02:45:42,160 --> 02:45:46,160
which is important
4696
02:45:43,760 --> 02:45:48,640
um and that access to healthcare systems
4697
02:45:46,160 --> 02:45:51,279
is at least intended to be universal
4698
02:45:48,640 --> 02:45:52,880
but that there is opportunity to explore
4699
02:45:51,279 --> 02:45:56,240
whether
4700
02:45:52,880 --> 02:45:58,960
young people can actually benefit from
4701
02:45:56,240 --> 02:46:01,279
prevention and substance use screening
4702
02:45:58,960 --> 02:46:03,040
when we look across the broad spectrum
4703
02:46:01,279 --> 02:46:06,160
of where young people are seen and not
4704
02:46:03,040 --> 02:46:08,479
necessarily only in primary care
4705
02:46:06,160 --> 02:46:10,720
but specifically related to foster care
4706
02:46:08,479 --> 02:46:12,319
which is the population that i work with
4707
02:46:10,720 --> 02:46:14,000
there's a whole lot of social system
4708
02:46:12,319 --> 02:46:16,560
disruption that's happening that might
4709
02:46:14,000 --> 02:46:18,720
actually exacerbate risk so we know
4710
02:46:16,560 --> 02:46:21,040
there are over 400 000 young people in
4711
02:46:18,720 --> 02:46:23,600
foster care on any given day here in the
4712
02:46:21,040 --> 02:46:25,439
united states about 40 of those are ages
4713
02:46:23,600 --> 02:46:27,120
10 and older which indicates that they
4714
02:46:25,439 --> 02:46:30,240
are vulnerable for
4715
02:46:27,120 --> 02:46:32,160
voluntarily initiating substance use and
4716
02:46:30,240 --> 02:46:34,960
that there are disparities with respect
4717
02:46:32,160 --> 02:46:37,040
to race ethnicity and poverty on who
4718
02:46:34,960 --> 02:46:38,880
comes into foster care such that we have
4719
02:46:37,040 --> 02:46:40,960
an over-representation of young people
4720
02:46:38,880 --> 02:46:42,800
who have experienced poverty and young
4721
02:46:40,960 --> 02:46:45,840
people of color and foster care compared
4722
02:46:42,800 --> 02:46:47,439
to the general population
4723
02:46:45,840 --> 02:46:49,439
that those that are coming into foster
4724
02:46:47,439 --> 02:46:50,960
care are placed outside of their family
4725
02:46:49,439 --> 02:46:52,800
home which means that they are
4726
02:46:50,960 --> 02:46:54,720
frequently disrupted from things like
4727
02:46:52,800 --> 02:46:56,399
school healthcare and social settings
4728
02:46:54,720 --> 02:46:58,560
which means a lot of the opportunities
4729
02:46:56,399 --> 02:47:00,479
for prevention that we tend to think of
4730
02:46:58,560 --> 02:47:01,760
as being effective for prevention
4731
02:47:00,479 --> 02:47:03,920
delivery
4732
02:47:01,760 --> 02:47:05,680
for these young people are disrupted and
4733
02:47:03,920 --> 02:47:07,920
even though we have an increased
4734
02:47:05,680 --> 02:47:08,800
emphasis here in the united states now
4735
02:47:07,920 --> 02:47:10,720
on
4736
02:47:08,800 --> 02:47:12,399
kinship caregiving with the goal that
4737
02:47:10,720 --> 02:47:13,840
young people might come into foster care
4738
02:47:12,399 --> 02:47:15,600
but they won't have as much social
4739
02:47:13,840 --> 02:47:18,479
disruption we're still seeing a lot of
4740
02:47:15,600 --> 02:47:21,200
changes in school and healthcare
4741
02:47:18,479 --> 02:47:23,359
this contributes to exacerbated risk for
4742
02:47:21,200 --> 02:47:26,319
substance use for adolescents and adults
4743
02:47:23,359 --> 02:47:28,160
who have experienced foster care on top
4744
02:47:26,319 --> 02:47:30,560
of mechanisms we already know are
4745
02:47:28,160 --> 02:47:32,080
contributing to increased risk
4746
02:47:30,560 --> 02:47:34,640
and that's things like maltreatment and
4747
02:47:32,080 --> 02:47:35,920
parental substance use and i'm going to
4748
02:47:34,640 --> 02:47:37,520
specifically highlight parental
4749
02:47:35,920 --> 02:47:39,200
substance use here because you'll see it
4750
02:47:37,520 --> 02:47:41,120
repeated later on
4751
02:47:39,200 --> 02:47:43,279
so the first of two studies that have
4752
02:47:41,120 --> 02:47:45,520
been funded by nida
4753
02:47:43,279 --> 02:47:47,760
were what i call careful which is where
4754
02:47:45,520 --> 02:47:49,600
we linked child welfare
4755
02:47:47,760 --> 02:47:51,920
records with electronic health records
4756
02:47:49,600 --> 02:47:53,359
data for young people in hamilton county
4757
02:47:51,920 --> 02:47:55,760
which is the county that cincinnati
4758
02:47:53,359 --> 02:47:58,000
children sits in um
4759
02:47:55,760 --> 02:47:59,680
with their ehr data
4760
02:47:58,000 --> 02:48:02,960
if they were in foster care on at least
4761
02:47:59,680 --> 02:48:04,800
one day between 2012 and 2017 and they
4762
02:48:02,960 --> 02:48:06,720
were ages 10 or older
4763
02:48:04,800 --> 02:48:09,279
we were successful at linking more than
4764
02:48:06,720 --> 02:48:10,880
99 of those data so there were three
4765
02:48:09,279 --> 02:48:12,720
young people in our whole sample that we
4766
02:48:10,880 --> 02:48:14,319
weren't able to link records for and i'm
4767
02:48:12,720 --> 02:48:15,680
happy to have a separate conversation
4768
02:48:14,319 --> 02:48:17,840
about how
4769
02:48:15,680 --> 02:48:19,399
that process occurred but we ended up
4770
02:48:17,840 --> 02:48:22,080
with a cohort of
4771
02:48:19,399 --> 02:48:24,880
2787 young people who were represented
4772
02:48:22,080 --> 02:48:26,160
in our ehr at cincinnati children's
4773
02:48:24,880 --> 02:48:28,240
and then were able to extract a
4774
02:48:26,160 --> 02:48:31,200
comparison sample who was matched
4775
02:48:28,240 --> 02:48:33,600
one-to-one on gender race and ethnicity
4776
02:48:31,200 --> 02:48:36,479
date of birth within six months medicaid
4777
02:48:33,600 --> 02:48:38,399
status um and received primary care here
4778
02:48:36,479 --> 02:48:40,319
at cincinnati children's and we're never
4779
02:48:38,399 --> 02:48:42,080
in foster care so that we really were
4780
02:48:40,319 --> 02:48:45,279
looking at differences in
4781
02:48:42,080 --> 02:48:47,680
foster care involvement on screening and
4782
02:48:45,279 --> 02:48:49,040
referral practices and the goal of this
4783
02:48:47,680 --> 02:48:50,880
was to understand differences in
4784
02:48:49,040 --> 02:48:52,720
substance use screening and when our
4785
02:48:50,880 --> 02:48:55,120
health care system is identifying these
4786
02:48:52,720 --> 02:48:56,800
young people as being at risk so that we
4787
02:48:55,120 --> 02:48:58,640
could start seeing if the health care
4788
02:48:56,800 --> 02:48:59,680
system is an appropriate target for
4789
02:48:58,640 --> 02:49:01,760
healthcare
4790
02:48:59,680 --> 02:49:03,520
for prevention delivery
4791
02:49:01,760 --> 02:49:05,680
and also to identify disparities in
4792
02:49:03,520 --> 02:49:08,399
healthcare access that might have an
4793
02:49:05,680 --> 02:49:10,240
impact on substance use prevention
4794
02:49:08,399 --> 02:49:12,479
not surprisingly based on the data that
4795
02:49:10,240 --> 02:49:14,640
we saw earlier today
4796
02:49:12,479 --> 02:49:16,800
we when we pulled the structured ehr
4797
02:49:14,640 --> 02:49:18,240
data discovered that
4798
02:49:16,800 --> 02:49:21,120
only four percent of our clinical
4799
02:49:18,240 --> 02:49:23,600
encounters contain structured data about
4800
02:49:21,120 --> 02:49:26,399
substance use which obviously is a hard
4801
02:49:23,600 --> 02:49:28,720
stop um and i appreciate the challenges
4802
02:49:26,399 --> 02:49:32,240
that dr johnson experienced with his
4803
02:49:28,720 --> 02:49:34,080
uh study as well um so for us uh because
4804
02:49:32,240 --> 02:49:36,479
we knew that there had to be more data
4805
02:49:34,080 --> 02:49:38,319
in the ehr based on conversations we had
4806
02:49:36,479 --> 02:49:40,000
with our clinical team and
4807
02:49:38,319 --> 02:49:41,840
my colleagues in adolescent medicine in
4808
02:49:40,000 --> 02:49:43,439
our foster care clinics that i knew were
4809
02:49:41,840 --> 02:49:44,800
talking to young people about substance
4810
02:49:43,439 --> 02:49:46,880
use we did a
4811
02:49:44,800 --> 02:49:48,399
quick chart review and as all of you
4812
02:49:46,880 --> 02:49:50,319
have already discovered and we've
4813
02:49:48,399 --> 02:49:51,840
covered thoroughly today um that's
4814
02:49:50,319 --> 02:49:54,080
because that screening was in
4815
02:49:51,840 --> 02:49:56,640
unstructured clinical notes
4816
02:49:54,080 --> 02:49:59,040
and with us and this is not surprising
4817
02:49:56,640 --> 02:50:00,800
given that um the screening practices
4818
02:49:59,040 --> 02:50:03,359
were also not standardized across our
4819
02:50:00,800 --> 02:50:06,000
hospital system we were seeing a lot of
4820
02:50:03,359 --> 02:50:07,439
ambiguity in those clinical notes where
4821
02:50:06,000 --> 02:50:09,120
frequently
4822
02:50:07,439 --> 02:50:10,880
the reference to substance use was
4823
02:50:09,120 --> 02:50:13,040
actually to apparent or where it would
4824
02:50:10,880 --> 02:50:14,640
be difficult for us to take an out of
4825
02:50:13,040 --> 02:50:16,479
the box
4826
02:50:14,640 --> 02:50:18,880
natural language processing algorithm
4827
02:50:16,479 --> 02:50:20,720
and actually apply it to the data that
4828
02:50:18,880 --> 02:50:23,120
we were seeing with this population so i
4829
02:50:20,720 --> 02:50:24,880
give two real examples there one patient
4830
02:50:23,120 --> 02:50:26,960
has a neutral exposure to drugs and
4831
02:50:24,880 --> 02:50:28,479
alcohol and a second she discovered he
4832
02:50:26,960 --> 02:50:30,240
began drinking alcohol and using
4833
02:50:28,479 --> 02:50:32,640
marijuana where it would have been
4834
02:50:30,240 --> 02:50:34,720
difficult to know whether she is the mom
4835
02:50:32,640 --> 02:50:37,200
or whether she is the daughter who's
4836
02:50:34,720 --> 02:50:39,760
discovered her father's
4837
02:50:37,200 --> 02:50:41,920
substance use for example so
4838
02:50:39,760 --> 02:50:43,840
led by an amazing study coordinator
4839
02:50:41,920 --> 02:50:46,880
katie nass in my lab
4840
02:50:43,840 --> 02:50:48,640
we recruited a whole host of undergrads
4841
02:50:46,880 --> 02:50:51,840
from the university of cincinnati who
4842
02:50:48,640 --> 02:50:53,840
helped us to manually code all 26 000
4843
02:50:51,840 --> 02:50:56,640
notes that were represented by these
4844
02:50:53,840 --> 02:50:58,880
data um with high reliability we have
4845
02:50:56,640 --> 02:51:00,640
kappas about 0.8
4846
02:50:58,880 --> 02:51:02,479
and so we treated these clinical notes
4847
02:51:00,640 --> 02:51:04,960
as if they were
4848
02:51:02,479 --> 02:51:05,760
transcripts from qualitative interviews
4849
02:51:04,960 --> 02:51:07,040
or
4850
02:51:05,760 --> 02:51:08,720
um
4851
02:51:07,040 --> 02:51:10,560
the clinical data that we tend to get
4852
02:51:08,720 --> 02:51:13,120
from child welfare reports where we're
4853
02:51:10,560 --> 02:51:16,240
coding for maltreatment exposure
4854
02:51:13,120 --> 02:51:18,399
to really ensure that we had accurate
4855
02:51:16,240 --> 02:51:19,840
substance use data
4856
02:51:18,399 --> 02:51:21,600
on both the
4857
02:51:19,840 --> 02:51:22,880
foster care sample and the comparison
4858
02:51:21,600 --> 02:51:24,479
sample
4859
02:51:22,880 --> 02:51:26,319
and what we found with that and again i
4860
02:51:24,479 --> 02:51:28,080
want to emphasize that this is not with
4861
02:51:26,319 --> 02:51:30,479
us changing anything about the health
4862
02:51:28,080 --> 02:51:31,680
care system this is just what was in the
4863
02:51:30,479 --> 02:51:33,439
data
4864
02:51:31,680 --> 02:51:35,680
we were actually able to identify that
4865
02:51:33,439 --> 02:51:37,439
over 70 percent of our population had
4866
02:51:35,680 --> 02:51:40,399
been screened at least once over that
4867
02:51:37,439 --> 02:51:42,640
five-year period for substance use um
4868
02:51:40,399 --> 02:51:44,960
and not surprising for all of the
4869
02:51:42,640 --> 02:51:47,359
conversations we've had today
4870
02:51:44,960 --> 02:51:49,439
there was significantly more likely that
4871
02:51:47,359 --> 02:51:51,359
the positive screening information was
4872
02:51:49,439 --> 02:51:53,279
going to be stored in the unstructured
4873
02:51:51,359 --> 02:51:56,479
compared to structured data fields even
4874
02:51:53,279 --> 02:51:58,319
though we had a place in the ehr
4875
02:51:56,479 --> 02:51:59,680
for individuals to record that
4876
02:51:58,319 --> 02:52:01,920
information
4877
02:51:59,680 --> 02:52:03,760
we also found that foster youth were
4878
02:52:01,920 --> 02:52:05,920
significantly more likely to receive
4879
02:52:03,760 --> 02:52:08,000
screening and part of that is because
4880
02:52:05,920 --> 02:52:10,000
screening had been somewhat standardized
4881
02:52:08,000 --> 02:52:11,520
in our foster care clinic
4882
02:52:10,000 --> 02:52:13,359
and so we were seeing a difference
4883
02:52:11,520 --> 02:52:15,279
between those that were in foster care
4884
02:52:13,359 --> 02:52:17,200
versus the young people that weren't in
4885
02:52:15,279 --> 02:52:19,120
foster care but were receiving primary
4886
02:52:17,200 --> 02:52:21,120
care because of differences in screening
4887
02:52:19,120 --> 02:52:22,880
across those settings
4888
02:52:21,120 --> 02:52:24,080
among those young people who were
4889
02:52:22,880 --> 02:52:26,080
screened
4890
02:52:24,080 --> 02:52:28,560
we were able to do survival analysis to
4891
02:52:26,080 --> 02:52:30,399
look at when substance use was initiated
4892
02:52:28,560 --> 02:52:31,840
and what we found was consistent with
4893
02:52:30,399 --> 02:52:33,359
the literature and that is that our
4894
02:52:31,840 --> 02:52:36,160
health care system
4895
02:52:33,359 --> 02:52:38,399
is uh effectively identifying when young
4896
02:52:36,160 --> 02:52:40,080
people initiate substance use and that
4897
02:52:38,399 --> 02:52:42,240
youth in foster care are initiating
4898
02:52:40,080 --> 02:52:45,040
substances earlier and a higher
4899
02:52:42,240 --> 02:52:47,200
frequency than the comparison sample
4900
02:52:45,040 --> 02:52:49,040
this was important because it was
4901
02:52:47,200 --> 02:52:50,960
demonstrated to our health care system
4902
02:52:49,040 --> 02:52:52,800
for the first time that actually there
4903
02:52:50,960 --> 02:52:54,319
was an opportunity for us to engage in
4904
02:52:52,800 --> 02:52:55,600
some of these prevention efforts and
4905
02:52:54,319 --> 02:52:57,920
we'll talk a little bit more about what
4906
02:52:55,600 --> 02:52:59,439
we did with that here in a minute
4907
02:52:57,920 --> 02:53:01,279
um but
4908
02:52:59,439 --> 02:53:03,680
we were also able to look at predictive
4909
02:53:01,279 --> 02:53:05,920
data and i think the work of dr chisholm
4910
02:53:03,680 --> 02:53:07,680
sets this up quite nicely where we were
4911
02:53:05,920 --> 02:53:10,560
able to look to see what the
4912
02:53:07,680 --> 02:53:13,279
true impact of child welfare involvement
4913
02:53:10,560 --> 02:53:15,920
and other factors was on
4914
02:53:13,279 --> 02:53:17,600
exacerbating risk for young people and
4915
02:53:15,920 --> 02:53:19,920
what we found there because we had
4916
02:53:17,600 --> 02:53:21,680
reliable information about foster care
4917
02:53:19,920 --> 02:53:23,680
status from our child welfare record
4918
02:53:21,680 --> 02:53:25,920
that was linked is that a history of
4919
02:53:23,680 --> 02:53:28,560
foster care significantly exacerbated
4920
02:53:25,920 --> 02:53:31,600
risk with an um
4921
02:53:28,560 --> 02:53:34,720
uh irr of around point eight
4922
02:53:31,600 --> 02:53:36,560
um that that somewhat changed over time
4923
02:53:34,720 --> 02:53:38,000
but what was more interesting for us is
4924
02:53:36,560 --> 02:53:40,319
that we found that there was a
4925
02:53:38,000 --> 02:53:42,399
protective effect of being in foster
4926
02:53:40,319 --> 02:53:43,760
care at age 13 so these are young people
4927
02:53:42,399 --> 02:53:44,800
that were screening
4928
02:53:43,760 --> 02:53:46,160
um
4929
02:53:44,800 --> 02:53:47,920
at the time of their
4930
02:53:46,160 --> 02:53:50,319
around the age of time of their 13th
4931
02:53:47,920 --> 02:53:52,399
birthday um but that seemed to be
4932
02:53:50,319 --> 02:53:54,720
protective for foster care placement but
4933
02:53:52,399 --> 02:53:57,680
that shifted over time so
4934
02:53:54,720 --> 02:54:00,800
the impact of being in foster care
4935
02:53:57,680 --> 02:54:02,240
changes with age on risk for initiating
4936
02:54:00,800 --> 02:54:04,479
substance use
4937
02:54:02,240 --> 02:54:07,840
and we saw similar interactions with age
4938
02:54:04,479 --> 02:54:08,880
for being a woman or a young person of
4939
02:54:07,840 --> 02:54:10,080
color
4940
02:54:08,880 --> 02:54:11,520
i mean that's consistent with the
4941
02:54:10,080 --> 02:54:12,800
literature
4942
02:54:11,520 --> 02:54:15,040
in general
4943
02:54:12,800 --> 02:54:16,800
we also detected significant differences
4944
02:54:15,040 --> 02:54:19,040
in health care utilization for these two
4945
02:54:16,800 --> 02:54:21,200
populations where
4946
02:54:19,040 --> 02:54:23,359
a first look
4947
02:54:21,200 --> 02:54:24,800
we found that young people in foster
4948
02:54:23,359 --> 02:54:26,960
care were
4949
02:54:24,800 --> 02:54:28,800
using more health care across a variety
4950
02:54:26,960 --> 02:54:31,439
of different settings compared to young
4951
02:54:28,800 --> 02:54:33,439
people that were not in foster care
4952
02:54:31,439 --> 02:54:35,840
but interestingly and i think this
4953
02:54:33,439 --> 02:54:37,840
echoes some of the work of others
4954
02:54:35,840 --> 02:54:39,520
once we accounted for substance use
4955
02:54:37,840 --> 02:54:40,800
those effects
4956
02:54:39,520 --> 02:54:43,439
were reversed
4957
02:54:40,800 --> 02:54:45,760
particularly for primary care
4958
02:54:43,439 --> 02:54:48,479
and so what this suggests to us is that
4959
02:54:45,760 --> 02:54:51,120
actually we have some differences in
4960
02:54:48,479 --> 02:54:52,560
access to healthcare services based on
4961
02:54:51,120 --> 02:54:54,720
whether young people are using
4962
02:54:52,560 --> 02:54:56,319
substances or not
4963
02:54:54,720 --> 02:54:58,479
where likely those young people are
4964
02:54:56,319 --> 02:55:00,240
going to be seen more often in emergency
4965
02:54:58,479 --> 02:55:02,800
care settings and are going to be less
4966
02:55:00,240 --> 02:55:06,240
likely to be seen in primary care
4967
02:55:02,800 --> 02:55:08,080
and so thinking about what we need to do
4968
02:55:06,240 --> 02:55:10,399
to make sure that we have
4969
02:55:08,080 --> 02:55:12,160
accurate data across all settings when
4970
02:55:10,399 --> 02:55:14,240
we're thinking about trying to implement
4971
02:55:12,160 --> 02:55:16,080
and standardize screening
4972
02:55:14,240 --> 02:55:17,680
for substance use and where that data is
4973
02:55:16,080 --> 02:55:18,960
going to come from is important that
4974
02:55:17,680 --> 02:55:20,160
young people are seen in lots of
4975
02:55:18,960 --> 02:55:22,080
different settings and we have to
4976
02:55:20,160 --> 02:55:23,120
account for that both in our research
4977
02:55:22,080 --> 02:55:25,279
and in what we're going to do with
4978
02:55:23,120 --> 02:55:27,520
clinical care
4979
02:55:25,279 --> 02:55:29,279
it turned out that the coded data which
4980
02:55:27,520 --> 02:55:31,120
we weren't initially setting out to
4981
02:55:29,279 --> 02:55:33,439
develop ai
4982
02:55:31,120 --> 02:55:35,600
around was actually really great as a
4983
02:55:33,439 --> 02:55:37,279
training set and so we partnered with dr
4984
02:55:35,600 --> 02:55:38,720
yiz auni who was here at cincinnati
4985
02:55:37,279 --> 02:55:40,880
children's at the time and has since
4986
02:55:38,720 --> 02:55:41,760
moved to kaiser
4987
02:55:40,880 --> 02:55:45,760
who
4988
02:55:41,760 --> 02:55:48,080
helps to develop some rule-based matches
4989
02:55:45,760 --> 02:55:49,680
matching algorithms as well as some nlp
4990
02:55:48,080 --> 02:55:52,160
and deep learning models so that we
4991
02:55:49,680 --> 02:55:54,160
could take that structured data when it
4992
02:55:52,160 --> 02:55:55,279
was present because it was there some of
4993
02:55:54,160 --> 02:55:57,279
the time
4994
02:55:55,279 --> 02:55:59,120
and the unstructured clinical narrative
4995
02:55:57,279 --> 02:55:59,840
and integrate that together
4996
02:55:59,120 --> 02:56:02,240
to
4997
02:55:59,840 --> 02:56:03,920
set up a series of classifications so
4998
02:56:02,240 --> 02:56:05,840
that young people are classified based
4999
02:56:03,920 --> 02:56:08,160
on whether or not they have received any
5000
02:56:05,840 --> 02:56:09,920
screening so had they been screened yes
5001
02:56:08,160 --> 02:56:12,479
or no and then if they had been screened
5002
02:56:09,920 --> 02:56:14,319
was that screening positive or negative
5003
02:56:12,479 --> 02:56:16,800
for each of the different substances or
5004
02:56:14,319 --> 02:56:18,720
for any substance use if it was generic
5005
02:56:16,800 --> 02:56:20,640
and then we added another category that
5006
02:56:18,720 --> 02:56:22,080
was actually family history so was there
5007
02:56:20,640 --> 02:56:23,359
an evidence of family history of
5008
02:56:22,080 --> 02:56:26,479
substance use
5009
02:56:23,359 --> 02:56:28,479
um and it turned out that uh linking
5010
02:56:26,479 --> 02:56:30,479
this structured and unstructured data
5011
02:56:28,479 --> 02:56:32,800
together across all of these different
5012
02:56:30,479 --> 02:56:35,200
sets was very important
5013
02:56:32,800 --> 02:56:37,120
because we were able to secure a samsa
5014
02:56:35,200 --> 02:56:39,520
grant to implement standardized
5015
02:56:37,120 --> 02:56:41,680
screening the craft on welcome tablets
5016
02:56:39,520 --> 02:56:42,720
and are now doing substance use
5017
02:56:41,680 --> 02:56:44,640
um
5018
02:56:42,720 --> 02:56:46,080
brief intervention and refer screening
5019
02:56:44,640 --> 02:56:47,200
brief intervention and refer all the
5020
02:56:46,080 --> 02:56:49,200
treatment
5021
02:56:47,200 --> 02:56:51,840
where now all of our young people are
5022
02:56:49,200 --> 02:56:53,439
receiving um the craft on welcome
5023
02:56:51,840 --> 02:56:55,760
tablets at the beginning of their visit
5024
02:56:53,439 --> 02:56:56,960
so that they can report themselves
5025
02:56:55,760 --> 02:56:59,120
and that screening is happening
5026
02:56:56,960 --> 02:57:01,840
universally we've just started this so
5027
02:56:59,120 --> 02:57:04,319
we are i don't have any um
5028
02:57:01,840 --> 02:57:06,160
any hard data to present but i do want
5029
02:57:04,319 --> 02:57:07,520
to share some learnings early on that
5030
02:57:06,160 --> 02:57:09,600
we've had
5031
02:57:07,520 --> 02:57:11,359
which is first that that when we
5032
02:57:09,600 --> 02:57:12,880
implemented we decided that we would
5033
02:57:11,359 --> 02:57:14,800
train our health care providers to
5034
02:57:12,880 --> 02:57:16,720
validate abstinence
5035
02:57:14,800 --> 02:57:19,359
um so those young people that reported
5036
02:57:16,720 --> 02:57:21,120
that they weren't using substances and
5037
02:57:19,359 --> 02:57:23,120
in part driven by some conversations i
5038
02:57:21,120 --> 02:57:25,120
had with dr sterling
5039
02:57:23,120 --> 02:57:26,960
and that was turn has turned out to be
5040
02:57:25,120 --> 02:57:29,040
an opportunity to confirm screening
5041
02:57:26,960 --> 02:57:30,720
results so now we have a healthcare
5042
02:57:29,040 --> 02:57:32,640
provider who says i'm so proud of you
5043
02:57:30,720 --> 02:57:34,000
for being abstinent and that young
5044
02:57:32,640 --> 02:57:36,960
person will say
5045
02:57:34,000 --> 02:57:39,359
actually i'm not um and and that's being
5046
02:57:36,960 --> 02:57:41,840
documented in our clinical notes and so
5047
02:57:39,359 --> 02:57:43,920
by integrating our standardized
5048
02:57:41,840 --> 02:57:46,080
structured data with our unstandardized
5049
02:57:43,920 --> 02:57:47,520
screening results we're able to confirm
5050
02:57:46,080 --> 02:57:49,439
that validation
5051
02:57:47,520 --> 02:57:51,200
um and report discrepancies so that
5052
02:57:49,439 --> 02:57:52,960
clinicians and researchers can use both
5053
02:57:51,200 --> 02:57:54,640
pieces of information
5054
02:57:52,960 --> 02:57:56,399
and we're finding that that's happening
5055
02:57:54,640 --> 02:57:58,160
so far and we're just two months into
5056
02:57:56,399 --> 02:58:00,080
this but in about five percent of our
5057
02:57:58,160 --> 02:58:02,080
population
5058
02:58:00,080 --> 02:58:03,279
it also allows us to ensure that our
5059
02:58:02,080 --> 02:58:06,160
behavioral health providers are
5060
02:58:03,279 --> 02:58:08,000
addressing you so we can pull that
5061
02:58:06,160 --> 02:58:09,840
pull that unstructured data and ensure
5062
02:58:08,000 --> 02:58:11,359
that even if they aren't being seen in
5063
02:58:09,840 --> 02:58:12,960
our clinic where we have standardized
5064
02:58:11,359 --> 02:58:15,040
universal screening that we have that
5065
02:58:12,960 --> 02:58:17,359
information from other places
5066
02:58:15,040 --> 02:58:20,399
and are able to continuously monitor
5067
02:58:17,359 --> 02:58:22,800
that over time so that if we have
5068
02:58:20,399 --> 02:58:24,880
an issue where a young person didn't
5069
02:58:22,800 --> 02:58:26,640
respond or skipped those questions that
5070
02:58:24,880 --> 02:58:28,160
we can catch them the next time and we
5071
02:58:26,640 --> 02:58:29,680
know whether they were screened or not
5072
02:58:28,160 --> 02:58:31,520
which has been extremely helpful as
5073
02:58:29,680 --> 02:58:32,960
we've implemented
5074
02:58:31,520 --> 02:58:35,120
expert
5075
02:58:32,960 --> 02:58:36,560
but we're also fortunate to be able to
5076
02:58:35,120 --> 02:58:38,720
continue to
5077
02:58:36,560 --> 02:58:39,920
validate the algorithm that we created
5078
02:58:38,720 --> 02:58:42,080
initially
5079
02:58:39,920 --> 02:58:43,920
so with our new knight of funding we're
5080
02:58:42,080 --> 02:58:46,479
going to be
5081
02:58:43,920 --> 02:58:48,240
pulling a broader set of notes
5082
02:58:46,479 --> 02:58:50,160
that allows us to look at both publicly
5083
02:58:48,240 --> 02:58:51,920
and privately insured young people who
5084
02:58:50,160 --> 02:58:54,080
are in urban and suburban pediatric
5085
02:58:51,920 --> 02:58:56,479
settings and begin to examine some of
5086
02:58:54,080 --> 02:58:59,520
the bias that others have raised earlier
5087
02:58:56,479 --> 02:59:01,040
today in thinking about what differences
5088
02:58:59,520 --> 02:59:02,960
we might have around screening and
5089
02:59:01,040 --> 02:59:05,040
documentation
5090
02:59:02,960 --> 02:59:06,720
for substance use based on gender race
5091
02:59:05,040 --> 02:59:08,080
and ethnicity insurance status and
5092
02:59:06,720 --> 02:59:09,680
counter sites
5093
02:59:08,080 --> 02:59:11,680
so what are people doing in different
5094
02:59:09,680 --> 02:59:14,000
settings and how important is that
5095
02:59:11,680 --> 02:59:15,600
one of our hypotheses that we'll be able
5096
02:59:14,000 --> 02:59:17,840
to test out in this grant is actually
5097
02:59:15,600 --> 02:59:19,200
that by capturing both screening
5098
02:59:17,840 --> 02:59:21,200
standardized
5099
02:59:19,200 --> 02:59:23,120
structured data and the unstandardized
5100
02:59:21,200 --> 02:59:25,040
screening results that we can
5101
02:59:23,120 --> 02:59:26,960
potentially provide a more comprehensive
5102
02:59:25,040 --> 02:59:29,359
view that's longitudinal and we can
5103
02:59:26,960 --> 02:59:31,200
reduce some of those biases because
5104
02:59:29,359 --> 02:59:33,600
young people that might have experienced
5105
02:59:31,200 --> 02:59:35,359
some targeted screening in one setting
5106
02:59:33,600 --> 02:59:36,880
may be captured in another setting of a
5107
02:59:35,359 --> 02:59:38,640
different encounter
5108
02:59:36,880 --> 02:59:40,640
where they are engaging in universal
5109
02:59:38,640 --> 02:59:42,399
screening and we can ensure a more
5110
02:59:40,640 --> 02:59:44,479
comprehensive coverage of young people
5111
02:59:42,399 --> 02:59:46,960
by that by using that information
5112
02:59:44,479 --> 02:59:48,560
longitudinally from multiple sites
5113
02:59:46,960 --> 02:59:49,600
so with that
5114
02:59:48,560 --> 02:59:51,760
um
5115
02:59:49,600 --> 02:59:53,279
i want to echo the the comments of
5116
02:59:51,760 --> 02:59:55,439
others that i think it's important for
5117
02:59:53,279 --> 02:59:57,040
us to be thinking about this both from a
5118
02:59:55,439 --> 02:59:58,800
clinical standpoint and why it's
5119
02:59:57,040 --> 03:00:01,359
important to know whether your patient
5120
02:59:58,800 --> 03:00:03,439
was screened at a previous encounter and
5121
03:00:01,359 --> 03:00:05,120
what that clinician reported or observed
5122
03:00:03,439 --> 03:00:06,960
about that screening
5123
03:00:05,120 --> 03:00:09,439
needs to be shared for clinical care
5124
03:00:06,960 --> 03:00:11,279
delivery as well as for um
5125
03:00:09,439 --> 03:00:12,880
for research purposes
5126
03:00:11,279 --> 03:00:14,880
so we need to be able to track and
5127
03:00:12,880 --> 03:00:16,560
monitor that over time but also because
5128
03:00:14,880 --> 03:00:18,319
we know that substance use is changing
5129
03:00:16,560 --> 03:00:19,840
with age
5130
03:00:18,319 --> 03:00:21,760
and that we're reliant on both the
5131
03:00:19,840 --> 03:00:24,080
health care system to properly document
5132
03:00:21,760 --> 03:00:26,640
and adolescence to accurately report so
5133
03:00:24,080 --> 03:00:28,240
we really likely do need to think about
5134
03:00:26,640 --> 03:00:29,279
integrating both the standardized
5135
03:00:28,240 --> 03:00:31,840
screening
5136
03:00:29,279 --> 03:00:33,760
and trained clinical follow-up that can
5137
03:00:31,840 --> 03:00:35,680
ensure that we're capturing
5138
03:00:33,760 --> 03:00:37,200
recanting or other issues that might be
5139
03:00:35,680 --> 03:00:38,800
happening that result resulted
5140
03:00:37,200 --> 03:00:40,800
discrepancies between structured and
5141
03:00:38,800 --> 03:00:44,960
unstructured data collection
5142
03:00:40,800 --> 03:00:45,760
so with that i am going to turn it over
5143
03:00:44,960 --> 03:00:49,600
um
5144
03:00:45,760 --> 03:00:49,600
go and stop sharing my screen
5145
03:00:50,640 --> 03:00:53,920
thank you sarah
5146
03:00:52,720 --> 03:00:55,840
there we go
5147
03:00:53,920 --> 03:00:57,279
great thank you so much that was great
5148
03:00:55,840 --> 03:00:59,840
um
5149
03:00:57,279 --> 03:01:02,000
and we just have a few few questions or
5150
03:00:59,840 --> 03:01:03,920
a few few minutes for questions um if
5151
03:01:02,000 --> 03:01:05,520
you have any additional questions please
5152
03:01:03,920 --> 03:01:08,160
go ahead and
5153
03:01:05,520 --> 03:01:10,240
pop them into the chat
5154
03:01:08,160 --> 03:01:12,560
but i wanted to pick up on
5155
03:01:10,240 --> 03:01:14,319
an issue that you just
5156
03:01:12,560 --> 03:01:16,240
were kind of um
5157
03:01:14,319 --> 03:01:18,399
you were discussing at the end sarah and
5158
03:01:16,240 --> 03:01:20,319
i think maybe um
5159
03:01:18,399 --> 03:01:21,120
amy and vinod that you probably have
5160
03:01:20,319 --> 03:01:23,680
some
5161
03:01:21,120 --> 03:01:26,240
um some nuggets for us as well thinking
5162
03:01:23,680 --> 03:01:27,920
about the these issues of sharing across
5163
03:01:26,240 --> 03:01:30,800
providers um
5164
03:01:27,920 --> 03:01:33,920
a lot of our earlier speakers are in
5165
03:01:30,800 --> 03:01:36,240
more closed systems where um kaiser or
5166
03:01:33,920 --> 03:01:38,640
the va where you know you can kind of
5167
03:01:36,240 --> 03:01:39,840
rely on the fact that um
5168
03:01:38,640 --> 03:01:41,200
different clinicians are going to be
5169
03:01:39,840 --> 03:01:43,200
able to see
5170
03:01:41,200 --> 03:01:44,720
the same ehr or at least going to be
5171
03:01:43,200 --> 03:01:46,399
able to see the same data even if they
5172
03:01:44,720 --> 03:01:48,880
have a little bit of a different view
5173
03:01:46,399 --> 03:01:50,240
within the hr um but
5174
03:01:48,880 --> 03:01:51,920
you know when we're when we're dealing
5175
03:01:50,240 --> 03:01:54,319
with sort of different patient
5176
03:01:51,920 --> 03:01:55,200
populations who may be seeing
5177
03:01:54,319 --> 03:01:57,600
um
5178
03:01:55,200 --> 03:02:00,640
seeing providers outside of um the
5179
03:01:57,600 --> 03:02:02,800
current system um you know are there any
5180
03:02:00,640 --> 03:02:05,040
lessons learned any any
5181
03:02:02,800 --> 03:02:06,800
tools that can be used that we can kind
5182
03:02:05,040 --> 03:02:07,600
of think about in making sure that we're
5183
03:02:06,800 --> 03:02:10,080
not
5184
03:02:07,600 --> 03:02:12,319
um sort of duplicating efforts and we're
5185
03:02:10,080 --> 03:02:14,960
streamlining data but also
5186
03:02:12,319 --> 03:02:17,200
obviously navigating a whole lot of
5187
03:02:14,960 --> 03:02:20,399
technological and privacy
5188
03:02:17,200 --> 03:02:21,840
um privacy concerns that that will will
5189
03:02:20,399 --> 03:02:23,760
naturally come up in those sort of
5190
03:02:21,840 --> 03:02:25,520
situations
5191
03:02:23,760 --> 03:02:27,439
i did kind of bring up one of those kind
5192
03:02:25,520 --> 03:02:29,200
of privacy concerns that hasn't come up
5193
03:02:27,439 --> 03:02:32,640
yet and that's just thinking about 42
5194
03:02:29,200 --> 03:02:34,560
cfr um and you know that different
5195
03:02:32,640 --> 03:02:37,040
institutions interpret that in different
5196
03:02:34,560 --> 03:02:38,640
ways and so um vanilla can speak to this
5197
03:02:37,040 --> 03:02:40,880
more thoughtfully but you know when we
5198
03:02:38,640 --> 03:02:42,560
have two substances disorder clinics as
5199
03:02:40,880 --> 03:02:44,960
part of our project as we're looking at
5200
03:02:42,560 --> 03:02:47,439
risk of developing an open use disorder
5201
03:02:44,960 --> 03:02:49,359
um and kind of overnight one day the
5202
03:02:47,439 --> 03:02:51,680
proms data from the substance use
5203
03:02:49,359 --> 03:02:53,520
disorder clinics disappeared um you know
5204
03:02:51,680 --> 03:02:55,040
and then knew that that data was there
5205
03:02:53,520 --> 03:02:56,720
and so new to kind of advocating kind of
5206
03:02:55,040 --> 03:02:59,279
ask for it to come back but you know
5207
03:02:56,720 --> 03:03:00,640
anything if it's a clinician you know if
5208
03:02:59,279 --> 03:03:01,840
researchers are partnering with
5209
03:03:00,640 --> 03:03:04,319
clinicians they're going to you know
5210
03:03:01,840 --> 03:03:06,479
pretty quickly pick up this issue but um
5211
03:03:04,319 --> 03:03:09,040
but it's an issue that me you know some
5212
03:03:06,479 --> 03:03:12,600
people may not be as aware of um it
5213
03:03:09,040 --> 03:03:12,600
exists so
5214
03:03:18,479 --> 03:03:23,520
all right and then another sort of along
5215
03:03:20,960 --> 03:03:25,439
those same same lines um this was a
5216
03:03:23,520 --> 03:03:26,640
question that came into the chat
5217
03:03:25,439 --> 03:03:28,399
from
5218
03:03:26,640 --> 03:03:30,560
one of our colleagues but how can we set
5219
03:03:28,399 --> 03:03:32,479
up tools or support
5220
03:03:30,560 --> 03:03:35,520
to help providers reflect and choose the
5221
03:03:32,479 --> 03:03:37,359
appropriate course and avoid automation
5222
03:03:35,520 --> 03:03:40,319
bias that can lead to
5223
03:03:37,359 --> 03:03:41,600
draconian response or bias care um and i
5224
03:03:40,319 --> 03:03:43,680
think i you know you think about this a
5225
03:03:41,600 --> 03:03:46,319
lot um you know we haven't quite said
5226
03:03:43,680 --> 03:03:47,600
you know there is a stigma related you
5227
03:03:46,319 --> 03:03:51,120
know both
5228
03:03:47,600 --> 03:03:53,200
by patients and clinicians related to um
5229
03:03:51,120 --> 03:03:56,000
related to substance use
5230
03:03:53,200 --> 03:03:58,640
also related to
5231
03:03:56,000 --> 03:03:59,600
foster care also related to mental
5232
03:03:58,640 --> 03:04:01,279
health
5233
03:03:59,600 --> 03:04:02,800
so there's there's a lot kind of that
5234
03:04:01,279 --> 03:04:04,399
we're navigating
5235
03:04:02,800 --> 03:04:07,520
but any thoughts on that of how we can
5236
03:04:04,399 --> 03:04:09,680
kind of safeguard or at least put some
5237
03:04:07,520 --> 03:04:12,560
put some safeguards in place to try to
5238
03:04:09,680 --> 03:04:12,560
minimize bias
5239
03:04:12,800 --> 03:04:15,840
um so
5240
03:04:14,000 --> 03:04:19,840
at least one strategy that we're using
5241
03:04:15,840 --> 03:04:21,680
within cincinnati children's so far
5242
03:04:19,840 --> 03:04:23,520
is that
5243
03:04:21,680 --> 03:04:26,319
we're trying to highlight that if it's
5244
03:04:23,520 --> 03:04:28,560
universal that that reduces stigma right
5245
03:04:26,319 --> 03:04:30,960
so if everybody is screened
5246
03:04:28,560 --> 03:04:32,479
um and we screen all the time
5247
03:04:30,960 --> 03:04:34,479
um then it's
5248
03:04:32,479 --> 03:04:38,240
it becomes a little bit easier to be
5249
03:04:34,479 --> 03:04:40,479
able to um advocate and and frame the
5250
03:04:38,240 --> 03:04:43,120
questions that we're asking everyone and
5251
03:04:40,479 --> 03:04:44,880
so it's it's not as biasing
5252
03:04:43,120 --> 03:04:47,680
the second thing is
5253
03:04:44,880 --> 03:04:49,439
for us to highlight that substance use
5254
03:04:47,680 --> 03:04:51,200
is somewhat normative in adolescence and
5255
03:04:49,439 --> 03:04:53,359
we know what's going to happen
5256
03:04:51,200 --> 03:04:55,200
but that we really want to set up and
5257
03:04:53,359 --> 03:04:57,040
partner with youth and families to
5258
03:04:55,200 --> 03:05:00,560
ensure that there are safeguards so that
5259
03:04:57,040 --> 03:05:02,080
they are are not moving from
5260
03:05:00,560 --> 03:05:04,800
experimental substance use to
5261
03:05:02,080 --> 03:05:06,640
problematic substance use and how we can
5262
03:05:04,800 --> 03:05:09,120
frame that in such a way that young
5263
03:05:06,640 --> 03:05:10,319
people feel comfortable disclosing their
5264
03:05:09,120 --> 03:05:12,399
use
5265
03:05:10,319 --> 03:05:14,160
and trusting providers and then the last
5266
03:05:12,399 --> 03:05:15,040
thing is that
5267
03:05:14,160 --> 03:05:16,800
i think
5268
03:05:15,040 --> 03:05:18,640
it's also important to train healthcare
5269
03:05:16,800 --> 03:05:20,240
providers to be aware that there are
5270
03:05:18,640 --> 03:05:22,560
some biases
5271
03:05:20,240 --> 03:05:24,800
even in the way that we ask and talk
5272
03:05:22,560 --> 03:05:26,640
with young people around
5273
03:05:24,800 --> 03:05:28,880
substance use and screen for that and
5274
03:05:26,640 --> 03:05:30,800
that we have to be prepared
5275
03:05:28,880 --> 03:05:33,040
to respond to it so
5276
03:05:30,800 --> 03:05:33,920
so that we're not just looking at a
5277
03:05:33,040 --> 03:05:35,840
score
5278
03:05:33,920 --> 03:05:38,000
um and a great example of that is that
5279
03:05:35,840 --> 03:05:40,000
we have a
5280
03:05:38,000 --> 03:05:42,080
non-ignorable number of young people on
5281
03:05:40,000 --> 03:05:43,359
the craft who are reporting that they
5282
03:05:42,080 --> 03:05:45,120
have been in the vehicle with an
5283
03:05:43,359 --> 03:05:47,520
intoxicated driver
5284
03:05:45,120 --> 03:05:49,600
and it's not the same risk that we think
5285
03:05:47,520 --> 03:05:51,600
of when we when that that question was
5286
03:05:49,600 --> 03:05:53,840
initially described around peers right
5287
03:05:51,600 --> 03:05:56,399
but it's actually a caregiver
5288
03:05:53,840 --> 03:05:58,080
um and so explaining to a clinician that
5289
03:05:56,399 --> 03:06:00,160
they need to have a conversation around
5290
03:05:58,080 --> 03:06:01,760
how to safely
5291
03:06:00,160 --> 03:06:03,439
navigate that when it's your parent
5292
03:06:01,760 --> 03:06:04,880
who's intoxicated is an important
5293
03:06:03,439 --> 03:06:06,720
conversation that's about child
5294
03:06:04,880 --> 03:06:08,479
protection and not about bias towards
5295
03:06:06,720 --> 03:06:09,520
that child they're spending their time
5296
03:06:08,479 --> 03:06:12,080
with
5297
03:06:09,520 --> 03:06:13,520
um and so so that all of those things
5298
03:06:12,080 --> 03:06:15,920
helping to contextualize that i think
5299
03:06:13,520 --> 03:06:19,120
motivates discussion with providers
5300
03:06:15,920 --> 03:06:19,120
that's less judgmental
5301
03:06:20,160 --> 03:06:24,640
all right so my final question um
5302
03:06:22,880 --> 03:06:27,279
is is
5303
03:06:24,640 --> 03:06:29,520
advice for us so um
5304
03:06:27,279 --> 03:06:32,560
as nida if we're thinking about how we
5305
03:06:29,520 --> 03:06:35,520
can support
5306
03:06:32,560 --> 03:06:36,960
support prevention research using ehrs
5307
03:06:35,520 --> 03:06:39,120
if we can if we're thinking about how we
5308
03:06:36,960 --> 03:06:41,120
can support
5309
03:06:39,120 --> 03:06:43,279
prevention
5310
03:06:41,120 --> 03:06:45,680
within primary care and especially
5311
03:06:43,279 --> 03:06:47,279
implementation research to promote the
5312
03:06:45,680 --> 03:06:49,200
you know the implementation of of
5313
03:06:47,279 --> 03:06:50,960
intervention screening or you know
5314
03:06:49,200 --> 03:06:52,720
interventions that we know work
5315
03:06:50,960 --> 03:06:54,479
um how
5316
03:06:52,720 --> 03:06:55,600
what are do you have any advice for us
5317
03:06:54,479 --> 03:06:57,520
and this is probably a question we
5318
03:06:55,600 --> 03:06:59,680
should have asked everybody uh but
5319
03:06:57,520 --> 03:07:00,479
others can kind of chime in too if they
5320
03:06:59,680 --> 03:07:02,560
um
5321
03:07:00,479 --> 03:07:04,319
if they still have energy but you know
5322
03:07:02,560 --> 03:07:05,760
do you have advice for us for thinking
5323
03:07:04,319 --> 03:07:08,479
through like what we should be
5324
03:07:05,760 --> 03:07:10,080
prioritizing and how we can kind of
5325
03:07:08,479 --> 03:07:12,160
you know ensure that we're asking the
5326
03:07:10,080 --> 03:07:13,680
right questions and that we're um we're
5327
03:07:12,160 --> 03:07:15,279
not also not duplicating efforts and
5328
03:07:13,680 --> 03:07:17,200
that we're we're also supporting you
5329
03:07:15,279 --> 03:07:19,200
know sarah you mentioned that you talked
5330
03:07:17,200 --> 03:07:21,520
to um stacy
5331
03:07:19,200 --> 03:07:24,880
um which is wonderful um but that we're
5332
03:07:21,520 --> 03:07:26,720
kind of helping to support um to support
5333
03:07:24,880 --> 03:07:28,880
each other and kind of asking the right
5334
03:07:26,720 --> 03:07:31,040
questions avoiding duplication and
5335
03:07:28,880 --> 03:07:33,920
getting to answers more quickly do you
5336
03:07:31,040 --> 03:07:33,920
have any advice for us
5337
03:07:36,000 --> 03:07:39,760
great question i mean i will say that
5338
03:07:37,840 --> 03:07:41,279
this has been a really helpful workshop
5339
03:07:39,760 --> 03:07:43,120
um you know that i think kind of we're
5340
03:07:41,279 --> 03:07:44,640
all have been eagerly listening to the
5341
03:07:43,120 --> 03:07:46,880
different talks and so having
5342
03:07:44,640 --> 03:07:48,880
opportunities to to get people together
5343
03:07:46,880 --> 03:07:49,840
to talk about oh screening adolescence
5344
03:07:48,880 --> 03:07:52,000
via
5345
03:07:49,840 --> 03:07:53,840
you know kind of telehealth um you know
5346
03:07:52,000 --> 03:07:55,200
i think he brian mentioned kind of oh
5347
03:07:53,840 --> 03:07:57,439
you just set up the proxies but like
5348
03:07:55,200 --> 03:07:59,600
that's actually a talk in and of itself
5349
03:07:57,439 --> 03:08:00,720
is how you set up proxies and
5350
03:07:59,600 --> 03:08:02,160
then i think also learning from
5351
03:08:00,720 --> 03:08:04,479
different systems we have children's
5352
03:08:02,160 --> 03:08:06,319
hospitals and then hospital systems that
5353
03:08:04,479 --> 03:08:09,279
treat adults and children and so that
5354
03:08:06,319 --> 03:08:11,359
there's lessons to be learned um there
5355
03:08:09,279 --> 03:08:13,439
as well so so thank you for the
5356
03:08:11,359 --> 03:08:15,279
opportunity to have us all together and
5357
03:08:13,439 --> 03:08:16,800
and to hear all the information that was
5358
03:08:15,279 --> 03:08:20,120
presented today
5359
03:08:16,800 --> 03:08:20,120
my only thoughts
5360
03:08:21,680 --> 03:08:27,359
all right well on that note um we i'm
5361
03:08:24,399 --> 03:08:29,120
going to turn it over to carlos um
5362
03:08:27,359 --> 03:08:31,840
blanco to
5363
03:08:29,120 --> 03:08:34,000
finish us off and close us off um before
5364
03:08:31,840 --> 03:08:35,680
i turn it over to carlos i want to let
5365
03:08:34,000 --> 03:08:38,640
everybody know that we did record this
5366
03:08:35,680 --> 03:08:40,960
and we'll be putting it online
5367
03:08:38,640 --> 03:08:42,399
and we also will be putting together a
5368
03:08:40,960 --> 03:08:45,040
summary
5369
03:08:42,399 --> 03:08:47,279
of the of the discussion so
5370
03:08:45,040 --> 03:08:49,840
a lot of the issues that have come up
5371
03:08:47,279 --> 03:08:51,040
today we'll be able to document and put
5372
03:08:49,840 --> 03:08:54,880
online
5373
03:08:51,040 --> 03:08:57,600
um if you'd like copies of uh of the
5374
03:08:54,880 --> 03:08:59,840
the slides you can reach out to
5375
03:08:57,600 --> 03:09:01,920
um i believe caitlyn um and caitlin i
5376
03:08:59,840 --> 03:09:04,479
don't know if you can put in the chat um
5377
03:09:01,920 --> 03:09:06,000
your email again i know you it was up up
5378
03:09:04,479 --> 03:09:08,319
a ways in the chat
5379
03:09:06,000 --> 03:09:11,120
um but we can provide those um or at
5380
03:09:08,319 --> 03:09:13,840
least most of them that have released um
5381
03:09:11,120 --> 03:09:15,920
to you all and i just want to thank the
5382
03:09:13,840 --> 03:09:17,680
um i know carlos will do this but i
5383
03:09:15,920 --> 03:09:19,760
really want to thank
5384
03:09:17,680 --> 03:09:21,439
the speakers who um
5385
03:09:19,760 --> 03:09:23,279
took time out of their
5386
03:09:21,439 --> 03:09:25,439
their week to
5387
03:09:23,279 --> 03:09:26,319
prepare and you know time today to
5388
03:09:25,439 --> 03:09:27,439
present
5389
03:09:26,319 --> 03:09:29,680
and discuss
5390
03:09:27,439 --> 03:09:31,120
their research and um their expertise
5391
03:09:29,680 --> 03:09:33,120
with us
5392
03:09:31,120 --> 03:09:34,319
carlos are you there
5393
03:09:33,120 --> 03:09:35,359
i'm here
5394
03:09:34,319 --> 03:09:37,120
yes
5395
03:09:35,359 --> 03:09:39,600
no thanks sarah i mean this was a
5396
03:09:37,120 --> 03:09:41,359
wonderful workshop as i think we all
5397
03:09:39,600 --> 03:09:43,439
expected so i want to
5398
03:09:41,359 --> 03:09:45,359
to thank everybody for participating for
5399
03:09:43,439 --> 03:09:48,000
the questions and for sharing your your
5400
03:09:45,359 --> 03:09:49,760
knowledge and and that was no questions
5401
03:09:48,000 --> 03:09:51,279
and we'll have to we'll have to chew on
5402
03:09:49,760 --> 03:09:53,359
it and see
5403
03:09:51,279 --> 03:09:56,000
where we go but certainly you have a lot
5404
03:09:53,359 --> 03:09:57,680
of you have given us a lot to think to
5405
03:09:56,000 --> 03:09:58,479
think about so thanks as sarah was
5406
03:09:57,680 --> 03:10:00,479
saying
5407
03:09:58,479 --> 03:10:03,120
to all the speakers and everybody who
5408
03:10:00,479 --> 03:10:05,040
has attended the workshop and also to
5409
03:10:03,120 --> 03:10:07,279
the contractors for setting up
5410
03:10:05,040 --> 03:10:08,880
everything so that everything went um
5411
03:10:07,279 --> 03:10:11,520
went very smoothly
5412
03:10:08,880 --> 03:10:14,640
so sarah i'll send it back to you for
5413
03:10:11,520 --> 03:10:16,319
for you to close the workshop
5414
03:10:14,640 --> 03:10:18,160
all right thank you
5415
03:10:16,319 --> 03:10:22,080
um i don't think there is anything else
5416
03:10:18,160 --> 03:10:23,680
from us so um thank you so much for
5417
03:10:22,080 --> 03:10:24,880
for joining us everyone who's been on
5418
03:10:23,680 --> 03:10:26,880
the line
5419
03:10:24,880 --> 03:10:29,279
thanks for your engagement
5420
03:10:26,880 --> 03:10:31,840
and your interest and
5421
03:10:29,279 --> 03:10:33,120
look out for some additional information
5422
03:10:31,840 --> 03:10:35,040
as our
5423
03:10:33,120 --> 03:10:35,760
as our summary and our recording come
5424
03:10:35,040 --> 03:10:39,040
out
5425
03:10:35,760 --> 03:10:40,880
and please be in touch with any
5426
03:10:39,040 --> 03:10:45,160
any thoughts or comments that you'd like
5427
03:10:40,880 --> 03:10:45,160
to provide to us thank you