Big Data and Next Generation Mental Health@ U.S. Congress: @ U.S. Congress: 18 September, 18 September,

20152015

Disclaimers: This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA), and Space Warfare Systems Center Pacific under Contract N66001-11-4006. Also supported by, the Intelligence Advanced Research Projects Activity (IARPA) via the Department of Interior National Business Center contract number N10PC20221. The opinions, findings and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the Defense Advanced Research Projects Agency (DARPA) and Space, the Naval Warfare Systems Center Pacific, or the IARPA, DOI/NBC, or the U.S. Government.

© 2013-2015 Patterns and Predictions

Chris PoulinChris PoulinPrincipal PartnerPrincipal Partner

The Problem

Mental Health issues often go undiagnosed, sometimes leading to;

Suicide (Self Harm) •As many as 22 Veterans per day•With 80% of Suicidal Veterans are not in VA care•And while The Clay Hunt act provides more VA oversight & operational reform…not innovative action

Mass Shootings (Harm of others)•Often problems are detected•But the proper response is lacking•Action could be taken Before problems arise

Insider Threat (Theft of property)•With National Security implications•Multi-type: e.g. Germanwings Slide 2

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Medical Context for Suicide

• The project was named in honor of Emile Durkheim, a founding sociologist whose 1897 publication of Suicide defined early language analysis for suicide explanations.

• Our team was comprised of a multidisciplinary team of artificial intelligence, & medical experts (Dartmouth & VA)

• Funded by DARPA from mid 2011- early 2013• Based on mathematics funded prior by IARPA • Delivered a data-powered mental health

screening system

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The Durkheim Project

The math is like that of Moneyball (Lewis), where instead of statistics on your players, your looking at statistics on your consenting users. Big Data + Analytics provides a;•Greater risk assessment (over time) for individuals•Greater number of individuals that can be reached (e.g. rural communities)•Cost Reductions. As we can;

• Reach over 100,000 veterans with CURRENT systems

• Cut health care costs by isolating those at TRULY risk

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Predictive Health Care

Slide 9

• Red terms are from Suicide Positive Cohort

• Yellow terms are from Psychiatric/Non-Suicidal Control

• Green terms are from Control Group

Example Features

• We developed linguistics-driven prediction models to estimate the risk of suicide.

• These models were generated from unstructured clinical notes

• From the clinical notes, we generated datasets of single keywords and multi-word phrases

• We were able to initially predict suicide with 65%* accuracy on a small dataset.

• * We have since reached 70%

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Machine Learning (with VA)

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Results

Dashboard• Provides real-time monitoring of patients by Clinical Professionals• Also enables a buddy-system• (Live at Dartmouth Hitchcock Medical Center)

Comparative Risk Monitoring• By Cohort• Daily Tracking (think Fitbit™ for mental health)

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Dashboard Solution (for DARPA)

• Simplified user participation for consent, and privacy control

• Consent based access to online resources:

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Opt-In Interface

• The Data is Secure/Protected• Specifically, the data persists at a medical center, behind a HIPAA

compliant firewall (e.g. Dartmouth Hitchcock Medical Center below)

• The highest professional security standards

Slide 13

Storage Layer

On July 2013, in conjunction with Facebook, Inc., we publically launched our project, with the aim of raising awareness, as well as direct recruiting of subjects. https://www.facebook.com/notes/us-military-on-facebook/durkheim-project-launch/472400246179609

… And since, we have been positively covered by NPR, NBC.com, Time.com, Fast Company, The Boston Globe, Daily Mail UK, Mashable, CIO, and CNN.com

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Facebook Partnership

InterventionAutomated systems are coming online for potential patients and families seeking treatment, as well as passive intervention strategies (i.e. ‘safety plan’narratives).

Interventions that are designed to be timely and appropriate

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Slide 17

Interventions Sequence

Germanwings Flight 9525

"Germanwings co-pilot Andreas Lubitz saw 41 doctors in five years;..." -ABC

"Germanwings Co-Pilot Andreas Lubitz Was Treated for Suicidal Tendencies" -WSJ

"Andreas Lubitz repeatedly set the same plane for an unauthorised descent earlier that day." -BBC

"He told former girlfriend he was planning an act so horrifying his name would be remembered forever." -Dailymail.co.uk

Should pilots be tested?Slide 4

Insider Threat: The Murder-Suicide Scenario

Why isn’t DARPA funding this further?The perception is that now that the science of the detection problem is proven, the next steps are 'too medical' for their agency mandate

Why isn’t NIH funding this?Heavy clinical/incremental medical studies focus & lack of dedicated technology funding for NIMH

Why isn’t VA funding this?The VA has scattered /uncoordinated attempts at similar. But the VA has a core outreach problem (well known statistics). And leading VA researchers are not (yet) taking Big Data approach

Why not Homeland Security?Pilot studies (of similar, not same technology) have been conducted. However, core policing engagement with suspects remains unchanged

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Q&A

Suicide Risk:An opt-in risk assessment and intervention routing system ALREADY exists. We just need to deploy this at scale, through the responsible interface with medical practitioners and social workers.

Mass Shootings:Public surveillance and risk prediction, that ALSO protects personal rights IS possible through proper training. One that enables law enforcement and community preservation, where citizens are innocent before proven guilty.

Insider Threat: Agencies can incorporate motive models into their behavioral characterizations, rather than be blindsided.

Funding:No government agency has an existing mandate to rise to the challenge.

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Takeaways

Fund Appropriations for comprehensive technology initiatives utilizing big data to detect mental health risks

• Research Programs• Pilot Projects

Fund training programs for professionals that can use technology for proper intervention, such as;

• Medical Staff • Police and Firefighters• Veterans and Social Workers

Public Awareness• Spotlight on mental health/suicide prevention• Congressional Hearings• Community involvement in District

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How Congress Can Help

Thank you

Chris PoulinChris PoulinPatterns and PredictionsPatterns and Predictions

+1 617.755.9049+1 617.755.9049

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• Opt-In is critical• Technical Problem: How to build a system that collects, stores,

analyzes, and allows clinicians to react at Internet scale?Phase 1:

• Machine Learning (Basic)• Scalable Machine Learning Phase 2:

• Opt-In Interface Layer• Data Collection Layer• Storage LayerPhase 3:

• Automated Intervention

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Appendix: Our Technology Approach