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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Image

Innovative Data Science
Approaches to Identify
Individuals, Populations,
and Communities at High
Risk for Suicide

_____

Francis K. Amankwah, Robert Pool, and
Sharyl J. Nass, Rapporteurs

Forum on Mental Health and Substance
Use Disorders

Board on Health Care Services

Health and Medicine Division

Proceedings of a Workshop

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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THE NATIONAL ACADEMIES PRESS 500 Fifth Street, NW Washington, DC 20001

This activity was funded by the Office of the Assistant Secretary for Health [Contract No. HHSP233201400020B (Task Order No. 75P00121F37111)], with support from the Centers for Disease Control and Prevention and the National Institutes of Health. Any opinions, findings, conclusions, or recommendations expressed in this publication do not necessarily reflect the views of any organization or agency that provided support for the project.

International Standard Book Number-13: 978-0-309-69506-0
International Standard Book Number-10: 0-309-69506-6
Digital Object Identifier: https://doi.org/10.17226/26752

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Suggested citation: National Academies of Sciences, Engineering, and Medicine. 2022. Innovative data science approaches to identify individuals, populations, and communities at high risk for suicide. Washington, DC: The National Academies Press. https://doi.org/10.17226/26752.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

The National Academy of Sciences was established in 1863 by an Act of Congress, signed by President Lincoln, as a private, nongovernmental institution to advise the nation on issues related to science and technology. Members are elected by their peers for outstanding contributions to research. Dr. Marcia McNutt is president.

The National Academy of Engineering was established in 1964 under the charter of the National Academy of Sciences to bring the practices of engineering to advising the nation. Members are elected by their peers for extraordinary contributions to engineering. Dr. John L. Anderson is president.

The National Academy of Medicine (formerly the Institute of Medicine) was established in 1970 under the charter of the National Academy of Sciences to advise the nation on medical and health issues. Members are elected by their peers for distinguished contributions to medicine and health. Dr. Victor J. Dzau is president.

The three Academies work together as the National Academies of Sciences, Engineering, and Medicine to provide independent, objective analysis and advice to the nation and conduct other activities to solve complex problems and inform public policy decisions. The National Academies also encourage education and research, recognize outstanding contributions to knowledge, and increase public understanding in matters of science, engineering, and medicine.

Learn more about the National Academies of Sciences, Engineering, and Medicine at www.nationalacademies.org.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

Consensus Study Reports published by the National Academies of Sciences, Engineering, and Medicine document the evidence-based consensus on the study’s statement of task by an authoring committee of experts. Reports typically include findings, conclusions, and recommendations based on information gathered by the committee and the committee’s deliberations. Each report has been subjected to a rigorous and independent peer-review process and it represents the position of the National Academies on the statement of task.

Proceedings published by the National Academies of Sciences, Engineering, and Medicine chronicle the presentations and discussions at a workshop, symposium, or other event convened by the National Academies. The statements and opinions contained in proceedings are those of the participants and are not endorsed by other participants, the planning committee, or the National Academies.

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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

WORKSHOP PLANNING COMMITTEE1

BENJAMIN MILLER (Co-Chair), President, Well Being Trust

SEAN JOE (Co-Chair), Benjamin E. Youngdahl Professor of Social Development; Fellow, American Academy of Social Welfare and Social Work; Principal Director, Race and Opportunity Lab, George Warren Brown School of Social Work, Washington University in Saint Louis

PATRICIA AREÁN, Professor, Psychiatry and Behavioral Sciences; Co-Director, UW/NIMH ALACRITY Center; Director, UW CREATIV Lab, University of Washington

COLLEEN CARR, Director, National Action Alliance for Suicide Prevention, Education Development Center

GLEN COPPERSMITH, Chief Data Officer, SonderMind; Advisory Board Member and Adjunct Research Scientist, Johns Hopkins University Human Language Technology Center of Excellence; Adjunct Staff, Institute for Defense Analyses

JOHN MCCARTHY, Office of Mental Health and Suicide Prevention, Department of Veterans Affairs; Director, Data and Surveillance, Suicide Prevention Program; Director, Serious Mental Illness Treatment Resource and Evaluation Center; Research Associate Professor, Department of Psychiatry, University of Michigan

GREGORY SIMON, Investigator, Kaiser Permanente Washington Health Research Institute

AYAH ZIRIKLY, Assistant Research Scientist, Center for Language and Speech Processing, Johns Hopkins University

Project Staff

FRANCIS AMANKWAH, Program Officer (starting May 2022)

ADRIENNE FORMENTOS, Research Associate

ANESIA WILKS, Senior Program Assistant

ARZOO TAYYEB, Finance Business Partner

___________________

1 The National Academies of Sciences, Engineering, and Medicine’s planning committees are solely responsible for organizing the workshop, identifying topics, and choosing speakers. The responsibility for the published Proceedings of a Workshop rests with the workshop rapporteurs and the institution.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

ALEXANDRA ANDRADA, Director, Forum on Mental Health and Substance Use Disorders

SHARYL NASS, Senior Director, Board on Health Care Services

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

FORUM ON MENTAL HEALTH AND SUBSTANCE USE DISORDERS1

MARGARITA ALEGRÍA (Co-Chair), Harvard Medical School

HOWARD H. GOLDMAN (Co-Chair), University of Maryland School of Medicine

ERIN BAGALMAN, Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services

CARLOS BLANCO, National Institute on Drug Abuse, National Institutes of Health

CHRIS M. CROWE, U.S. Department of Veterans Affairs

W. PERRY DICKINSON, University of Colorado

ANTHONY T. ESTREET, Morgan State University

SYLVIA K. FISHER, Health Resources and Services Administration

RICHARD G. FRANK, Harvard Medical School

ROBERT HEINSSEN, National Institute of Mental Health

KRISTIN KROEGER, American Psychiatric Association

LAUREN B. LOWENSTEIN, Centers for Medicare & Medicaid Services

HUSSEINI K. MANJII, Janssen Research & Development, LLC

R. KATHRYN MCHUGH, Harvard Medical School

BEN MILLER, Well Being Trust

ANNIE PETERS, National Association of Addiction Treatment Providers

KATHY PHAM, American College of Clinical Pharmacy

JOE PYLE, Scattergood Foundation

DEIDRA ROACH, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health

MARY ROACH, Substance Abuse and Mental Health Services Administration

GLORINDA SEGAY, Indian Health Service

RUTH SHIM, University of California, Davis

MATTHEW TIERNEY, University of California, San Francisco, School of Nursing and Office of Population Health

___________________

1 The National Academies of Sciences, Engineering, and Medicine’s forums and roundtables do not issue, review, or approve individual documents. The responsibility for the published Proceedings of a Workshop rests with the workshop rapporteurs and the institution.

Page viii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

Reviewers

This Proceedings of Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: A Workshop was reviewed in draft form by individuals chosen for their diverse perspectives and technical expertise. The purpose of this independent review is to provide candid and critical comments that will assist the National Academies of Sciences, Engineering, and Medicine in making each published proceedings as sound as possible and to ensure that it meets the institutional standards for quality, objectivity, evidence, and responsiveness to the charge. The review comments and draft manuscript remain confidential to protect the integrity of the process.

We thank the following individuals for their review of this proceedings:

MASON MARKS, Florida State University College of Law; Harvard Law School Petrie Flom Center

KENTON WHITE, Advanced Symbolics Inc.

HOLLY WILCOX, Johns Hopkins School of Public Health

Although the reviewers listed above provided many constructive comments and suggestions, they were not asked to endorse the content of the proceedings nor did they see the final draft before its release. The review of this proceedings was overseen by JOHN ZAVEN AYANIAN, Institute for Healthcare Policy and Innovation, University of Michigan. He was responsible for making certain that an independent examination of this proceedings was carried out in accordance with standards of the National Academies and that

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

all review comments were carefully considered. Responsibility for the final content rests entirely with the rapporteurs and the National Academies.

We also thank staff member Daniel Talmage for reading and providing helpful comments on this manuscript.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×

Acknowledgments

The Forum on Mental Health and Substance Use Disorders wishes to express its gratitude to the expert speakers whose presentations and discussions helped inform efforts to advance innovative data science techniques to help inform upstream suicide prevention efforts at the individual, community, and population levels. The Forum also wishes to thank the members of the planning committee who collaborated to ensure a workshop with informative presentations and rich discussions.

The Forum is grateful for the support of the Office of the Assistant Secretary for Health, the Centers for Disease Control and Prevention, and the National Institutes of Health, for this workshop.

The Forum is sponsored by the American College of Clinical Pharmacy, American Psychiatric Nurses Association, American Psychological Association, Association for Behavioral Health and Wellness, Council on Social Work Education, Janssen Research & Development, National Academy of Medicine, National Institute on Alcohol Abuse and Alcoholism, National Institute on Drug Abuse, National Institute of Mental Health, Office of the Assistant Secretary for Planning and Evaluation, Optum Behavioral Health, Think Bigger Do Good Policy Series (a partnership of the Scattergood Foundation, Peg’s Foundation, Patrick P. Lee Foundation, and Peter and Elizabeth Tower Foundation), U.S. Department of Veterans Affairs, and Well Being Trust.

Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Page xvii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Acronyms and Abbreviations

AI artificial intelligence
CDC Centers for Disease Control and Prevention
CMS Centers for Medicare & Medicaid Services
DBT dialectical behavioral therapy
DoD U.S. Department of Defense
ELSI ethical, legal, and social implications
EMS emergency medical services
ESSENCE Electronic Surveillance System for the Early Notification of Community-Based Epidemics
HIPAA Health Insurance Portability and Accountability Act
HHS U.S. Department of Health and Human Services
ICD International Classification of Diseases
JITAI just-in-time adaptive interventions
LGBTQ lesbian, gay, bisexual, transgender, queer
MHA Mental Health America
MHS Military Health System
Page xviii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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ML machine learning
MUM Multitask Unified Model
PHQ Patient Health Questionnaire
REACH VET Recovery Engagement and Coordination for Health—Veterans Enhanced Treatment
SAMHSA Substance Abuse and Mental Health Services Administration
TNSPN Tennessee Suicide Prevention Network
VA U.S. Department of Veterans Affairs
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
×
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Page viii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Page xiii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Page xvii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Page xviii Cite
Suggested Citation:"Front Matter." National Academies of Sciences, Engineering, and Medicine. 2022. Innovative Data Science Approaches to Identify Individuals, Populations, and Communities at High Risk for Suicide: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/26752.
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Emerging real-time data sources, together with innovative data science techniques and methods - including artificial intelligence and machine learning - can help inform upstream suicide prevention efforts. Select social media platforms have proactively deployed these methods to identify individual platform users at high risk for suicide, and in some cases may activate local law enforcement, if needed, to prevent imminent suicide. To explore the current scope of activities, benefits, and risks of leveraging innovative data science techniques to help inform upstream suicide prevention at the individual and population level, the Forum on Mental Health and Substance Use Disorders of the National Academies of Sciences, Engineering, and Medicine convened a virtual workshop series consisting of three webinars held on April 28, May 12, and June 30, 2022. This Proceedings highlights presentations and discussions from the workshop.

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