R01MH129433
Project Grant
Overview
Grant Description
Predicting firearm suicide in military veterans outside the VA health system using linked civilian electronic health record data - Abstract.
The ongoing epidemic of suicide among former U.S. military personnel—17 deaths every day—lies at the core of a 20-year trend of increasing suicide rates in the U.S. The rate of suicide in veterans is about 1.5 times that of the civilian population, due to veterans' unique burden of medical, psychological, and social-environmental risk factors compounded by easy access to lethal means.
To date, veteran suicide research and prevention efforts have focused almost entirely on the population served by the Veterans Health Administration (VHA). Meanwhile, most veterans do not seek VHA care but prefer private-sector health services. Since 2005, suicides among veterans outside the reach of VHA have increased at more than double the rate seen among VHA users (57% vs. 28%, respectively).
This study's primary objective is to develop efficient longitudinal predictive algorithms for suicide and firearm-related suicide among military veterans who utilized non-VHA health care, by analyzing the largest database ever assembled of linked civilian medical record data pertinent to veteran suicide risk.
Too little is known about veterans receiving care outside the VHA, including the nature and severity of their health conditions, their patterns of healthcare utilization, and their unique risk factors for all suicide and firearm-related suicide. Filling these gaps in knowledge is crucial to the goal of meaningfully reducing suicide in the veteran population overall.
To that end, our multi-disciplinary team of nationally distinguished researchers will assemble and analyze an unprecedented longitudinal database of linked VA and Department of Defense data, health records, social indicators, and death records of veterans receiving health care from 5 large civilian health systems in North Carolina and Utah. The database will yield an estimated 3.8 million person-year observations, including approximately 900 firearm-involved suicides and 1,190 total suicide deaths.
We will analyze these data to describe the demographic and health characteristics of veterans who utilize non-VHA healthcare services, their patterns of healthcare utilization, their mortality outcomes, and their incidence of suicide deaths, by method. We will use machine learning methods to develop specific risk algorithms for predicting all suicides and firearm-related suicides among veterans who utilize non-VHA healthcare, to identify veterans at elevated risk of suicide.
Utah-based collaborators will use linked VHA data to identify and describe risk patterns for veterans who combine VHA and non-VHA healthcare. Finally, we will conduct a series of key informant interviews to better understand barriers and facilitators to integrating this type of algorithm into civilian health system workflows.
In summary, the proposed work will fill critical gaps in the literature by leveraging large-scale, real-world data sources to yield novel knowledge of suicide risks, while informing prevention efforts aimed at reducing veteran suicide. We will also gather implementation information to inform how large civilian health systems will be able to use this information to identify and intervene with the veterans who are at greatest risk of suicide within their patient populations.
The ongoing epidemic of suicide among former U.S. military personnel—17 deaths every day—lies at the core of a 20-year trend of increasing suicide rates in the U.S. The rate of suicide in veterans is about 1.5 times that of the civilian population, due to veterans' unique burden of medical, psychological, and social-environmental risk factors compounded by easy access to lethal means.
To date, veteran suicide research and prevention efforts have focused almost entirely on the population served by the Veterans Health Administration (VHA). Meanwhile, most veterans do not seek VHA care but prefer private-sector health services. Since 2005, suicides among veterans outside the reach of VHA have increased at more than double the rate seen among VHA users (57% vs. 28%, respectively).
This study's primary objective is to develop efficient longitudinal predictive algorithms for suicide and firearm-related suicide among military veterans who utilized non-VHA health care, by analyzing the largest database ever assembled of linked civilian medical record data pertinent to veteran suicide risk.
Too little is known about veterans receiving care outside the VHA, including the nature and severity of their health conditions, their patterns of healthcare utilization, and their unique risk factors for all suicide and firearm-related suicide. Filling these gaps in knowledge is crucial to the goal of meaningfully reducing suicide in the veteran population overall.
To that end, our multi-disciplinary team of nationally distinguished researchers will assemble and analyze an unprecedented longitudinal database of linked VA and Department of Defense data, health records, social indicators, and death records of veterans receiving health care from 5 large civilian health systems in North Carolina and Utah. The database will yield an estimated 3.8 million person-year observations, including approximately 900 firearm-involved suicides and 1,190 total suicide deaths.
We will analyze these data to describe the demographic and health characteristics of veterans who utilize non-VHA healthcare services, their patterns of healthcare utilization, their mortality outcomes, and their incidence of suicide deaths, by method. We will use machine learning methods to develop specific risk algorithms for predicting all suicides and firearm-related suicides among veterans who utilize non-VHA healthcare, to identify veterans at elevated risk of suicide.
Utah-based collaborators will use linked VHA data to identify and describe risk patterns for veterans who combine VHA and non-VHA healthcare. Finally, we will conduct a series of key informant interviews to better understand barriers and facilitators to integrating this type of algorithm into civilian health system workflows.
In summary, the proposed work will fill critical gaps in the literature by leveraging large-scale, real-world data sources to yield novel knowledge of suicide risks, while informing prevention efforts aimed at reducing veteran suicide. We will also gather implementation information to inform how large civilian health systems will be able to use this information to identify and intervene with the veterans who are at greatest risk of suicide within their patient populations.
Awardee
Funding Goals
THE MISSION OF THE NATIONAL INSTITUTE OF MENTAL HEALTH (NIMH) IS TO TRANSFORM THE UNDERSTANDING AND TREATMENT OF MENTAL ILLNESSES THROUGH BASIC AND CLINICAL RESEARCH, PAVING THE WAY FOR PREVENTION, RECOVERY, AND CURE. WE FULFILL THIS MISSION BY SUPPORTING AND CONDUCTING RESEARCH ON MENTAL ILLNESSES, HEALTH SERVICES, AND THE UNDERLYING BASIC SCIENCE OF THE BRAIN AND BEHAVIOR; SUPPORTING THE TRAINING OF SCIENTISTS TO CARRY OUT BASIC AND CLINICAL MENTAL HEALTH RESEARCH; AND COMMUNICATING WITH SCIENTISTS, PATIENTS, PROVIDERS, AND THE PUBLIC ABOUT MENTAL HEALTH RESEARCH ADVANCES AND PRIORITIES. IN MAY 2024, NIMH RELEASED ITS STRATEGIC PLAN FOR RESEARCH. THE STRATEGIC PLAN BUILDS ON THE SUCCESSES OF PREVIOUS NIMH STRATEGIC PLANS BY PROVIDING A FRAMEWORK FOR SCIENTIFIC RESEARCH AND EXPLORATION, AND ADDRESSING NEW CHALLENGES IN MENTAL HEALTH.THE NEW STRATEGIC PLAN OUTLINES FOUR HIGH-LEVEL GOALS: GOAL 1: DEFINE THE BRAIN MECHANISMS UNDERLYING COMPLEX BEHAVIORS GOAL 2: EXAMINE MENTAL ILLNESS TRAJECTORIES ACROSS THE LIFESPAN GOAL 3: STRIVE FOR PREVENTION AND CURES GOAL 4: STRENGTHEN THE PUBLIC HEALTH IMPACT OF NIMH-SUPPORTED RESEARCH THESE FOUR GOALS FORM A BROAD ROADMAP FOR THE INSTITUTES RESEARCH PRIORITIES OVER THE NEXT FIVE YEARS, BEGINNING WITH THE FUNDAMENTAL SCIENCE OF THE BRAIN AND BEHAVIOR, AND EXTENDING THROUGH EVIDENCE-BASED SERVICES THAT IMPROVE PUBLIC HEALTH OUTCOMES.
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Durham,
North Carolina
277051104
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 71% from $1,927,302 to $3,287,373.
Duke University was awarded
Predicting Firearm Suicide in Veterans Outside VA
Project Grant R01MH129433
worth $3,287,373
from the National Institute of Mental Health in April 2023 with work to be completed primarily in Durham North Carolina United States.
The grant
has a duration of 4 years and
was awarded through assistance program 93.242 Mental Health Research Grants.
The Project Grant was awarded through grant opportunity Innovative Mental Health Services Research Not Involving Clinical Trials (R01 Clinical Trials Not Allowed).
Status
(Ongoing)
Last Modified 4/20/26
Period of Performance
4/1/23
Start Date
3/31/27
End Date
Funding Split
$3.3M
Federal Obligation
$0.0
Non-Federal Obligation
$3.3M
Total Obligated
Activity Timeline
Subgrant Awards
Disclosed subgrants for R01MH129433
Transaction History
Modifications to R01MH129433
Additional Detail
Award ID FAIN
R01MH129433
SAI Number
R01MH129433-1589770189
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Private Institution Of Higher Education
Awarding Office
75N700 NIH National Institute of Mental Health
Funding Office
75N700 NIH National Institute of Mental Health
Awardee UEI
TP7EK8DZV6N5
Awardee CAGE
4B478
Performance District
NC-04
Senators
Thom Tillis
Ted Budd
Ted Budd
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| National Institute of Mental Health, National Institutes of Health, Health and Human Services (075-0892) | Health research and training | Grants, subsidies, and contributions (41.0) | $963,651 | 100% |
Modified: 4/20/26