REACH VET Suicide Risk Prediction and Recovery Engagement

Overview

Development stage

DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.

High-impact designation

High-impactSource: a) High-impact

Impact justification

Not reported

Start date

Not reported

Withheld from public reporting

Not reported

Mission

Topic area

Health and Medical

Operational functions

Forecasting and prediction, Clinical and medical Derived by keyword rules; see methodology

Problem the AI is intended to solve

Suicide is a low frequency event, but clinical attention and intervention can reduce the risk of suicide and other adverse behavioral health outcomes. REACH VET offers a targeted suicide prevention approach to focus attention on Veterans with the greatest risk/need. This AI system is designed to support identification of Veterans at an elevated risk of suicide or other preventable adverse outcomes to support mitigation of risks, if indicated.

Expected benefits

The REACH VET 2.0 model is expected to identify a population of Veterans at elevated risk of suicide and other adverse outcomes for review by providers. Providers conduct outreach to identified Veterans when appropriate. This model and the targeted prevention in which it is used (i.e. the REACH VET clinical program), is used to augment VHA's extensive clinical suicide prevention program. While VHA conducts universal screenings for suicide risk by asking patients structured questions regarding suicidality, this screening process does not identify all Veterans at elevated risk. The REACH VET model is intended to supplement clinical screening and assessments and support identification of changes in risk. The REACH VET model supplements clinical practices by identifying Veterans at statistical risk of suicide, given similarities in their health care data with prior suicide decedents. After identification, reevaluation of care and outreach are completed to support risk mitigation. This targeted prevention program was nationally implemented in VHA in 2017 and there was an evaluation of the effects of the REACH VET program. This evaluation found that REACH VET implementation was associated with greater treatment engagement, new safety plan documentation, and fewer mental health admissions, emergency department visits, and documented suicide attempts. Full findings of this program evaluation are available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8524305/.

System outputs

The REACH VET 2.0 predictive model provides an estimate of the likelihood of dying of suicide in the next month for all active VHA Veterans.

Technology

AI classification

Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…

System name(s)

Not reported

Custom-developed code

Yes

Public source code

Not reported

Sourcing

How it was built

Contract and in-houseSource: c) Developed with both contracting and in-house resources

Vendor (as reported)

Not reported

Vendors (standardized)

None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Not reported

Privacy Impact Assessment

Not reported

Authorization to Operate

Not reported

Demographic features

Not reported

Training and evaluation data

Not reported

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported