# Developing Suicide Risk Algorithms for Diverse Clinical Settings using Data Fusion

> **NIH NIH R01** · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · 2020 · $854,246

## Abstract

Suicide is one of the most serious public health problems facing the United States. Recent evidence indicates
that many if not most of individuals who die by suicide have been in contact with the healthcare system in the
months prior to their death, providing data that can be used to identify patients at risk prior to an attempt. The
proposed project will develop an innovative method for identifying patients at risk of suicidal behavior using
data from a large multistate health information exchange, integrated with data from the State of Connecticut’s
CHIME hospital database. We will develop and test suicide risk algorithms using principles associated with
transfer learning, in which information from a comprehensive external data source is used to improve
prediction in a more limited dataset. Specifically, we will use multimodal data fusion techniques to develop and
test algorithms that can identify patients at risk of suicidal behavior by clinicians in hospitals with limited
numbers of patients, select patient populations, and lack of access to outpatient data. This approach is not
only generalizable to hospitals throughout the US but can be extended to very diverse clinical settings, e.g.,
primary and specialty care practices, community health centers, urgent care clinics.
The potential public health significance of this study is substantial. The fragmentation of the healthcare
system, particularly in relation to patients’ behavioral health needs, highlights the critical need to cultivate
comprehensive, system-wide approaches to identifying and managing at patients at risk of suicide.

## Key facts

- **NIH application ID:** 10104208
- **Project number:** 1R01MH124740-01
- **Recipient organization:** UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
- **Principal Investigator:** Robert H Aseltine
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $854,246
- **Award type:** 1
- **Project period:** 2020-09-16 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10104208

## Citation

> US National Institutes of Health, RePORTER application 10104208, Developing Suicide Risk Algorithms for Diverse Clinical Settings using Data Fusion (1R01MH124740-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10104208. Licensed CC0.

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