Creating algorithms to identify patients at risk of suicide
Developing Suicide Risk Algorithms for Diverse Clinical Settings using Data Fusion
['FUNDING_R01'] · UNIVERSITY OF CONNECTICUT SCH OF MED/DNT · NIH-10647718
This study is working on new ways to spot people who might be at risk of suicide by looking at health information from different places, like hospitals and clinics, to help doctors find and support those in need before a crisis happens.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF CONNECTICUT SCH OF MED/DNT (nih funded) |
| Locations | 1 site (FARMINGTON, UNITED STATES) |
| Trial ID | NIH-10647718 on ClinicalTrials.gov |
What this research studies
This research aims to develop innovative algorithms that can identify individuals at risk of suicidal behavior by analyzing data from various healthcare sources. By integrating information from a multistate health information exchange and Connecticut's hospital database, the project will utilize advanced data fusion techniques to enhance prediction accuracy. The algorithms will be tested in diverse clinical settings, including hospitals, primary care practices, and community health centers, making them applicable across the healthcare system. This approach seeks to improve early identification of at-risk patients, ultimately aiming to prevent suicide attempts.
Who could benefit from this research
Good fit: Ideal candidates for this research include adults aged 21 and older who have interacted with the healthcare system and may be at risk for suicidal behavior.
Not a fit: Patients who are not in contact with healthcare services or those under 21 years old may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective identification and intervention for individuals at risk of suicide, potentially saving lives.
How similar studies have performed: Other research has shown success in using data-driven approaches to identify at-risk populations, indicating that this methodology has potential for impactful outcomes.
Where this research is happening
FARMINGTON, UNITED STATES
- UNIVERSITY OF CONNECTICUT SCH OF MED/DNT — FARMINGTON, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: ASELTINE, ROBERT H — UNIVERSITY OF CONNECTICUT SCH OF MED/DNT
- Study coordinator: ASELTINE, ROBERT H
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.