Using language processing to improve predictions of Veteran suicide risk

Can suicide theory-guided natural language processing of clinical progress notes improve existing prediction models of Veteran suicide mortality?

NIH-funded research Veterans Admin Palo Alto Health Care Sys · NIH-11145608

This study is looking to improve how we identify U.S. Veterans who might be at risk for suicide by using smart technology to analyze their medical notes, so we can better support those who need help the most.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionVeterans Admin Palo Alto Health Care Sys NIH-funded
Lab location1 site (Palo Alto, United States)
Project IDNIH-11145608 on NIH RePORTER

What this research studies

This research aims to enhance the prediction of suicide risk among U.S. Veterans by utilizing natural language processing to analyze clinical progress notes. By extracting valuable information from unstructured text in these notes, the study seeks to identify Veterans who may be at high risk of suicide more accurately. The approach involves developing a specialized system that can recognize and interpret suicide-related information, which has not been effectively utilized in current prediction models. The ultimate goal is to ensure that intervention resources are directed towards those Veterans who need them the most, potentially preventing suicide attempts and deaths.

Who could benefit from this research

Good fit: Ideal candidates for this research are U.S. Veterans, particularly those who have previously shown signs of mental health challenges or suicidal thoughts.

Not a fit: Patients who are not Veterans or those who do not have any history of mental health issues may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more accurate identification of Veterans at risk for suicide, allowing for timely and targeted interventions.

How similar studies have performed: Previous research has shown promise in using advanced data analysis techniques to improve risk prediction in various health contexts, suggesting that this approach could be effective.

Where this research is happening

Palo Alto, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.