Creating algorithms to predict suicide risk in emergency department patients using health records
Development and clinical interpretation of machine learning emergency department suicide prediction algorithms using electronic health records and claims
['FUNDING_R01'] · UNIVERSITY OF PENNSYLVANIA · NIH-10837811
This study is working to help doctors in emergency rooms better spot patients who might be at risk of suicide, using smart technology to look at health records and data, so they can provide the right support and care when it's needed most.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF PENNSYLVANIA (nih funded) |
| Locations | 1 site (PHILADELPHIA, UNITED STATES) |
| Trial ID | NIH-10837811 on ClinicalTrials.gov |
What this research studies
This research aims to improve the identification of patients at risk of suicide who visit emergency departments for mental health issues. By utilizing advanced machine learning techniques, the project will analyze electronic health records and claims data to develop predictive models that assess the likelihood of non-fatal suicide events and suicide within 90 days of the emergency visit. The study will also involve collaboration with emergency department physicians to ensure that the developed tools are clinically relevant and useful for real-world applications. Ultimately, this research seeks to enhance the understanding of risk factors and improve patient outcomes in emergency settings.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals who present to emergency departments with mental health complaints and are at risk of suicide.
Not a fit: Patients who do not seek emergency care for mental health issues or those with stable mental health conditions may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to better identification and intervention for individuals at high risk of suicide, potentially saving lives.
How similar studies have performed: Other research has shown promise in using machine learning for predicting suicide risk, indicating that this approach could be effective.
Where this research is happening
PHILADELPHIA, UNITED STATES
- UNIVERSITY OF PENNSYLVANIA — PHILADELPHIA, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: MARCUS, STEVEN C — UNIVERSITY OF PENNSYLVANIA
- Study coordinator: MARCUS, STEVEN C
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.
Conditions: Mental health disorders, Psychiatric Disease, Psychiatric Disorder, psychological disorder, Mental disorders