New models for predicting suicide risk

Combining data from electronic health records with results from standardized depression questionnaires better predicts suicide risk in the 90 days following either mental health specialty or primary care outpatient visits, reports a team from the Mental Health Research Network, led by Kaiser Permanente research scientists.

The study, “Predicting Suicide Attempts and Suicide Death Following Outpatient Visits Using Electronic Health Records,” conducted in five Kaiser Permanente regions (Colorado, Hawaii, Oregon, California and Washington), the Henry Ford Health System in Detroit, and the HealthPartners Institute in Minneapolis, was published today in theĀ American Journal of Psychiatry.

Combining a variety of information from the past five years of people’s electronic health records and answers to questionnaires, the new models predicted suicide risk more accurately than before, according to the authors. The strongest predictors include prior suicide attempts, mental health and substance use diagnoses, medical diagnoses, psychiatric medications dispensed, inpatient or emergency room care, and scores on a standardized depression questionnaire.

Full story at Science Daily