A new study, spearheaded by the Veterans Affair’s Office (VA) and the National Institute of Mental Health (NIMH), successfully allowed scientists to “identify very small groups of individuals within the VHA’s patient population with very high, predicted suicide risk – most of whom had not been identified for suicide risk by clinicians.”

The study used a suicide risk algorithm developed by Dr. John McCarthy, director of the Serious Mental Illness Treatment Resource and Evaluation Center in the VA Office of Mental Health Operations, and his colleagues after analyzing the Veterans Health Administration’s (VHA) patient population data from fiscal years 2009 to 2011. “Data on the manner of death came from the National Death Index, and predictors of suicides and other types of death came from VHA clinical records.” Using one half of the patient population, researchers developed their predictive model, and then tested it on the remaining half. The researchers “compared predicted suicide risk to actual mortality to assess the performance of the predictive model.”

The predictive model is deemed successful as “even in groups with the highest predicted suicide risk based on the model, less than one-third of the patients had been identified clinically” by the VHA.

The impact and the importance of this study are insurmountable. Dr. Michael Schoenbaum, co-author of the report, states, “If the VA can identify small groups of people with a particularly high-risk of suicide, then they can target enhanced prevention and treatment services to these highest-risk individuals.”

This research will not only have an impact on the prevention of military personnel suicides but can be then used to help prevent civilian suicides.

The full NIH article can be read here.