Risk Model May Help Reduce Military Suicides
By Christine Kern, contributing writer
A recent study leads to the development of a computer program that helps reduce risks of suicides.
A recent study published by the JAMA Psychology set out to develop a program that could predict and intervene in cases where suicide was likely among soldiers. The research was conducted in response to a sharp increase in soldier suicides since 2004, revealing a greater risk of soldiers to take their own lives in the year immediately following inpatient treatment of psychiatric disorders.
Researchers analyzed data from 53,000 Army soldiers hospitalized between 2004 and 2009 for a psychiatric condition. During the study, 68 soldiers committed suicide within 12 months of release, a rate of 264 suicides per 100,000 hospitalized soldiers per year, compared to 18.5 suicides per 100,000 soldiers among all U.S. Army personnel.
The computer system factored in numerous variables, including age at military enlistment, rank, access to weapons, and history of run-ins with leadership. Furthermore, models were used to help predict suicide risk that relied heavily on self-reports and potential predictions of power. In order to determine if the soldiers had the highest suicide risk, the team tested and retested more than 300 factors.
Computer algorithms have already been shown to provide far more accurate prediction of suicide risk than doctors, since a computer model can calculate hundreds of potential risk factors at once according to Fox News. The study found that more than 50 percent of the study’s suicides came from the 5 percent of soldiers who were predicted by their model to have the highest risk of suicide after their hospital discharge.
“The high concentration of suicide risk in the 5 percent of highest-risk hospitalizations is striking,” study co-author Ronald Kessler, a professor of health care policy at Harvard Medical School, said in a statement. What's more, this 5 percent was also at high risk for other adverse outcomes following the individual's hospital release, including dying from an unintentional injury, attempting suicide or being readmitted to the hospital.
Spiraling suicide rates have plagued the Army since 2004. “Although interventions in this high-risk stratum would not solve the entire U.S. Army suicide problem, given that post-hospitalization suicides account for only 12 percent of all U.S. Army suicides, the algorithm would presumably help target preventive interventions,” the researchers wrote in the November 12 issue of the journal JAMA Psychiatry.
“According to their estimate, we could save four lives for every hundred people we treated,” Lt. Gen. Eric B. Schoomaker, a former surgeon general of the Army and a professor of military and emergency medicine at the Uniformed Services University of the Health Sciences in Bethesda, MD, told Science World Report. “This would be unparalleled, compared to almost any other intervention we could make in medicine. This study begins to show the positive effects big data can have, when combined with administrative health records.”
While more research is necessary before the computer model can be widely employed, and while it will most likely be applicable only to healthcare facilities that cater to the specific needs of military personnel, the study has widespread implications for suicide prevention in the future.