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Algorithmic psychiatry involves many practical complexities. The Veterans Health Administration, a division of the Department of Veterans Affairs, may be the first large health-care provider to confront them. A few days before Thanksgiving, 2005, a twenty-two-year-old Army specialist named Joshua Omvig returned home to Iowa, after an eleven-month deployment in Iraq, showing signs of post-traumatic stress disorder; a month later, he died by suicide in his truck. In 2007, Congress passed the Joshua Omvig Veterans Suicide Prevention Act, the first federal legislation to address a long-standing epidemic of suicide among veterans. Its initiatives—a crisis hotline, a campaign to destigmatize mental illness, mandatory training for V.A. staff—were no match for the problem. Each year, thousands of veterans die by suicide—many times the number of soldiers who die in combat. A team that included John McCarthy, the V.A.’s director of data and surveillance for suicide prevention, gathered information about V.A. patients, using statistics to identify possible risk factors for suicide, such as chronic pain, homelessness, and depression. Their findings were shared with V.A. caregivers, but, between this data, the evolution of medical research, and the sheer quantity of patients’ records, “clinicians in care were getting just overloaded with signals,” McCarthy told me.
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In 2013, the team started working on a program that would analyze V.A. patient data automatically, hoping to identify those at risk. In tests, the algorithm they developed flagged many people who had gone unnoticed in other screenings—a signal that it was “providing something novel,” McCarthy said. The algorithm eventually came to focus on sixty-one variables. Some are intuitive: for instance, the algorithm is likely to flag a widowed veteran with a serious disability who is on several mood stabilizers and has recently been hospitalized for a psychiatric condition. But others are less obvious: having arthritis, lupus, or head-and-neck cancer; taking statins or Ambien; or living in the Western U.S. can also add to a veteran’s risk.
In 2017, the V.A. announced an initiative called reach vet, which introduced the algorithm into clinical practice throughout its system. Each month, it flags about six thousand patients, some for the first time; clinicians contact them and offer mental-health services, ask about stressors, and help with access to food and housing. Inevitably, there is a strangeness to the procedure: veterans are being contacted about ideas they may not have had. The V.A. had “considered being vague—just saying, ‘You’ve been identified as at risk for a bunch of bad outcomes,’ ” McCarthy told me. “But, ultimately, we communicated rather plainly, ‘You’ve been identified as at risk for suicide. We wanted to check in and see how you’re doing.’ ”
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