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When You Think You’re Going To Die…
In another study, patients about to undergo surgery who were “convinced” of their impending death were compared to another group of patients who were merely “unusually apprehensive” about death. While the apprehensive bunch fared pretty well, those who were convinced they were going to die usually did.
A patient goes into the emergency room for a broken toe, is given a series of standardized tests, has their data fed into an algorithm, and—though they haven’t mentioned feeling depressed or having any suicidal thoughts—the machine identifies them as at high risk of suicide in the next week. Though the patient didn’t ask for help, medical professionals must now broach the subject of suicide and find some way of intervening.
This scenario, where an actionable diagnosis comes not from a doctor’s evaluation or family member’s concern, but an algorithm, is an imminent reality. Last year, data scientists at Vanderbilt University Medical Center in Nashville, Tennessee, created a machine-learning algorithm (paywall) that uses hospital-admissions data, including age, gender, zip code, medication, and diagnostic history, to predict the likelihood of any given individual taking their own life. In trials using data gathered from more than 5,000 patients who had been admitted to the hospital for either self-harm or suicide attempts, the algorithm was 84% accurate at predicting whether someone would attempt suicide in the next week, and 80% accurate at predicting whether someone would attempt suicide within the next two years.