By Siddhartha Mukherjee.
Published in the New York Times Magazine.
Of the many small humiliations heaped on a young oncologist in his final year of fellowship, perhaps this one carried the oddest bite: A 2-year-old black-and-white cat named Oscar was apparently better than most doctors at predicting when a terminally ill patient was about to die. The story appeared, astonishingly, in The New England Journal of Medicine in the summer of 2007. Adopted as a kitten by the medical staff, Oscar reigned over one floor of the Steere House nursing home in Rhode Island. When the cat would sniff the air, crane his neck and curl up next to a man or woman, it was a sure sign of impending demise. The doctors would call the families to come in for their last visit. Over the course of several years, the cat had curled up next to 50 patients. Every one of them died shortly thereafter…
But what if an algorithm could predict death? In late 2016 a graduate student named Anand Avati at Stanford’s computer-science department, along with a small team from the medical school, tried to “teach” an algorithm to identify patients who were very likely to die within a defined time window. “The palliative-care team at the hospital had a challenge,” Avati told me. “How could we find patients who are within three to 12 months of dying?” This window was “the sweet spot of palliative care.” A lead time longer than 12 months can strain limited resources unnecessarily, providing too much, too soon; in contrast, if death came less than three months after the prediction, there would be no real preparatory time for dying — too little, too late. Identifying patients in the narrow, optimal time period, Avati knew, would allow doctors to use medical interventions more appropriately and more humanely. And if the algorithm worked, palliative-care teams would be relieved from having to manually scour charts, hunting for those most likely to benefit. [ . . .]
About the Author
Siddhartha Mukherjee is the author of The Emperor of All Maladies: A Biography of Cancer and, more recently, The Gene: An Intimate History.