October 2022—When I was in pathology training back in the ’90s, physicians carried around an index card for each patient, with all of the information we needed to know about them easily covered in that small space.
Today, the practice of medicine—and specifically the practice of pathology—looks very different in the era of big data. Of course, we still have to fill our traditional roles: making the correct diagnosis for individual patients and ensuring the integrity of laboratory results. But increasingly large data sets inform the diagnosis in individual cases and, at the same time, individual cases become data points in large data sets that inform the health of populations. Beginning in the 2000s with the value-based care movement and accelerating with the rise of high-parameter tests, we find ourselves having to be data scientists as much as physicians. We are being asked to incorporate data-heavy tests and pipelines, some of which require clinical decision support algorithms that demand a certain fluency with more sophisticated software. We find ourselves in the new position of considering population health in addition to patient health, an element that can involve predictive analytics and data mining.