How the Pandemic Made Algorithms Go Haywire

Algorithms have always had some trouble getting things right—hence the fact that ads often follow you around the internet for something you’ve already purchased. So the algorithm couldn’t effectively discern sicker from healthier patients, and consequently it flagged more than twice as many patients as “sick” even though hospital capacity was 35 percent lower than normal. We saw a similar issue first-hand in the hospital where we both work: We recently published a study examining a health care machine-learning algorithm used to identify the sickest of patients with cancer. Because of this decreased use of health care services, sicker patients did not have as much data to contribute to predictive algorithms. Third, COVID’s impact on health care and spending habits were particularly stark for marginalized populations, and that has led to algorithms being more likely to misfire for poor and nonwhite individuals.