Bias in Health Care Prediction Algorithms May Lead to Disparate Provision of Health Care

Medical institutions have utilized algorithms in the provision of health care. Many of these algorithms have been useful in triaging patient care. However, one such algorithm may be detrimentally impacting access to health care and exacerbating existing health care disparities. A study from the University of California found that an algorithm that determines which patients receive priority access to “high-risk health care management programs” was racially biased. This algorithm erroneously accepted healthier white patients to the health care management program instead of accepting black patients who needed the services more. If the algorithm’s bias were corrected, it would “double the number of black patients automatically admitted” to the programs. Alarmingly, this particular algorithm is “widely used in the healthcare industry,” and many variations of these algorithms are employed by health care providers across the nation. The racial bias in the equation is a consequence of the algorithm’s structure, which correlated patient risk with health care costs. High health care costs do not necessarily correlate with the degree of sickness. As one executive highlighted, “[i]nstead of being trained to find the sickest, in a physiological sense, [these algorithms] ended up being trained to find the sickest in the sense of those whom we spend the most money on…And there are systemic racial differences in health care in who[m] we spend money on.”

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Blog post authored by Navpreet Natt

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