“The Centers for Medicare & Medicaid Services will use artificial intelligence to derive a patient’s race using factors like name, ZIP code, and language preference, when the patient’s race is not fully disclosed on hospital forms, to help spot and improve on health-care inequities.”
“The CMS thinks the computer-estimated data, from two algorithms developed by independent contractors, would be a closer match to what respondents might have self-reported if they were given more races and ethnicities to select from as their response. The de-identified data will be shared with hospitals, which already use information on race to identify risk factors for certain illnesses or to keep their own tabs on disparities in quality of care.”
The CMS currently relies on data from the Social Security Administration to understand health equity gaps among Medicare beneficiaries, but the accuracy is questionable. “For example, prior to 1980, only three categories were available for individuals to self-report race,” the CMS said. They were Black, White, and Other.
“The agency has tried updating incorrect information and initiatives like “direct mailings” to beneficiaries to no avail—the data’s accuracy still skews toward correctly identifying Black and White patients and struggling to identify other races.”
“Privacy advocates warn that the use of artificial intelligence could harm the very groups it’s trying to protect. The software is built to make decisions like humans do, meaning it tends to perpetuate the biases—perhaps unintentional—of its builders. People are also becoming more cautious about how their data is used and potentially misused, and the sensitivity of health-care data warrants added vigilance…” Read the full article here.
Source: Medicare AI Will Infer Race to Close Health Equity Gap – By Allie Reed, August 5, 2021. Bloomberg Law.
