Colorado Law, a First, Targets Racist Health Care Algorithms

Health plans, always reliant on data, have deepened their focus on quantitative analysis and predictive algorithms in recent years — and experts warn that trend might also embed structural racism in health care even further. In response, Colorado passed a law earlier this year that bans health insurance companies from discriminating against members through “algorithms and predictive models,” which health care insiders say could kick off a nationwide trend of similar legislation.

Actuarial work has always been a fundamental part of the health insurance business. Even so, its importance has increased as firms have attempted to leverage emerging “big data” technologies to trim costs, calculate risk scores, and set premium rates; meanwhile, more provider contracts have moved to outcomes-based, capitated reimbursement based on intricate calculations. In addition, an industrywide attempt to address racial disparities in care and social determinants of health relies heavily on population health data and nonmedical demographic data. Ironically, that emphasis on taking race into account may have backfired.

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Peter Johnson

Peter Johnson

Peter has worked as a journalist since 2011 and has covered health care since 2020. At AIS Health, Peter covers trends in finance, business and policy that affect the health insurance and pharma sectors. For Health Plan Weekly, he covers all aspects of the U.S. health insurance sector, including employer-sponsored insurance, Medicaid managed care, Medicare Advantage and the Affordable Care Act individual marketplaces. In Radar on Drug Benefits, Peter covers the operations of (and conflicts between) pharmacy benefit managers and pharmaceutical manufacturers, with a particular focus on pricing dynamics and market access. Before joining AIS Health, Peter covered transportation, public safety and local government for various outlets in Seattle, his hometown and current place of residence. He graduated with a B.A. from Colby College.

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