A Medicare tool for adjusting risk underpredicts mortality and overpredicts spending for rural beneficiaries, according to research from the Philadelphia-based Leonard Davis Institute of Health Economics at the University of Pennsylvania.
The study, published in the September 2025 issue of Health Affairs Scholar, reviewed data from over 4 million traditional Medicare beneficiaries in 2018 through 2019 and compared spending risk predicted by the CMS Hierarchical Condition Category model with actual mortality rates.
While researchers said the model sufficed for urban beneficiaries, the model’s lack of consideration of social determinants of health could contribute to weaknesses with the rural population.
“Barriers such as reduced transportation access, limited diagnostic testing and lower quality of clinical documentation disproportionately affect rural beneficiaries,” LDI Senior Fellow Kristin Linn, PhD, said. “These factors result in undercoding of comorbidities and, consequently, underadjustment of risk scores.”
Incorrect spending and risk predictions could lead to lower payments for providers and plans in rural areas, exacerbating existing issues.
Rural health is not just top of mind in academia. All 50 states have applied to the $50 billion Rural Health Transformation Program by Nov. 5.
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