Health affairs scholar · 2026
Unattributed Medicare beneficiaries have greater social disadvantage than those linked to primary care physicians.
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Ianni Katherine M, Hatfield Laura A
Аннотация
INTRODUCTION: Attributing patients to physicians using claims data is a key design feature of most payment and delivery models. However, claims-based attribution makes model participants less representative by excluding beneficiaries who use less care.
METHODS: We used the attribution methodology from the largest completed primary care model, Comprehensive Primary Care Plus (CPC+), to describe differences in attributable and unattributable Medicare beneficiaries living in CPC + regions from 2016 to 2021.
RESULTS: Unattributed beneficiaries were more male (56% vs 43%), eligible for the low-income drug subsidy (15% vs 12%), dual eligible (13% vs 10%), and non-White (22% vs 15%).
CONCLUSION: Tests of models that use claims-based attribution may fail to generate evidence relevant to underserved groups. Policymakers should consider attribution designs that could improve representativeness of model test populations.
METHODS: We used the attribution methodology from the largest completed primary care model, Comprehensive Primary Care Plus (CPC+), to describe differences in attributable and unattributable Medicare beneficiaries living in CPC + regions from 2016 to 2021.
RESULTS: Unattributed beneficiaries were more male (56% vs 43%), eligible for the low-income drug subsidy (15% vs 12%), dual eligible (13% vs 10%), and non-White (22% vs 15%).
CONCLUSION: Tests of models that use claims-based attribution may fail to generate evidence relevant to underserved groups. Policymakers should consider attribution designs that could improve representativeness of model test populations.