Insurance-related differences in Chronic Conditions Data Warehouse comorbidities of Medicare beneficiaries.
Academic Article
Overview
abstract
OBJECTIVES: To demonstrate the prevalence of comorbidities documented by Chronic Conditions Data Warehouse (CCW) data for Medicare beneficiaries and to illustrate how failing to account for differences in reported comorbidities can result in information bias. STUDY DESIGN: Retrospective cohort study of Medicare beneficiaries who underwent coronary artery bypass grafting (CABG) between 2008 and 2019. METHODS: A total of 1,158,701 Medicare beneficiaries underwent CABG. The prevalence of CCW-reported comorbidities was compared between beneficiaries enrolled in Medicare Advantage (MA) or traditional Medicare (TM) plans. Median survival differences (with 95% CIs) were compared in unadjusted and risk-adjusted analyses using overlap propensity score weighting, with and without inclusion of CCW-reported comorbidities during risk adjustment. RESULTS: The proportion of MA-enrolled CABG recipients increased annually from 17.5% in 2008 to 38.3% in 2019. MA-enrolled beneficiaries had fewer CCW-reported comorbidities than TM-enrolled beneficiaries (average standardized mean difference across 27 CCW comorbidities, 0.431). After risk adjustment for demographics, median survival differed minimally between MA- and TM-enrolled beneficiaries (10.00 vs 10.05 years; difference, -15 [95% CI, -41 to 13] days). However, when CCW-reported comorbidity data were included in risk adjustment, MA-enrolled beneficiaries demonstrated substantially lower median survival (9.52 vs 10.91 years; difference, -507 [95% CI, -538 to -466] days). CONCLUSIONS: The prevalence of CCW-reported comorbidities differs significantly between TM-enrolled and MA-enrolled beneficiaries who underwent CABG. These differences can introduce substantial bias in risk-adjusted analyses that erroneously assume equivalent CCW-reported comorbidity documentation across insurance types. Medicare outcomes research that relies on CCW-reported comorbidity data without accounting for insurance-related differences may produce biased treatment-effect estimates, potentially misinforming clinical or policy decisions.
