Varied differences in the health status between Medicare advantage and fee-for-service enrollees

Regional and Temporal Variations in Comorbidity Among US Dialysis Patients: A Longitudinal Study of Medicare Claims Data

Medicare claims data are commonly used to query comorbidities for case-mix adjustment in research of patients with end-stage renal disease (ESRD) in the United States. These adjustments may affect reimbursement and quality rating through comparative profiling and ranking of dialysis facilities. We studied regional and temporal variations in comorbidity from claims data in the United States Renal Data System. Patients with a previous 1-year Medicare history who initiated dialysis therapy between 2006 and 2009 were examined with a follow-up period until 2012. By linking pre- and post-ESRD Medicare claims with the Dartmouth Atlas, we carried out a longitudinal data analysis with multivariable adjustment to investigate regional and temporal variations in the Liu comorbidity index. We identified 23 336 incident hemodialysis patients who were covered by Medicare the year prior to dialysis initiation and had survived with complete 3 years of follow-up data. With the United States divided into 4 geographic regions, the Western region was found to have the lowest Liu index over all 3 follow-up years, compared with the respective years in the other regions (Midwest, Northeast, and South). In comparison with the first year, the Liu index dropped significantly during the second and third years of follow-up across all 4 regions. Significant regional and temporal variations observed in the comorbidity index cannot be explained by differences in reimbursement (average per state) or predialysis comorbidity. Based on our exploratory study, future studies should focus on identifying the factors and reasons for these variations which have the potential to affect health care policy and research.

Mortality Differences Between Traditional Medicare and Medicare Advantage: A Risk-Adjusted Assessment Using Claims Data

Medicare Advantage (MA) has grown rapidly since the Affordable Care Act; nearly one-third of Medicare beneficiaries now choose MA. An assessment of the comparative value of the 2 options is confounded by an apparent selection bias favoring MA, as reflected in mortality differences. Previous assessments have been hampered by lack of access to claims diagnosis data for the MA population. An indirect comparison of mortality as an outcome variable was conducted by modeling mortality on a traditional fee-for-service (FFS) Medicare data set, applying the model to an MA data set, and then evaluating the ratio of actual-to-predicted mortality in the MA data set. The mortality model adjusted for clinical conditions and demographic factors. Model development considered the effect of potentially greater coding intensity in the MA population. Further analysis calculated ratios for subpopulations. Predicted, risk-adjusted mortality was lower in the MA population than in FFS Medicare. However, the ratio of actual-to-predicted mortality (0.80) suggested that the individuals in the MA data set were less likely to die than would be predicted had those individuals been enrolled in FFS Medicare. Differences between actual and predicted mortality were particularly pronounced in low income (dual eligibility), nonwhite race, high morbidity, and Health Maintenance Organization (HMO) subgroups. After controlling for baseline clinical risk as represented by claims diagnosis data, mortality differences favoring MA over FFS Medicare persisted, particularly in vulnerable subgroups and HMO plans. These findings suggest that differences in morbidity do not fully explain differences in mortality between the 2 programs.