Inquiry: The Journal of Health Care Organization, Provision, and Financing (May 2018)

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

  • Yi Mu PhD,
  • Andrew I. Chin MD,
  • Abhijit V. Kshirsagar MD, MPH,
  • Yi Zhang PhD,
  • Heejung Bang PhD

DOI
https://doi.org/10.1177/0046958018771163
Journal volume & issue
Vol. 55

Abstract

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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.