Assessment of cost and health resource utilization for elderly patients with heart failure and diabetes mellitus

J Card Fail. 2010 Jun;16(6):454-60. doi: 10.1016/j.cardfail.2010.01.007. Epub 2010 Mar 6.

Abstract

Background: Our aim was to examine the health resource utilization and cost of care associated with heart failure (HF) and diabetes mellitus (DM) for elderly Medicare enrollees.

Methods and results: A retrospective case-control design was used to identify 4 groups of elderly patients with HF and DM (n = 498), HF only (n = 1089), DM only (n = 971), and no-HF and no-DM (n = 5438) using an administrative database of a large urban academic health care system. Demographic, diagnostic, health resource utilization, and cost (reimbursement) data were obtained from the Medicare claims database for the years 2000 and 2001. Disease states were identified by ICD-9 codes. Costs and health resource utilization were compared across the groups. The mean total costs were highest for the group with HF and DM ($32,676), and second highest for the HF only group ($22,230). In multivariable models that adjusted for potentially influential covariates, the group with HF and DM had a 3-fold increase in total cost compared with the group without DM and HF (relative total cost = 4.51, 95% confidence interval 3.82-5.31).

Conclusions: The presence of DM has a substantial influence on the costs for managing older patients with HF. An integrated approach to management may be needed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Aged
  • Aged, 80 and over
  • Case-Control Studies
  • Confidence Intervals
  • Costs and Cost Analysis / economics
  • Diabetes Mellitus / economics*
  • Female
  • Health Care Costs
  • Health Resources / economics
  • Health Resources / statistics & numerical data*
  • Heart Failure / complications
  • Heart Failure / economics*
  • Humans
  • Length of Stay / statistics & numerical data
  • Male
  • Medicare / economics
  • Models, Statistical
  • Multivariate Analysis
  • Pennsylvania
  • Retrospective Studies
  • United States