Following the money: factors associated with the cost of treating high-cost Medicare beneficiaries

Health Serv Res. 2011 Aug;46(4):997-1021. doi: 10.1111/j.1475-6773.2011.01242.x. Epub 2011 Feb 9.


Objective: To identify factors associated with the cost of treating high-cost Medicare beneficiaries.

Data sources: A national sample of 1.6 million elderly, Medicare beneficiaries linked to 2004-2005 Community Tracking Study Physician Survey respondents and local market data from secondary sources.

Study design: Using 12 months of claims data from 2005 to 2006, the sample was divided into predicted high-cost (top quartile) and lower cost beneficiaries using a risk-adjustment model. For each group, total annual standardized costs of care were regressed on beneficiary, usual source of care physician, practice, and market characteristics.

Principal findings: Among high-cost beneficiaries, health was the predominant predictor of costs, with most physician and practice and many market factors (including provider supply) insignificant or weakly related to cost. Beneficiaries whose usual physician was a medical specialist or reported inadequate office visit time, medical specialist supply, provider for-profit status, care fragmentation, and Medicare fees were associated with higher costs.

Conclusions: Health reform policies currently envisioned to improve care and lower costs may have small effects on high-cost patients who consume most resources. Instead, developing interventions tailored to improve care and lowering cost for specific types of complex and costly patients may hold greater potential for "bending the cost curve."

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Female
  • Health Expenditures / statistics & numerical data*
  • Health Services Research / statistics & numerical data
  • Health Status
  • Humans
  • Insurance Claim Review / statistics & numerical data
  • Male
  • Medicare / statistics & numerical data*
  • Practice Patterns, Physicians' / statistics & numerical data
  • Residence Characteristics / statistics & numerical data
  • Risk Adjustment
  • United States