Risk adjustment using administrative data-based and survey-derived methods for explaining physician utilization

Med Care. 2010 Feb;48(2):175-82. doi: 10.1097/MLR.0b013e3181c16102.


Objectives: The objective of this study was to evaluate an administrative data-based risk adjustment method for predicting physician utilization and the contribution of survey-derived indicators of health status. The results of this study will support the use of administrative data for planning, reimbursement, and assessing equity of physician utilization.

Methods: The Ontario portion of the 2000-2001 Canadian Community Health Survey was linked with administrative physician claims data from 2002-2003 and 2003-2004. Explanatory models of family physician (FP) and specialist physician (SP) utilization were run using demographic information and The Johns Hopkins University Adjusted Clinical Groups (ACG) Case-mix System. Survey-based measures of health status were then added to the models. The coefficient of determination, R, indicated the models' explanatory power.

Results: The study sample consisted of 25,558 individuals aged 20 to 79 years representing approximately 7.8 million people. Over the 2 years of study period, 82.5% of the study population had a FP visit with a median of 6 visits and 53.2% had a SP visit with a median of 1 visit. The R values based on administrative data alone were 33% and 21% for the frequency of FP and SP visits and 16% and 35% for having one or more visit to an FPs and SPs, respectively. The addition of the survey-based measures to the administrative data-based models produced less than a 2% increase in explanatory power for any outcome.

Conclusion: Administrative data-based measures of morbidity burden are valid and useful indicators of future physician utilization. The survey-derived measures used in this study did not contribute significantly to models on the basis of administrative data-based measures. These findings support the future use of administrative data-based data and Adjusted Clinical Groups for planning, reimbursement, and research.

Publication types

  • Comparative Study
  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Family Practice*
  • Female
  • Forecasting
  • Health Care Rationing
  • Health Care Surveys / statistics & numerical data*
  • Health Services Research / methods
  • Health Services Research / statistics & numerical data
  • Health Status Indicators*
  • Humans
  • Insurance Claim Review / statistics & numerical data*
  • Logistic Models
  • Male
  • Middle Aged
  • Morbidity
  • Ontario / epidemiology
  • Primary Health Care / statistics & numerical data*
  • Prospective Studies
  • Risk Adjustment / methods*