How well do diagnosis-related groups explain variations in costs or length of stay among patients and across hospitals? Methods for analysing routine patient data

Health Econ. 2012 Aug;21 Suppl 2:6-18. doi: 10.1002/hec.2837.


We set out an analytical strategy to examine variations in resource use, whether cost or length of stay, of patients hospitalised with different conditions. The methods are designed to evaluate (i) how well diagnosis-related groups (DRGs) capture variation in resource use relative to other patient characteristics and (ii) what influence the hospital has on their resource use. In a first step, we examine the influence of variables that describe each individual patient, including the DRG to which the patients are assigned and a range of personal and treatment-related characteristics. In a second step, we explore the influence that hospitals have on the average cost or length of stay of their patients, purged of the influence of the variables accounted for in the first stage. We provide a rationale for the variables used in both stages of the analysis and detail how each is defined. The analytical strategy allows us (i) to identify those factors that explain variation in resource use across patients, (ii) to assess the explanatory power of DRGs relative to other patient and treatment characteristics and (iii) to assess relative hospital performance in managing resources and the characteristics of hospitals that explain this performance.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Age Factors
  • Diagnosis-Related Groups / statistics & numerical data*
  • Episode of Care
  • Hospital Costs / statistics & numerical data*
  • Humans
  • Length of Stay / economics
  • Length of Stay / statistics & numerical data*
  • Models, Economic
  • Quality of Health Care / statistics & numerical data
  • Sex Factors
  • Socioeconomic Factors