Can patient injury claims be utilised as a quality indicator?

Health Policy. 2012 Feb;104(2):155-62. doi: 10.1016/j.healthpol.2011.08.012. Epub 2011 Sep 28.


Objectives: To examine the association between patient injury claims and well-known quality indicators and to assess whether claims can be utilised in performance measurement.

Methods: Data were derived from administrative registers and comprised hip and knee replacement patients (n=34181) in Finland from 1998 to 2003. Hospital-level correlations were calculated between claims and quality indicators (5-year revision rate, 1-year deep infection rate, and 14-day readmission rate), while logistic regression analysis was used to analyze patient-level data for an association between claims and quality indicators.

Results: Correlations between claims and revisions as well as claims and infections were statistically significant, with correlation coefficients ranging from 0.21 to 0.62. In the regression analysis, both the revision and the infection indicator had a positive and statistically significant association with filing a claim (OR 1.002; 95% CI 1.001-1.003 and 1.001; 1.00005-1.001, respectively) and obtaining compensation (1.003; 1.001-1.005 and 1.001; 1.0003-1.002, respectively).

Conclusions: A claims indicator has the potential to be applied as a quality indicator. It should be complemented, however, with other indicators or actions to improve its acceptability by health professionals and to mitigate its possible undesirable effects.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Arthroplasty, Replacement, Hip / adverse effects*
  • Arthroplasty, Replacement, Hip / legislation & jurisprudence
  • Arthroplasty, Replacement, Hip / statistics & numerical data
  • Arthroplasty, Replacement, Knee / adverse effects*
  • Arthroplasty, Replacement, Knee / legislation & jurisprudence
  • Arthroplasty, Replacement, Knee / statistics & numerical data
  • Compensation and Redress / legislation & jurisprudence
  • Female
  • Finland
  • Humans
  • Male
  • Malpractice / statistics & numerical data*
  • Medical Errors / legislation & jurisprudence
  • Medical Errors / statistics & numerical data
  • Middle Aged
  • Quality Indicators, Health Care / standards*