The profile inter-unit reliability

Biometrics. 2020 Jun;76(2):654-663. doi: 10.1111/biom.13167. Epub 2019 Nov 10.

Abstract

To assess the quality of health care, patient outcomes associated with medical providers (eg, dialysis facilities) are routinely monitored in order to identify poor (or excellent) provider performance. Given the high stakes of such evaluations for payment as well as public reporting of quality, it is important to assess the reliability of quality measures. A commonly used metric is the inter-unit reliability (IUR), which is the proportion of variation in the measure that comes from inter-provider differences. Despite its wide use, however, the size of the IUR has little to do with the usefulness of the measure for profiling extreme outcomes. A large IUR can signal the need for further risk adjustment to account for differences between patients treated by different providers, while even measures with an IUR close to zero can be useful for identifying extreme providers. To address these limitations, we propose an alternative measure of reliability, which assesses more directly the value of a quality measure in identifying (or profiling) providers with extreme outcomes. The resulting metric reflects the extent to which the profiling status is consistent over repeated measurements. We use national dialysis data to examine this approach on various measures of dialysis facilities.

Keywords: health provider profiling; inter-unit reliability; national dialysis data; quality of care; reliability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Analysis of Variance
  • Biometry
  • Humans
  • Kidney Failure, Chronic / mortality
  • Kidney Failure, Chronic / therapy
  • Linear Models
  • Medicare
  • Outcome Assessment, Health Care / statistics & numerical data
  • Patient Readmission / statistics & numerical data
  • Quality of Health Care / statistics & numerical data*
  • Renal Dialysis / standards
  • Renal Dialysis / statistics & numerical data
  • Reproducibility of Results
  • United States / epidemiology