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Identifying and quantifying variation between healthcare organisations and geographical regions: using mixed-effects models
  1. Gary Abel1,
  2. Marc N Elliott2
  1. 1 University of Exeter Medical School (Primary Care), Exeter, UK
  2. 2 RAND Corporation, Santa Monica, California, USA
  1. Correspondence to Dr Gary Abel, Primary Care, University of Exeter, Exeter EX1 2LU, UK; g.a.abel{at}exeter.ac.uk

Abstract

When the degree of variation between healthcare organisations or geographical regions is quantified, there is often a failure to account for the role of chance, which can lead to an overestimation of the true variation. Mixed-effects models account for the role of chance and estimate the true/underlying variation between organisations or regions. In this paper, we explore how a random intercept model can be applied to rate or proportion indicators and how to interpret the estimated variance parameter.

  • healthcare quality improvement
  • performance measures
  • quality measurement
  • statistics

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Footnotes

  • Contributors GAA conceived the paper. GAA and MNE jointly wrote the paper. Both GAA and MNE are statisticians with expertise in profiling of healthcare institutions. MNE leads the CMS Medicare CAHPS® (Consumer Assessment of Health Providers and Systems) Analysis project. GAA has advised NHS England on use of the Cancer Patient Experience data and Public Health England on the interpretation of variation.

  • Funding GAA was partly supported in this work by funding from Public Health England

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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