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Competing risks in quality and safety research: a framework to guide choice of analysis and improve reporting
  1. Perla J Marang-van de Mheen1,
  2. Hein Putter2,
  3. Esther Bastiaannet3,
  4. Alex Bottle4
  1. 1 Department of Biomedical Data Sciences, Medical Decision Making, J10-S, Leiden University Medical Center, Leiden, The Netherlands
  2. 2 Department of Biomedical Data Sciences, Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands
  3. 3 Department of Surgery, Leiden University Medical Center, Leiden, Zuid-Holland, The Netherlands
  4. 4 School of Public Health, Faculty of Medicine, Imperial College London, London, UK
  1. Correspondence to Dr Perla J Marang-van de Mheen, Department of Biomedical Data Sciences, Medical Decision Making, J10-S, Leiden University Medical Center, 2300 RC Leiden, The Netherlands; p.j.marang-van_de_mheen{at}lumc.nl

Abstract

When comparing hospitals on their readmission rates as currently done in the Hospital Readmission and Reduction Program (HRRP) in the USA, should we include the competing risk of mortality after discharge, which precludes the readmission, in the analysis? Not including competing risks in current HRRP metrics was raised recently as a limitation with possible unintended consequences, as financial penalties for higher readmission rates are more severe than for higher mortality rates. Incorrectly including or ignoring competing risks can both induce bias. In this paper, we present a framework to clarify situations when competing risks should be taken into account and when they should not. We argue that the research question and the perspective from which it is asked determine whether the competing risk is also of interest and should be included in the analysis, or if only the event of interest should be considered. This information is often not explicitly reported but is needed to interpret whether the results are valid. Using the examples of readmissions and cancer, we show how different research questions fit different perspectives from which these are asked (patient, system, regulatory/insurance). Slightly changing the research question or perspective may thus change the analysis. Even though some may argue that any introduced bias is likely to be small, in the context of the HRRP, even small changes may mean that a hospital will face (higher) financial penalties. The impact of getting it wrong matters.

  • health services research
  • pay for performance
  • performance measures
  • statistics

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Footnotes

  • Twitter @DrAlexBottle

  • Contributors PJM-vdM and AB conceived this study. PJM-vdM wrote the first draft. All the authors contributed to the development of the paper, critically reviewed the manuscript and approved the final version. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

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

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