Abstract
Causal variance decompositions for a given disease-specific quality indicator can be used to quantify differences in performance between hospitals or health care providers. While variance decompositions can demonstrate variation in quality of care, causal mediation analysis can be used to study care pathways leading to the differences in performance between the institutions. This raises the question of whether the two approaches can be combined to decompose between-hospital variation in an outcome type indicator to that mediated through a given process (indirect effect) and remaining variation due to all other pathways (direct effect). For this purpose, we derive a causal mediation analysis decomposition of between-hospital variance, discuss its interpretation, and propose an estimation approach based on generalized linear mixed models for the outcome and the mediator. We study the performance of the estimators in a simulation study and demonstrate its use in administrative data on kidney cancer care in Ontario.
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The data that support the findings of this study are available from ICES (https://www.ices.on.ca/). Restrictions apply to the access to these data, which were used under agreement for this study.
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R code to reproduce the simulation study will be made available at the Journal website.
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Acknowledgements
This work was supported by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada (to OS), a Catalyst Grant in Health Services and Economics Research from the Canadian Institutes of Health Research (to AF, KAL and OS) and the Ontario Institute for Cancer Research through funding provided by the Government of Ontario (to BC). This study contracted ICES Data & Analytic Services (DAS) and used de-identified data from the ICES Data Repository, which is managed by ICES with support from its funders and partners: Canada’s Strategy for Patient-Oriented Research (SPOR), the Ontario SPOR Support Unit, the Canadian Institutes of Health Research and the Government of Ontario. The opinions, results and conclusions reported are those of the authors. No endorsement by ICES or any of its funders or partners is intended or should be inferred. Parts of this material are based on data and information compiled and provided by CIHI. However, the analyses, conclusions, opinions and statements expressed herein are those of the author, and not necessarily those of CIHI. Parts of this material are based on data and information provided by Cancer Care Ontario (CCO). The opinions, results, view, and conclusions reported in this paper are those of the authors and do not necessarily reflect those of CCO. No endorsement by CCO is intended or should be inferred.
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Chen, B., Lawson, K.A., Finelli, A. et al. Causal mediation analysis decomposition of between-hospital variance. Health Serv Outcomes Res Method 22, 118–144 (2022). https://doi.org/10.1007/s10742-021-00256-6
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DOI: https://doi.org/10.1007/s10742-021-00256-6