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Patient-reported outcomes as hospital performance measures: the challenge of confounding and how to handle it

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It is highly appealing to use patient-reported outcomes (PROs) as hospital performance measures; however, so far, the attention to key methodological issues has been limited. One of the most critical challenges when comparing PRO-based performance measures across providers is to rule out confounding. In this paper, we explain confounding and why it matters when comparing across providers. Using examples from studies, we present potential strategies for dealing with confounding when using PRO data at an aggregated level. We aim to give clinicians an overview of how confounding can be addressed in both the design stage (restriction, matching, self-controlled design and propensity score) and the analysis stage (stratification, standardization and multivariable adjustment, including multilevel analysis) of a study. We also briefly discuss strategies for confounding control when data on important confounders are missing or unavailable.

Original languageEnglish
JournalInternational Journal for Quality in Health Care
Pages (from-to)II59-II64
Publication statusPublished - Apr 2022

Bibliographical note

Publisher Copyright:
© 2022 The Author(s) 2022. Published by Oxford University Press on behalf of International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

    Research areas

  • confounding factors, patient-reported outcomes, quality of health care, small-area analysis

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