Addressing missing data in patient-reported outcome measures (PROMs): implications for comparing provider performance

Manuel Gomes, Nils Gutacker (), Chris Bojke and Andrew Street
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Chris Bojke: Centre for Health Economics, University of York, UK

No 101cherp, Working Papers from Centre for Health Economics, University of York

Abstract: Patient-reported outcome measures (PROMs) are now routinely collected in the English National Health Service (NHS) and used to compare and reward hospital performance within a high-powered pay-for-performance scheme. However, PROMs are prone to missing data. For example, hospitals often fail to administer the pre-operative questionnaire at hospital admission, or patients may refuse to participate or fail to return their post-operative questionnaire. A key concern with missing PROMs is that the individuals with complete information tend to be an unrepresentative sample of patients within each provider, and inferences based on the complete cases will be misleading. This study proposes a strategy for addressing missing data in the English PROMs survey using multiple imputation techniques, and investigates its impact on assessing provider performance. We find that inferences about relative provider performance are sensitive to the assumptions made about the reasons for the missing data.

Keywords: Missing data; Multiple Imputation; Patient-reported outcome measures; Provider performance; Missing not at Random (search for similar items in EconPapers)
Pages: 24 pages
Date: 2014-07
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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http://www.york.ac.uk/media/che/documents/papers/r ... ider_performance.pdf First version, 2014 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:chy:respap:101cherp

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