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. 2016 May;25(5):515-28.
doi: 10.1002/hec.3173. Epub 2015 Mar 5.

Addressing Missing Data in Patient-Reported Outcome Measures (PROMS): Implications for the Use of PROMS for Comparing Provider Performance

Manuel Gomes  1 , Nils Gutacker  2 , Chris Bojke  2 , Andrew Street  2
Affiliations

Addressing Missing Data in Patient-Reported Outcome Measures (PROMS): Implications for the Use of PROMS for Comparing Provider Performance

Manuel Gomes et al. Health Econ. 2016 May.

Abstract

Patient-reported outcome measures (PROMs) are now routinely collected in the English National Health Service 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 PROM 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; missing not at random; multiple imputation; patient-reported outcome measures; provider performance.

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Figures

Figure 1
Figure 1
Missing data and its implications for assessing provider performance via funnel plots
Figure 2
Figure 2
Kernel density of the risk‐adjusted post‐operative OHS for CCA and MI
Figure 3
Figure 3
Funnel plots of provider‐specific outcomes according to complete cases (N = 279), and after multiple imputation: volume and mean outcome effects (N = 298)
See this image and copyright information in PMC

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