Work

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

Year: 2014

Type: preprint

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.

Source: RePEc: Research Papers in Economics

Authors: Manuel Gomes, Nils Gutacker, Christopher Bojke, Andrew Street

Institution: University of York

Language: English

Topic: Statistical Methods and Bayesian Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: Medical Research Council, Division of Chemistry

Award: Developing appropriate methods for handling missing data in health economic evaluation.