• Claudia Bull, Joshua Byrnes, Ruvini Hettiarachchi, and Martin Downes.
• Centre for Applied Health Economics (CAHE), Griffith University, Brisbane, Queensland, Australia.
• Health Serv Res. 2019 Oct 1; 54 (5): 1023-1035.

ObjectivesTo identify patient-reported experience measures (PREMs), assess their validity and reliability, and assess any bias in the study design of PREM validity and reliability testing.Data Sources/Study SettingArticles reporting on PREM development and testing sourced from MEDLINE, CINAHL and Scopus databases up to March 13, 2018.Study DesignSystematic review.Data Collection/Extraction MethodsCritical appraisal of PREM study design was undertaken using the Appraisal tool for Cross-Sectional Studies (AXIS). Critical appraisal of PREM validity and reliability was undertaken using a revised version of the COSMIN checklist.Principal FindingsEighty-eight PREMs were identified, spanning across four main health care contexts. PREM validity and reliability was supported by appropriate study designs. Internal consistency (n = 58, 65.2 percent), structural validity (n = 49, 55.1 percent), and content validity (n = 34, 38.2 percent) were the most frequently reported validity and reliability tests.ConclusionsCareful consideration should be given when selecting PREMs, particularly as seven of the 10 validity and reliability criteria were not undertaken in ≥50 percent of the PREMs. Testing PREM responsiveness should be prioritized for the application of PREMs where the end user is measuring change over time. Assessing measurement error/agreement of PREMs is important to understand the clinical relevancy of PREM scores used in a health care evaluation capacity.© Health Research and Educational Trust.

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