A systematic review of the validity and reliability of patient-reported experience measures

Health Serv Res. 2019 Oct;54(5):1023-1035. doi: 10.1111/1475-6773.13187. Epub 2019 Jun 19.

Abstract

Objectives: To 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 setting: Articles reporting on PREM development and testing sourced from MEDLINE, CINAHL and Scopus databases up to March 13, 2018.

Study design: Systematic review.

Data collection/extraction methods: Critical 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 findings: Eighty-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.

Conclusions: Careful 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.

Keywords: health care organization and systems; reliability; survey research and questionnaire design; systematic reviews/meta-analyses; validity.

Publication types

  • Systematic Review

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Cross-Sectional Studies
  • Female
  • Humans
  • Male
  • Middle Aged
  • Patient Reported Outcome Measures*
  • Patient Satisfaction / statistics & numerical data*
  • Reproducibility of Results
  • Surveys and Questionnaires / standards*