Psychometric Properties and Methodological Quality of Healthcare Utilization Questionnaires in Adult Populations: A Systematic Review of 112 Validation Studies

Objectives: This study identified and synthesized validation evidence on healthcare utilization questionnaires (HUQs) in adult populations. Methods: A systematic review retrieved validation studies of HUQs from 5 databases from January 1990 to May 2024. Study characteristics, instrument features, and validation evidence were extracted. Measurement properties and methodological quality were assessed using Consensus-based Standards for Selection of Health Measurement Instruments. Results: Out of the 5626 records screened, 112 articles were included, predominantly from European and North-American countries and noninstitution settings (>80%). Eighty-eight HUQs were identified, with 90.9% being originally designed, 64.8% targeting specific conditions, and >50% being self or remotely administered. Over 90% HUQs measured medical care, whereas <50% addressed social care, productivity loss, or family care. Validation evidence was dispersed across instruments and individual items. Criterion validity was most frequently evaluated in 52 (59.1%) HUQs, followed by cross-cultural validity/measurement invariance (44.3%), content validity (42.0%), construct validity (34.1%), and reliability (20.5%). Thirty-four HUQs demonstrated acceptable criterion validity with quality evidence; fewer for construct validity (16), content validity (13), cross-cultural/measurement invariance (8), and reliability (7). Conclusions: Although numerous HUQs exist, most are original instruments with insufficient validation on measurement properties; only 11 met the minimum criteria for content validity and criterion validity or internal consistency. Selection of HUQs should comprehensively consider target population and disease, service scope, measurement property, and healthcare setting. Future efforts should prioritize rigorous scale development, validation against nonmedical resource, and applicability across diverse populations and settings, to support robust cross-context analyses and enhance study comparability at macro levels.