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Pediatric Quality Measures in Vision Screening and Follow-Up
Alaa A Ahmed1, Genie Han1, Megan E Collins2
1Evidence-Based Practice Center, Department of Health Policy and Management, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland.
Context:
Timely detection and management of vision problems is essential in children for optimal outcomes.
Objective:
To summarize pediatric quality measures for vision screening and follow-up in the United States.
Data Sources:
PubMed, Embase, CINAHL, Cochrane Central, and PsychINFO (2009-December 2024), plus gray literature from governmental and nongovernmental sources.
Study Selection:
Relevant systematic reviews, original studies, and gray literature.
Data Extraction:
Two reviewers extracted information using Distiller SR and Excel.
Results:
We identified 50 vision screening and 34 follow-up measures, mostly focused on early childhood in primary care settings. Sources included 6 systematic reviews (7 screening and 10 follow-up measures), 12 studies (36 screening and 24 follow-up), and 11 gray literature (8 screening and 2 follow-up). We found evidence of reliability, validity, usability, and feasibility for 21, 32, 21, and 28 screening measures and for 5, 21, 11, and 9 follow-up measures, respectively; 3 screening and 9 follow-up measures had evidence against feasibility. Several sources showed improvement with the use of specific tools or implementation practices. Reports described differences by population, state, institution, or provider. Barriers were related to data infrastructure, collection, and measure standardization. Evidence was limited on demographic variations, use and alignment across care levels, and associated outcomes.
Limitations:
Exclusion of non-US sources and studies before 2009.
Conclusions:
Many pediatric vision screening and follow-up measures have evidence of reliability, validity, and usability, but feasibility is a concern. Research should prioritize feasible, standardized follow-up measures; integrated data systems; and evaluation, alignment, and stratification of measure outcomes.
