ArticlePloS one2021
Application of big-data for epidemiological studies of refractive error.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Reflective broadband adaptive optics scanning light ophthalmoscope with 20 D focus range.Biomedical optics express · 2026Article
- Temporal trends in refractive error among children and adolescents in Germany - a large-scale analysis of spectacle sales data from dispensing opticians from 2001 to 2025.Frontiers in public health · 2026Observational
- Fast and Slow Response of the Accommodation System in Young and Incipient-Presbyope Adults During Sustained Reading Task.Journal of clinical medicine · 2025Article
- Prevalence of refractive error in Portugal estimated from ophthalmic lens manufacturing data: Ten-years analysis.PloS one · 2023Article
- The Refractive Error and Vision Impairment Estimation with Spectacle Data Study.Ophthalmology science · 2022Article
- Using electronic medical record data to establish and monitor the distribution of refractive errorsJournal of optometry · 2022Article
- Application of big data in ophthalmology.Taiwan journal of ophthalmologyReview
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo examine whether data sourced from electronic medical records (EMR) and a large industrial spectacle lens manufacturing database can estimate refractive error distribution within large populations as an alternative to typical population surveys of refractive error. SUBJECTS: A total of 555,528 patient visits from 28 Irish primary care optometry practices between the years 1980 and 2019 and 141,547,436 spectacle lens sales records from an international European lens manufacturer between the years 1998 and 2016.
methodsAnonymized EMR data included demographic, refractive and visual acuity values. Anonymized spectacle lens data included refractive data. Spectacle lens data was separated into lenses containing an addition (ADD) and those without an addition (SV). The proportions of refractive errors from the EMR data and ADD lenses were compared to published results from the European Eye Epidemiology (E3) Consortium and the Gutenberg Health Study (GHS).
resultsAge and gender matched proportions of refractive error were comparable in the E3 data and the EMR data, with no significant difference in the overall refractive error distribution (χ2 = 527, p = 0.29, DoF = 510). EMR data provided a closer match to the E3 refractive error distribution by age than the ADD lens data. The ADD lens data, however, provided a closer approximation to the E3 data for total myopia prevalence than the GHS data, up to age 64.
conclusionsThe prevalence of refractive error within a population can be estimated using EMR data in the absence of population surveys. Industry derived sales data can also provide insights on the epidemiology of refractive errors in a population over certain age ranges. EMR and industrial data may therefore provide a fast and cost-effective surrogate measure of refractive error distribution that can be used for future health service planning purposes.
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