ArticleOphthalmology science2022
Social Determinants of Health Data Availability for Patients with Eye Conditions.
Article in Ophthalmology science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 31 citations in OpenAlex.
- Returning value to communities from the All of Us Research Program through the lens of social determinants of health and ethical, legal, and social implications.International journal for equity in health · 2026Review
- Identifying Patients at High Risk of Lapses in Diabetic Retinopathy Care: A Machine Learning Study.Ophthalmology science · 2026Article
- Complexity and Barriers to Vision Care: A Narrative Review Informed by a Mobile Eye Program.International journal of environmental research and public health · 2025Review
- Quality of Care in Patients With Newly Diagnosed Glaucoma.JAMA ophthalmology · 2025Article
- Identifying Transportation Needs in Ophthalmology Clinic Notes Using Natural Language Processing: Retrospective, Cross-Sectional Study.JMIR medical informatics · 2025Article
- High-Density Lipoproteins Associated with Age-Related Macular Degeneration in the All of Us Research Program.Ophthalmology · 2025Article
- The Association of Social Determinants of Health on Monitoring for Disease Progression Among Patients With Primary Open-Angle Glaucoma.Translational vision science & technology · 2025Article
- Pedagogical Principles in Implementing a Data Visualization Project in an Undergraduate Public Health Informatics Course.Applied clinical informatics · 2024Article
- Article
- Social determinants of health and health disparities in glaucoma: A review.Clinical & experimental ophthalmology · 2024Review
- Disparities in Eye Care Utilization Among Refugee and Migrant Populations.Translational vision science & technology · 2024Article
- Realizing the potential of social determinants data in EHR systems: A scoping review of approaches for screening, linkage, extraction, analysis, and interventions.Journal of clinical and translational science · 2024Article
- Social Determinants of Health in Pediatric Ophthalmology Patients: Availability of Data in the Electronic Health Record and Association With Clinic Attendance.Translational vision science & technology · 2023Article
- Social Risk Factor Associations With Presenting Visual Acuity in Patients With Microbial Keratitis.JAMA ophthalmology · 2023Article
- Association between Food Insecurity and Chronic Eye Disease in the National Institutes of Health's All of Us Research Program.Ophthalmology scienceArticle
- Entering the Exciting Era of Artificial Intelligence and Big Data in Ophthalmology.Ophthalmology scienceArticle
- Socioeconomic Disparities and Emergency Department Visits for Diabetic Retinopathy in California.Journal of vitreoretinal diseasesArticle
- Associations between Socioeconomic Factors and Visit Adherence among Patients with Glaucoma in the All of Us Research Program.Ophthalmology. GlaucomaArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Purpose: To quantify and characterize social determinants of health (SDoH) data coverage using single-center electronic health records (EHRs) and the National Institutes of Health All of Us research program. Design: Retrospective cohort study from June 2014 through June 2021. Participants: Adults 18 years of age or older with a diagnosis of diabetic retinopathy, glaucoma, cataracts, or age-related macular degeneration. Methods: For All of Us, research participants completed online survey forms as part of a nationwide prospective cohort study. In local EHRs, patients were selected based on diagnosis codes. Main Outcome Measures: Social determinants of health data coverage, characterized by the proportion of each disease cohort with available data regarding demographics and socioeconomic factors. Results: In All of Us, we identified 23 806 unique adult patients, of whom 2246 had a diagnosis of diabetic retinopathy, 13 448 had a diagnosis of glaucoma, 6634 had a diagnosis of cataracts, and 1478 had a diagnosis of age-related macular degeneration. Survey completion rates were high (99.5%-100%) across all cohorts for demographic information, overall health, income, education, and lifestyle. However, health care access (12.7%-29.4%), housing (0.7%-1.1%), social isolation (0.2%-0.3%), and food security (0-0.1%) showed significantly lower response rates. In local EHRs, we identified 80 548 adult patients, of whom 6616 had a diagnosis of diabetic retinopathy, 26 793 had a diagnosis of glaucoma, 40 427 had a diagnosis of cataracts, and 6712 had a diagnosis of age-related macular degeneration. High data coverage was found across all cohorts for variables related to tobacco use (82.84%-89.07%), alcohol use (77.45%-83.66%), and intravenous drug use (84.76%-93.14%). However, low data coverage (< 50% completion) was found for all other variables, including education, finances, social isolation, stress, physical activity, food insecurity, and transportation. We used chi-square testing to assess whether the data coverage varied across different disease cohorts and found that all fields varied significantly (P < 0.001). Conclusions: The limited and highly variable data coverage in both local EHRs and All of Us highlights the need for researchers and providers to develop SDoH data collection strategies and to assemble complete datasets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.