Evaluating Discrepancies in Self-Reported Glaucoma and Electronic Health Records in the National Institutes of Health All of Us Database

Megan E Paul; Victoria L Tseng; Ken Kitayama; Fei Yu; Anne L Coleman

doi:10.1016/j.ogla.2023.03.003

Evaluating Discrepancies in Self-Reported Glaucoma and Electronic Health Records in the National Institutes of Health All of Us Database

Ophthalmol Glaucoma. 2023 Sep-Oct;6(5):521-529. doi: 10.1016/j.ogla.2023.03.003. Epub 2023 Mar 15.

Authors

Megan E Paul¹, Victoria L Tseng², Ken Kitayama³, Fei Yu⁴, Anne L Coleman⁵

Affiliations

¹ Department of Medical Education, Icahn School of Medicine at Mount Sinai, New York, New York.
² Department of Ophthalmology, Stein and Doheny Eye Institutes, University of California, Los Angeles, California.
³ Department of Ophthalmology, Stein and Doheny Eye Institutes, University of California, Los Angeles, California; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, California.
⁴ Department of Ophthalmology, Stein and Doheny Eye Institutes, University of California, Los Angeles, California; Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, California.
⁵ Department of Ophthalmology, Stein and Doheny Eye Institutes, University of California, Los Angeles, California; Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, California. Electronic address: coleman@jsei.ucla.edu.

PMID: 36931428
DOI: 10.1016/j.ogla.2023.03.003

Abstract

Purpose: Patient understanding of glaucoma diagnosis is critical for disease management and it is unclear if there are racial/ethnic differences in this regard. The purpose of this study was to determine the level of agreement between glaucoma diagnosis by self-report and electronic health record (EHR) data using the National Institute of Health's "All of Us (AoU)" database and to examine the association between race/ethnicity and discordance of glaucoma diagnosis between self-report and EHR data.

Design: Cross-sectional study.

Participants: Individuals in AoU who answered a survey question about glaucoma diagnosis and had EHR data availability.

Methods: The agreement between self-reported glaucoma and EHR data was estimated using Cohen's κ coefficient. Multivariable logistic regression was performed, adjusting for age, sex, education level, income, and health care literacy, to examine the associations between race/ethnicity and discordance between self-reported glaucoma and EHR diagnosis.

Main outcome measures: Agreement between self-reported glaucoma and EHR diagnosis.

Results: Of all 87 782 individuals, 1985 (2.26%) had both self-reported and EHR glaucoma, 81 781 (92.16%) had no glaucoma, 2022 (2.31%) individuals had EHR-only glaucoma, and 1994 (2.27%) had self-report-only glaucoma (Cohen's κ = 0.47). In the multivariable regression, Black or African American (adjusted odds ratio [aOR], 1.67; 95% confidence interval [CI], 1.40-1.98), Asian (aOR, 2.63; 95% CI, 1.97-3.44), and Hispanic or Latino (aOR, 1.63; 95% CI, 1.33-1.99) individuals were more likely to have EHR-only glaucoma than White individuals. Additionally, Black or African American (aOR, 2.30; 95% CI, 1.97-2.67) and Hispanic or Latino individuals (aOR,1.47; 95% CI, 1.21-1.79) were more likely to have self-report-only glaucoma compared with White individuals.

Conclusions: In the AoU database, we found that Black or African American and Hispanic or Latino individuals had higher odds of discordance between glaucoma diagnosis by self-report and EHR. Future studies are needed to examine the issues leading to this discordance, such as a lack of patient understanding regarding their diagnosis or a lack of culturally appropriate physician explanation/teaching.

Financial disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Keywords: All of Us; Glaucoma; Patient education.

MeSH terms

Cross-Sectional Studies
Electronic Health Records
Glaucoma* / diagnosis
Humans
National Institutes of Health (U.S.)
Population Health*
Racial Groups
Self Report
United States / epidemiology