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Abstract #79212 Published in IGR 20-1
Leveraging Electronic Health Records to Identify and Characterize Patients with Low Vision
Swenor BK; Guo X; Boland MV; Goldstein JEOphthalmic Epidemiology 2019; 26: 132-139
PURPOSE: To use electronic health record (EHR) data to estimate the prevalence and characteristics of low-vision (LV) patients. METHODS: EHR data were obtained for all patients at the nine clinical locations of the Wilmer Eye Institute in 2014. LV status at each visit was defined as visual acuity (VA) worse than 20/40 in the better-seeing eye. Prevalence and incidence estimates were determined over a 12-month period. Demographic and clinical data were used to compare the characteristics of patients with and without LV. Logistic regression analyses were used to determine prevalence and incidence estimates adjusted for age, sex, race, and ethnicity. RESULTS: A total of 100,755 patients were included in the analysis. There were 7752 (7.7%) prevalent and 1962 (2.1%) incident cases of LV. Among patients with LV, 55% had VA between 20/40 and 20/60. Outside of LV clinics, retina and glaucoma clinics had the highest prevalence (18% and 14%, respectively) and incidence (5% and 4%, respectively) of LV. The urban hospital center had twice the prevalence of LV than suburban clinics (11.5% vs. 5.6%). The odds of prevalent LV was greatest among patients 80 years and older (odds ratio = 6.18; 95% confidence interval: 5.62-6.80) as compared to those 20-39 years old. CONCLUSIONS: EHR can be used to estimate the prevalence and describe the characteristics of patients with LV seeking ophthalmic care. The highest prevalence rates of LV are observed in the urban setting and among patients obtaining retina and glaucoma care.
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Classification:
1.1 Epidemiology (Part of: 1 General aspects)
1.5 Glaucomas as cause of blindness (Part of: 1 General aspects)