ArticleIndian journal of ophthalmology2020
Big data and the eyeSmart electronic medical record system - An 8-year experience from a three-tier eye care network in India.
Article in Indian journal of ophthalmology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed, 111 citations in OpenAlex.
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- Sustainable ophthalmology: an overview of concepts and practices.Eye (London, England) · 2025Review
- Electronic medical record (EMR) pre-deployment assessment for adoption readiness, acceptability, and associated factors at Hiwot Fana comprehensive specialized university hospital.BMC medical informatics and decision making · 2025Article
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- Real-world experience of full-thickness traumatic macular hole among young patients.International journal of retina and vitreous · 2024Article
- Intraocular pressure and gonioscopic findings in primary angle-closure disease in India-a big data study.International journal of ophthalmology · 2024Article
- Herpes simplex virus keratitis: electronic medical records driven big data analytics report from a tertiary eye institute of South India.International ophthalmology · 2023Article
- Implementation and scalability of shared care models for chronic eye disease: a realist assessment informed by health system stakeholders in Finland, the United Kingdom, and Australia.Eye (London, England) · 2023Article
- Electronic medical records driven big data analytics in retinal diseases, report number 1: non-oncological retinal diseases in children and adolescents in India.International ophthalmology · 2023Article
- Clinical profile and demographic distribution of pseudoexfoliation syndrome: An electronic medical record-driven big data analytics from an eye care network in India.Indian journal of ophthalmology · 2023Article
- The microbiological landscape and epidemiology of ocular infections in a multi-tier ophthalmology network in India: an electronic medical record driven analytics report.Eye (London, England) · 2023Article
- Prediction and analysis of time series data based on granular computing.Frontiers in computational neuroscience · 2023Article
- The prediction capability of a cataract surgery risk stratification model based on a large electronic medical record dataset.Indian journal of ophthalmology · 2022Article
- Clinical profile and demographic distribution of ophthalmia nodosa: An electronic medical record-driven big data analytics from a multitier eye care network.Indian journal of ophthalmology · 2022Article
- Retinitis pigmentosa in Laurence-Moon-Bardet-Biedl syndrome in India: Electronic medical records driven big data analytics: Report II.Indian journal of ophthalmology · 2022Observational
- Consanguinity and ocular disorders in India: Electronic medical records driven big data analytics.Indian journal of ophthalmology · 2022Article
- Retinitis pigmentosa in Usher syndrome in India: Electronic medical records driven big data analytics: Report III.Indian journal of ophthalmology · 2022Observational
- Clinical profile and demographic distribution of Fuchs' endothelial dystrophy: An electronic medical record-driven big data analytics from an eye care network in India.Indian journal of ophthalmology · 2022Article
- Article
- Clinical profile and microbiological trends of therapeutic keratoplasty at a network of tertiary care ophthalmology centers in India.International ophthalmology · 2022Article
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To assess the demographic details and distribution of ocular disorders in patients presenting to a three-tier eye care network in India using electronic medical record (EMR) systems across an 8-year period using big data analytics. Methods: An 8-year retrospective review of all the patients who presented across the three-tier eye care network of L.V. Prasad Eye Institute was performed from August 2010 to August 2018. Data were retrieved using an in-house eyeSmart EMR system. The demographic details and clinical presentation and ocular disease profile of all the patients were analyzed in detail. Results: In an 8-year period, a total of 2,270,584 patients were captured on the EMR system with 4,730,221 consultations. More than half of the patients presented at tertiary centers (n = 1,174,643, 51.73%), a quarter at the secondary centers (n = 564,251, 24.85%) followed by the vision centers (n = 531,690, 23.42%). The ratio of males and females was 1.18:1. Most common states of presentation were Andhra Pradesh (n = 1,103,733, 48.61%) and Telangana (n = 661,969, 29.15%). In total, 3,721,051 ocular diagnosis instances were documented in the patients. Most common ocular disorders were related to cornea and anterior segment (n = 1,347,754, 36.22%) followed by refractive error (n = 1,133,078, 30.45%). Conclusion: This study depicts the demographic details and distribution of various ocular disorders in a very large cohort of patients. There is a need to adopt digitization in geographies that cater to large populations to enable insightful research. The implementation of EMR systems enables structured data for research purposes and the development of real-time analytics for the same.
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