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ORIGINAL ARTICLE
Year : 2020  |  Volume : 68  |  Issue : 3  |  Page : 427-432

Big data and the eyeSmart electronic medical record system - An 8-year experience from a three-tier eye care network in India


Department of eyeSmart EMR and AEye, L.V. Prasad Eye Institute, Hyderabad, Telangana, India

Correspondence Address:
Dr. Anthony Vipin Das
Department of eyeSmart EMR and AEye, L.V. Prasad Eye Institute, Road No 2, Banjara Hills, Hyderabad - 500 034, Telangana
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijo.IJO_710_19

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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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