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Aaron Y Lee, Cecilia S Lee; Big data visualizations of disparities in US cataract surgery delivery. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):1399.
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© ARVO (1962-2015); The Authors (2016-present)
To analyze the pattern in cataract care delivery at the national level by combining the US Census and Centers for Medicare & Medicaid Services (CMS) Medicare Provider Utilization and Payment data.
Cross-sectional study based on two publicly available sources: CMS Medicare Provider Data (https://data.cms.gov) and 2010 data from the United States Census Bureau. All analyses were performed with Python, PostGIS, and R. Reverse geocoding was performed on all addresses from the Medicare dataset. A hexagon layer was created to normalize the US Census data. The expected number of cataract extractions (CE) in one year by decade of life were extrapolated using a Gaussian Process model (Erie et al., 2007). A general linear regression model was used to compare differences among US regions.
There were 2.2 million Medicare patients who underwent CE in 2012. The expected number of CE and distance to nearest cataract surgeon are shown in Figure 1A,B. There were 1901 expected cataracts more than 100 miles from the nearest cataract surgeon, and a rank order of these states were calculated (Figure 2A). A 50 mile average was calculated for expected number of CE versus observed number of CE, split by US economic regions (Figure 2B). A ratio between these two values was significantly different among US regions (p < 2.2e-16) and was used to create a choropleth of cataract surgery disparity (Figure 1C).
There is a significant discrepancy in cataract delivery across the country based on geographic and economic regions. Publicly available Medicare datasets are valuable tools that can delineate public access and utilization patterns in the US healthcare system.
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