Identifying U.S. Counties for Telemedicine Intervention to Address Geographic Disparities in Urologic Cancer Mortality

Authors: Anne Corrigan*, Bloomberg School of Public Health, Paige Nichols, Mayo Clinic, Hiten Patel, Johns Hopkins Brady Urological Institute, Frank Curriero, Bloomberg School of Public Health
Topics: Medical and Health Geography, Rural Geography, Spatial Analysis & Modeling
Keywords: telemedicine, urology, urological cancer, internet access, cluster detection
Session Type: Poster
Day: 4/4/2019
Start / End Time: 3:05 PM / 4:45 PM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded


Poor access to urology care is associated with high urologic cancer mortality rates (MR). Integrating internet-based services, known as telemedicine, into urologic care has been a highlighted strategy to decrease geographic disparities in urologic cancer MR. However, telemedicine requires participant access to high-speed internet which may not be available. This project examines the association between internet access rates (IAR) and urologic cancer mortality rates (MR) and uses two methods to identify U.S. counties optimal for telemedicine intervention today and counties that require internet expansion to lay the foundation for telemedicine. Univariate and multivariate regressions were run to assess the association between MR for bladder, kidney, prostate, and testis cancer and IAR. Multivariate models adjusted for variables including access to urologists, rurality, income, education, race, and related health conditions. Counties optimal for telemedicine intervention were identified in two ways. First, we examined those counties with a high mortality rate, no urologist, high IAR, and telemedicine-friendly policy in place. Second, we performed unadjusted spatial cluster detection to identify counties of anomalous MR. The first method allows for more characteristics to be considered in the identification process while the second method maximizes efficiency of a potential intervention by targeting geographically clustered counties. There were 400 counties, in clusters for both high urologic cancer MR and high IAR, that could be targeted for immediate telemedicine intervention. There were 274 counties, in clusters for high urologic cancer MR but low IAR, that would benefit from the expansion of high-speed internet prior to intervention.

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