Rural-Urban Disparities in Health Access Factors Over Time: Implications for Cancer Prevention and Health Equity in the Midwest.

Purpose: Population-level environmental and socioeconomic factors may influence cancer burden within communities, particularly in rural and urban areas that may be differentially impacted by factors related to health care access. Methods: The University of Kansas (KU) Cancer Center serves a geographically large diverse region with 75% of its 123 counties classified as rural. Using County Health Rankings data and joinpoint regression, we examined trends in four factors related to the socioeconomic environment and health care access from 2009 to 2017 in rural and urban counties across the KU Cancer Center catchment area. Findings: The adult health uninsurance rate declined significantly in rural and urban counties across the catchment area (rural annual percent change [APC]=-5.96; 95% CI=[-7.71 to -4.17]; urban APC=-5.72; 95% CI=[-8.03 to -3.35]). Childhood poverty significantly decreased in rural counties over time (APC=-2.94; 95% CI=[-4.52 to -1.33]); in contrast, urban childhood poverty rates did not significantly change before 2012 (APC=3.68; 95% CI=[-15.12 to 26.65]), after which rates declined (APC=-5.89; 95% CI=[-10.01 to -1.58]). The number of primary care providers increased slightly but significantly in both rural and urban counties (APC=0.54; 95% CI=[0.28 to 0.80]), although urban counties had more primary care providers than rural areas (76.1 per 100K population vs. 57.1 per 100K population, respectively; p=0.009). Unemployment declined significantly faster in urban counties (APC=-10.33; 95% CI=[-12.16 to -8.47]) compared with rural counties (APC=-6.71; 95% CI=[-8.22 to -5.18]) (p=0.02). Conclusion: Our findings reveal potential disparities in systemic factors that may contribute to differences in cancer prevention, care, and survivorship in rural and urban regions.

shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area.

PURPOSE: The University of Kansas Cancer Center (KU Cancer Center) recently developed a data warehouse to Organize and Prioritize Trends to Inform KU Cancer Center (OPTIK). The OPTIK database aggregates and standardizes data collected across the bistate catchment area served by the KU Cancer Center. To improve the usability of the OPTIK database, we developed shinyOPTIK, a user-friendly, interactive web application for visualizing cancer risk factor and mortality rate data across the KU Cancer Center Catchment area. METHODS: Data in the OPTIK database were first consolidated at the county level across the KU Cancer Center catchment area. Next, the shinyOPTIK development team met with the KU Cancer Center leadership to discuss the needs and priorities of the shinyOPTIK web application. shinyOPTIK was developed under the R Shiny framework and consists of a user interface (ui.R) and a web server (server.R). At present, shinyOPTIK can be used to generate county-level geographical heatmaps; bar plots of demographic, screening, and risk factors; and line plots to visualize temporal trends at different Rural-Urban Continuum Codes (RUCCs), rural-urban status, metropolitan, or county levels across the KU Cancer Center catchment area. RESULTS: Two examples, adult obesity prevalence and lung cancer mortality, are presented to illustrate how researchers can use shinyOPTIK. Each example is accompanied by post hoc visualizations to help explain key observations in terms of rural-urban disparities. CONCLUSION: Although shinyOPTIK was developed to improve understanding of spatial and temporal trends across the population served by the KU Cancer Center, our hope is that the description of the steps involved in the creation of this tool along with open-source code for our application provided herein will serve as a guide for other research centers in the development of similar tools.

OPTIK: a database for understanding catchment areas to guide mobilization of cancer center assets.

An increasingly diversified demographic landscape in rural and urban America warrants the attention of The University of Kansas Cancer Center (KU Cancer Center) researchers, clinicians, outreach staff and administrators as the institution assesses ways to reach its expansive, bi-state catchment area. Within the counties of the KU Cancer Center catchment area, patient level and public health data are available and categorized by varying geographic regional boundaries. Multiple data sources and different data collection processes complicate summarizing catchment area data. A curated data warehouse that retrieves and structures the data, with a common denominator, can support meaningful use of the data in a standard and consistent format. The KU Cancer Center built a data warehouse to Organize and Prioritize Trends to Inform KU Cancer Center (OPTIK), which functions to streamline the process of synthesizing data regarding Kansas and Missouri demographics, cancer risk factors and incidence and mortality rates. OPTIK standardizes these diverse data sources to enable analyses of the cancer burden at local, regional and national levels while upholding a strict standard of patient privacy. The OPTIK database enables researchers to use available data and create heat maps and other visualizations to aid in funding proposals, presentations and research activities. Furthermore, using knowledge provided by OPTIK, the KU Cancer Center is able to prioritize action items for research and outreach and more effectively communicate the impact of those efforts.