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

Health-care organization characteristics in cancer care delivery: an integrated conceptual framework with content validation

Context can influence cancer-related outcomes. For example, health-care organization characteristics, including ownership, leadership, and culture, can affect care access, communication, and patient outcomes. Health-care organization characteristics and other contextual factors can also influence whether and how clinical discoveries reduce cancer incidence, morbidity, and mortality. Importantly, policy, market, and technology changes are transforming health-care organization design, culture, and operations across the cancer continuum. Consequently, research is essential to examine when, for whom, and how organizational characteristics influence person-level, organization-level, and population-level cancer outcomes. Understanding organizational characteristics-the structures, processes, and other features of entities involved in health care delivery-and their dynamics is an important yet understudied area of care delivery research across the cancer continuum. Research incorporating organizational characteristics is critical to address health inequities, test care delivery models, adapt interventions, and strengthen implementation. The field lacks conceptual grounding, however, to help researchers identify germane organizational characteristics. We propose a framework identifying organizational characteristics relevant for cancer care delivery research based on conceptual work in health services, organizational behavior, and management science and refined using a systematic review and key informant input. The proposed framework is a tool for organizing existing research and enhancing future cancer care delivery research. Following a 2012 Journal of the National Cancer Institute monograph, this work complements National Cancer Institute efforts to stimulate research addressing the relationship between cancer outcomes and contextual factors at the patient, provider, team, delivery organization, community, and health policy levels.

A National Map of NCI-Designated Cancer Center Catchment Areas on the 50th Anniversary of the Cancer Centers Program

BACKGROUND

In 1971, the National Cancer Act created a process to recognize the leadership, facilities, and research efforts at cancer centers throughout the United States. Toward this goal, each NCI-designated cancer center defines and describes a catchment area to which they tailor specific scientific and community engagement activities.

METHODS

The geographically defined catchment areas of 63 NCI-designated comprehensive and clinical cancer centers are collated and presented visually. In addition, the NCI-designated cancer center catchment areas are geographically linked with publicly available data sources to aggregate sociodemographic and epidemiologic characteristics across the NCI Cancer Centers Program.

RESULTS

The national map portrays the size, shape, and locations for 63 catchment areas of the 71 NCI-designated cancer centers. The findings illustrate the geographic extent of the NCI Cancer Centers Program during the 50th anniversary of the National Cancer Act.

CONCLUSIONS

NCI-designated cancer centers occupy a prominent role in the cancer control ecosystem and continue to perform research to address the burden of cancer among their local communities. The strength of the NCI Cancer Centers Program is partly defined by the scope, quality, and impact of community outreach and engagement activities in the catchment areas.

IMPACT

The collation and geographic presentation of the distinct, but complementary, NCI-designated cancer center catchment areas are intended to support future research and community outreach activities among NCI-designated cancer centers. See related commentary by Vadaparampil and Tiro, p. 952.

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.