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. 2020 Jan 1:2020:baaa054.
doi: 10.1093/database/baaa054.

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

Dinesh Pal Mudaranthakam  1   2 , Lisa M Harlan-Williams  2   3 , Roy A Jensen  2   3   4 , Hanluen Kuo  2   5 , Vandita Garimella  1 , Ronald C Chen  2   6 , Matthew S Mayo  1   2 , Hope Krebill  2   5
Affiliations

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

Dinesh Pal Mudaranthakam et al. Database (Oxford). .

Abstract

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.

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Figures

Figure 1
Figure 1
OPTIK data architecture.
Figure 2
Figure 2
The University of Kansas Cancer Center catchment area. The red star designates the location of the University of Kansas Medical Center in Kansas City, Kansas, Wyandotte County.
Figure 3
Figure 3
The University of Kansas Cancer Center Catchment Area. Color coding classifies counties by population density. Urban (150.0 persons per square mile (ppsm) or more), semi-urban (40–149.9 ppsm), densely settled rural (20–39.9 ppsm), rural (6–19.9 ppsm) and frontier (<6 ppsm).
Figure 4
Figure 4
The University of Kansas Cancer Center catchment area counties color coded by the percentage of non-Hispanic White in each county.
Figure 5
Figure 5
The University of Kansas Cancer Center catchment area counties color coded by the age adjusted cancer mortality rates. Data Source: Centers for Disease Control and Prevention.
Figure 6
Figure 6
(A) The University of Kansas Cancer Center catchment area counties’ heat map representing the mortality rates of colorectal cancer. Colorectal cancer mortality data was suppressed in 72 counties, all of which had populations <34 000. (B) The University of Kansas Cancer Center catchment area average standard rate capturing the mortality rates of colorectal cancer comparing rural versus urban. (C) The University of Kansas Cancer Center catchment area average standard rate capturing the mortality rates of colorectal cancer comparing African American versus all the other races.
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