Creating Profiles for Cancer in Missouri by State Senatorial District

Background: Cancer incidence and mortality data have traditionally been presented in tables with rates shown by geographic area (e.g., county, region, state), tumor characteristic (e.g., site, histology, stage at diagnosis) and demographics (e.g., sex, race, ethnicity, age group). While useful and easily understandable by epidemiologists and statisticians, such tables are often difficult for some health professionals, cancer patients and the general public to interpret. Data visualization techniques offer an alternative way of presenting data that is more easily understood by these groups. The Missouri Cancer Registry and Research Center (MCR-ARC) has used data visualization to present cancer data for several years. In early 2015, we

Purpose: To expand data visualization efforts and display cancer incidence and mortality data by Missouri senatorial district.

Methods: We will give a live demonstration of traditional tables showing cancer incidence and mortality. Using an Internet connection to the MCR-ARC website, we will demonstrate how users can obtain incidence and mortality rates in a data visualization format (e.g., maps, graphs, bar charts) for all cancers and several major cancers by tumor characteristic (e.g., stage at diagnosis) for each of Missouri’s 34 state senatorial districts.

Results: We used data visualization techniques to create 34 Missouri Senatorial District Cancer Profiles, each containing a table showing cancer cases and deaths for black, white and total for each district and the state and another table showing percent of cases diagnosed at early, late and unknown stage for the state and senatorial district. We will show how senators and constituents can answer specific questions and easily comprehend the impact of all cancers and specific cancers on residents of the district.

Conclusions/Discussion: Data visualization offers a powerful means of showing the impact of cancer in a senatorial district. This may impact senators’ views of the importance of differences among constituents and contribute to health-related policy decisions. In the future, we hope to expand data visualization to include all legislative districts in the state.