NCI Data Jamboree (Project Abstract Submission): Submission #58

Abstract Cancer centers, public health agencies, and community organizations often use different criteria to identify areas with the greatest need for cancer screening interventions. However, there is currently no standardized, flexible tool that allows users to compare how priority areas change when different screening, cancer burden, healthcare access, and sociodemographic indicators are emphasized. This project will develop a publicly accessible web mapping application that integrates county-level measures of cancer burden with tract-level measures of screening barriers and access to care to visualize high-priority areas for screen-detectable cancers across the United States. The project aligns with the NCI Data Jamboree goal of promoting data harmonization, integration, visualization, and analysis by creating a reproducible framework for combining multiple cancer-related datasets into an interactive decision-support tool. Datasets will include county-level cancer incidence and late-stage incidence measures from State Cancer Profiles (NCI and CDC) for breast, cervical, colorectal, lung, and prostate cancers. Cancer screening estimates will be from CDC PLACES. Measures of access will be derived from the ACR Lung Cancer Screening Registry, National Provider Identifier (NPI/NPPES) data, and FDA-certified mammography facility locations. Additional indicators describing sociodemographic characteristics, transportation access, health insurance coverage, and economic conditions will be from U.S. Census data. The resulting application will allow users to select indicators, assign priorities, and visualize how geographic targeting recommendations change under alternative decision-making frameworks. This functionality will support resource allocation, outreach planning, community engagement, and cancer screening program development. During the Jamboree, the team will develop automated data pipelines using APIs, integrate datasets into a unified geospatial database, design the application's prioritization framework and user interface, and optimize analytical workflows for rapid data processing and visualization. Team members with expertise in APIs, dashboard or mapping applications, R/Python, cancer risk factors, cancer screening, small area estimates, or cancer statistics are welcome to join.