Lessons Learned from Designing an Aeronautical Reconnaissance Coverage Geographic Information System Dashboard in the Geographic Information System-Naïve Environment to Fit the Spatial Epidemiology Study - Irina Angel (Public Health, 2025)
BackgroundSince patient access to healthcare is controlled by geographic location, patient records routinely include street addresses, postal codes, or other location elements. By linking spatial, numeric, and categorical health data through a single interface, the aeronau-tical reconnaissance coverage geographic information system (ArcGIS) dashboard adds the dimension of location and the quality of health information needed at the point of care. Its functions may be used to answer questions that would be difficult to answer without integrating raw patient data with location intelligence technology. However, the provision of geographic information system (GIS) functionalities at the point of care has not been thoroughly investigated.AimThis paper evaluates the ArcGIS dashboard functionalities through a case study of disruption in care for international patient populations due to the coronavirus disease-2019 (COVID-19) pandemic based on their home locations at the tertiary hospital in the U. S. Since the data used in this case study comes from the hospital health data repository, constructing the dashboard afford-ed an opportunity to explore the provision of GIS functionalities in the GIS–naïve hospital environment.MethodsThe model used the loose-coupling approach where two components (electronic health records and GIS data) were integrated and visualized through dashboard linking operations and programming languages. The process resulted in three data-driven dashboard elements: area map, attribute table, and statistical plots, enabling simultaneous exploration of various properties of spatial data.ConclusionThis paper underpins the potential benefits of the provision of GIS functionalities in the electronic medical records to improve health outcomes, lower costs, and advance spatial epidemiology research. Additionally, it evaluates dashboard scaling limitations and solutions for overcoming the implementation barriers and proposes the future integration of the GIS dashboard with elec-tronic health records by using the health level seven (HL7) fast healthcare interoperability resources (FHIR).