Application for Epidemiological Geographic Information System: An Open-Source Spatial Analysis Tool based on the Common Data Model (Preprint)

Abstract

BACKGROUND Although spatial epidemiology is widely used to evaluate geographic variations and disparities in health outcomes, constructing geographic statistical models usually requires a labor-intensive process that limits its overall utility. OBJECTIVE This study aimed to develop open-source software for scalable spatial epidemiological analysis based on standardized geocode and a health care database and to demonstrate its applicability and methodological quality across countries. METHODS We developed Application for Epidemiological Geographic Information System (AEGIS) based on a standardized geocode and common data model (CDM) for health care data. AEGIS was implemented to access the geographic distribution in the incidences and health outcomes of non–communicable and communicable diseases in South Korea and the United States, specifically, the (1) geographical distribution of incident cancers, (2) spatial heterogeneity of 5-year mortality in Korean patients with cancer, and (3) identification of an endemic area of malaria in South Korea and the United States. The results from South Korea were compared with those of previous studies to assess the reliability of AEGIS. RESULTS AEGIS provides two widely used spatial analysis methods for health outcome assessment: disease mapping and detection of concentrated clusters of medical conditions or outcomes. It was possible to describe the spatial distribution, assess the spatial heterogeneity, and detect the focused area of a medical condition or outcome in various databases from different countries. The AEGIS-generated spatial distribution of incident cancer in Korea was consistent with those of previous reports. AEGIS was able to detect the known endemic area of malaria in South Korea. CONCLUSIONS As an open-source, cross-country, spatial analytics solution, AEGIS may globally expedite the assessment of differences in geographic health outcomes through the use of standardized geocode and health care databases.