Abstract
It is widely accepted that social determinants of health (SDOH) play a significant role in the determination of health outcomes. There are several external factors in the natural, built, and social environment beyond the control of the individual which affect their health, and disproportionalities in the burdens of these elements perpetuate health and healthcare disparities. However, there is still no centralized repository that links geographic locations and entities to specific aspects of determinants of health. Moreover, there is not a comprehensive understanding of the spatial and conceptual relationships between them. Ontologies are widely used in health and biomedical research as a means of increasing interoperability between datasets and connecting them to predictable, subsequent health outcomes. Recent projects have also sought to include and expand upon SDOH domains to standardize SDOH vocabulary and make it more accessible in patient care (Dieterle, 2021; Jani et al., 2020; Brenas et al., 2019). However, there have been no ontologies found to date that consider mappable geographical elements for determination of spatial relationships between SDOH domains and health outcome data. The purpose of this study was to source real-world data on South Carolina SDOH elements from public domains, process and manipulate them to highlight relevant attributes and geographies, and compile them into a single repository to allow for proximity and accessibility analyses from geographic coordinate inputs. This methodology resulted in the creation of the `dhomer` R-package which enables the user to perform these analyses via simple coding functions within the R programming language. The package integrates several datasets of factors within the natural, built, and social environment at varying geographic granularities. While the purpose of this package is to assist in a larger study on colorectal cancer pathology and disparities, the capabilities of this repository to increase the ease of spatial analyses and eliminate the time normally relegated to data-sourcing extend well beyond the scope of that study and can be applied to any geographic study considering determinants of health and health disparities. By classifying the datasets into categories of SDOH within the repository as well, this project also prepares mappable data for easy integration to a new SDOH ontology and linkage to existing ontologies regarding SDOH and health outcomes. By creating a centralized repository for all SDOH data, rather than categorizing them independently, this project has the potential to revolutionize the way we conceptualize the relationships between elements of an individual's environment and their synergistic effects on human health. Furthermore, by considering all of the data concurrently, we can now better visualize disparities in the natural, built, and social environment and identify exacerbations of these disparities due to the compounding of several adverse elements that are otherwise invisible when considering the data separately.
Citation Format: Lauren Cuppy, Tami Crawford, Alexander V. Alekseyenko. Sourcing real-world data to build the Determinants of Health Ontology of Mappable Elements (DHOME) [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-002.
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