A comprehensive, machine-readable, mapped social determinants of health (SDH) taxonomy in machine readable format was developed. The framework is intended to facilitate the extraction of social risk factors out of electronic health record (EHR) data and categorizing them by domain and determinant to facilitate interpretation. Where other SDH frameworks have been focused on data input, this framework is designed from a data extraction point of view using EHR data in conjunction with published literature, public health policy documents, and official crosswalk maps. Frameworks developed by leading public health organizations were reviewed and synthesized to create an SDH framework comprising of 97 distinct social determinants organized under 16 domains. 2,329 medical codes across three standardized medical vocabularies, 10,896 free-text diagnosis descriptors, and 25 health insurance keywords were mapped to individual determinants in the SDH framework. The framework is available as an open-source resource in python dictionary or JSON format.
A copy of the machine-readable SDH taxonomy in a python dictionary and JSON formats has been made available online as an open-source resource for others in the community to use, add to, and refine. It can be found at https://github.com/Veradigm-Life-Sciences-Research/SDoHTaxonomy. At this site, readers will also find an SDH taxonomy content catalog, a full copy of our comparative analysis of SDH frameworks, python code examples, and a list of keywords and word pairing that were used for text mining.