Discovering Associations between Social Determinants and Health Outcomes: Merging Knowledge Graphs from Literature and Electronic Health Data

Abstract

Social Determinants of Health (SDoH) are an increasingly important part of the broader research and public health efforts in understanding individuals' physical and mental well-being. Despite this, non-clinical factors affecting health are poorly recorded in electronic health databases and techniques to study how SDoH might relate to population outcomes are lacking. This paper proposes an approach to systematically identify and quantify associations between SDoH and health-related outcomes in a specific cohort of people by (1) leveraging published evidence from literature to build a knowledge graph of health and social factor associations and (2) analysing a large dataset of claims and medical records where those associations may be found. This work demonstrates how the proposed approach could be used to generate hypotheses and inform further research on SDoH in a data-driven manner.

Figure 1:

Illustration of the approach used in this paper

Figure 2:

Concept network representing housing problems. Each hexagon is a category and circles are UMLS entities that represent each category. Circles that are grayed out were not found by PubMed MetaMap.

Figure 3:

Concept network with ICD-9 and ICD-10 codes representing housing problems. Each hexagon represents a category and circles represent individual ICD codes. In the case of Homelessness they are ICD-10 Z59.0 and ICD-9 V60.0.