Wang, Yanshan
(2022)
Improving Health Equity by Analyzing Social Determinants of Health from the Electronic Health Records.
In: Pitt Momentum Fund 2022.
Abstract
Social determinants of health (SDOH) are the conditions under which people are born, grow, live, work, and age, and include factors such as socioeconomic status, education, employment, lifestyles, social support networks, access to medical care, and neighborhood characteristics. These factors have a major impact on health equity. With the passing of the HITECH Act in 2009, there has been increased emphasis on the use of electronic health records (EHRs) to document SDOH. While most of the documentation related to SDOH exists in free-text clinical notes, information on SDOH is also manifest in the structured data elements such as diagnosis codes. As a result, there is a big gap in leveraging heterogenous data within EHRs to infer a patient’s SDOH status. This study has two goals; 1) develop and evaluate artificial intelligence (AI) and natural language processing (NLP) models to automatically infer a patient’s respective SDOH from his/her EHRs; and 2) analyze the extracted SDOH information and provide implications for health equity. We hypothesize that applying digital technologies (e.g., AI, NLP) to extract and analyze the SDOH information embedded in EHRs will facilitate social and clinical research on SDOH, help understand current health disparities, and improve health equity among diverse populations.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
Metrics
Monthly Views for the past 3 years
Plum Analytics
Altmetric.com
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}