SDOH: A R Shiny application for predictive modeling Social Determinants of Health survey responses

Background: Social Determinants of Health (SDOH) surveys are data sets that provide useful health related information about individuals and communities at large. This study aims to develop a user-friend web application that allows clinicians to get predictive insight about the social needs of their patients prior to their in-patient visits using SDOH survey data to provide an improved and personalized service.
Method: The SDOH dataset used is a longitudinal survey that consists of 108,563 patient responses to 12 survey questions. It was collected from The University of Kansas Health System (TUKHS). The questions were designed to have a binary outcome as the response. Then the patient's most recent responses for each of these questions was modeled independently by incorporating explanatory variables. Multiple classification and regression techniques were used, including logistic regression, Bayesian generalized linear model, extreme gradient boosting, gradient boosting, neural networks, and random forests. Finally, these models were packaged into an R Shiny application that allows users to predict and make comparisons among models.
Results: Area under the curve (AUC) values for 72 models were calculated. Based on AUC values, Gradient Boosting models provided the highest precision values. Models were packaged into an R shiny application, a tool that can predict an individuals' response to a survey question based on their gender, race, ethnicity, age, and zip code.
Conclusions: We propose a predictive tool that aids the health system address patients in need of assistance and, by extension, improve their communities. This tool is hosted online as a freely available website by the University of Kansas Medical Center's Department of Biostatistics & Data Science: https://biostats-shinyr.kumc.edu/Predicting_SDOH/.The R source code and supporting materials used to host the models has been made publicly available on: github.com/CRISsupport/SDOH-Predictions-KS-WestMO.

Social Determinants of Health


Predictive modeling

Binary classification

R Shiny 

Mid-Level

Software & Data Science Technologies

Symposium on Data Science and Statistics (SDSS) 2023