Assessing differences in social determinants of health screening rates in a large, urban safety-net health system
J Prim Care Community Health
INTRODUCTION/OBJECTIVE: Previous studies have evaluated the implementation of standardized social determinants of health (SDOH) screening within healthcare settings, however, less is known about where screening gaps may exist following initial implementation based on facility characteristics. The objective of this study is to assess differences in screening rates for SDOH at a large, urban healthcare system.
METHODS: We used electronic health record data obtained from NYC Health + Hospitals primary care sites from 2019 to 2022. We calculated the mean number of visits that were SDOH screened by visit type, facility size, and the percentages of community characteristics. We conducted 4 logistic regression models predicting the odds of screening for any SDOH and for specific SDOH needs (housing, food, and medical cost assistance) based on facility type, facility size, and the socioeconomic characteristics of the surrounding community.
RESULTS: Among the 3 212 650 visits included, 16.90% were SDOH screened. Across all 4 multivariate logistic regression models predicting SDOH screening, a visit had significantly lower odds of being screened if based at a midsize or small facility, if it was a telemedicine visit, or based at a facility located in a zip-code with a higher percentage of SDOH needs.
CONCLUSIONS: Our study found important differences in SDOH screening rates at a large, NYC-based health system based on size, visit type, and community level characteristics. In particular, our findings point to barriers related to facility size and telemedicine workflow that should be addressed to increase uptake of SDOH screening within different visits and facility types.
Lindenfeld Z, Chen K, Kapur S, Chang JE. Assessing differences in social determinants of health screening rates in a large, urban safety-net health system. J Prim Care Community Health. 2023;14:21501319231207713. DOI:10.1177/21501319231207713. PMID: 37916515