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Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System

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 ob...

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Autores principales: Lindenfeld, Zoe, Chen, Kevin, Kapur, Supriya, Chang, Ji Eun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624082/
https://www.ncbi.nlm.nih.gov/pubmed/37916515
http://dx.doi.org/10.1177/21501319231207713
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author Lindenfeld, Zoe
Chen, Kevin
Kapur, Supriya
Chang, Ji Eun
author_facet Lindenfeld, Zoe
Chen, Kevin
Kapur, Supriya
Chang, Ji Eun
author_sort Lindenfeld, Zoe
collection PubMed
description 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.
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spelling pubmed-106240822023-11-04 Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System Lindenfeld, Zoe Chen, Kevin Kapur, Supriya Chang, Ji Eun J Prim Care Community Health Original Research 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. SAGE Publications 2023-11-02 /pmc/articles/PMC10624082/ /pubmed/37916515 http://dx.doi.org/10.1177/21501319231207713 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Lindenfeld, Zoe
Chen, Kevin
Kapur, Supriya
Chang, Ji Eun
Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System
title Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System
title_full Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System
title_fullStr Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System
title_full_unstemmed Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System
title_short Assessing Differences in Social Determinants of Health Screening Rates in a Large, Urban Safety-Net Health System
title_sort assessing differences in social determinants of health screening rates in a large, urban safety-net health system
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10624082/
https://www.ncbi.nlm.nih.gov/pubmed/37916515
http://dx.doi.org/10.1177/21501319231207713
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