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Clustering of Social Determinants of Health Among Patients

INTRODUCTION/OBJECTIVES: Many health systems screen patients for social determinants of health and refer patients with social needs to community organizations for assistance. Understanding how social determinants cluster together may help guide assistance programs. METHODS: This study examined patie...

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Autores principales: Schiltz, Nicholas K., Chagin, Kevin, Sehgal, Ashwini R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310337/
https://www.ncbi.nlm.nih.gov/pubmed/35861297
http://dx.doi.org/10.1177/21501319221113543
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author Schiltz, Nicholas K.
Chagin, Kevin
Sehgal, Ashwini R.
author_facet Schiltz, Nicholas K.
Chagin, Kevin
Sehgal, Ashwini R.
author_sort Schiltz, Nicholas K.
collection PubMed
description INTRODUCTION/OBJECTIVES: Many health systems screen patients for social determinants of health and refer patients with social needs to community organizations for assistance. Understanding how social determinants cluster together may help guide assistance programs. METHODS: This study examined patients screened by The MetroHealth System in Cleveland, Ohio for 9 social determinants, including food insecurity, financial strain, transportation limitations, inability to pay for housing or utilities, intimate partner violence, social isolation, infrequent physical activity, daily stress, and lack of internet access. Clustering analyses were performed to determine which combination of social determinants occurred together more often than would be expected if each determinant were independent of each other. RESULTS: Among 23 161 screened patients, there were 19 dyads, 13 triads, and one tetrad of social determinants that clustered together. The most prevalent triad of food insecurity, social isolation, and inability to pay for housing or utilities occurred among 1095 patients but would be expected to occur among 284 patients, for an observed/expected ratio of 3.85 (95% confidence interval 3.64-4.07). In multivariate analyses, younger, Black, and lower income patients were 2 to 3 times more likely to have this triad compared to older, White, and wealthier patients. CONCLUSIONS: Social determinants of health frequently cluster together, and such clustering is associated with patient demographic characteristics. Further work is needed to determine how social determinant clusters impact health and cost outcomes and to develop programs that can address multiple co-existing social needs.
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spelling pubmed-93103372022-07-26 Clustering of Social Determinants of Health Among Patients Schiltz, Nicholas K. Chagin, Kevin Sehgal, Ashwini R. J Prim Care Community Health Original Research INTRODUCTION/OBJECTIVES: Many health systems screen patients for social determinants of health and refer patients with social needs to community organizations for assistance. Understanding how social determinants cluster together may help guide assistance programs. METHODS: This study examined patients screened by The MetroHealth System in Cleveland, Ohio for 9 social determinants, including food insecurity, financial strain, transportation limitations, inability to pay for housing or utilities, intimate partner violence, social isolation, infrequent physical activity, daily stress, and lack of internet access. Clustering analyses were performed to determine which combination of social determinants occurred together more often than would be expected if each determinant were independent of each other. RESULTS: Among 23 161 screened patients, there were 19 dyads, 13 triads, and one tetrad of social determinants that clustered together. The most prevalent triad of food insecurity, social isolation, and inability to pay for housing or utilities occurred among 1095 patients but would be expected to occur among 284 patients, for an observed/expected ratio of 3.85 (95% confidence interval 3.64-4.07). In multivariate analyses, younger, Black, and lower income patients were 2 to 3 times more likely to have this triad compared to older, White, and wealthier patients. CONCLUSIONS: Social determinants of health frequently cluster together, and such clustering is associated with patient demographic characteristics. Further work is needed to determine how social determinant clusters impact health and cost outcomes and to develop programs that can address multiple co-existing social needs. SAGE Publications 2022-07-21 /pmc/articles/PMC9310337/ /pubmed/35861297 http://dx.doi.org/10.1177/21501319221113543 Text en © The Author(s) 2022 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
Schiltz, Nicholas K.
Chagin, Kevin
Sehgal, Ashwini R.
Clustering of Social Determinants of Health Among Patients
title Clustering of Social Determinants of Health Among Patients
title_full Clustering of Social Determinants of Health Among Patients
title_fullStr Clustering of Social Determinants of Health Among Patients
title_full_unstemmed Clustering of Social Determinants of Health Among Patients
title_short Clustering of Social Determinants of Health Among Patients
title_sort clustering of social determinants of health among patients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310337/
https://www.ncbi.nlm.nih.gov/pubmed/35861297
http://dx.doi.org/10.1177/21501319221113543
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