Cargando…

Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems

BACKGROUND: Homelessness is associated with substantial morbidity. Data linkages between homeless and health systems are important to understand unique needs across homeless populations, identify homeless individuals not registered in homeless databases, quantify the impact of housing services on he...

Descripción completa

Detalles Bibliográficos
Autores principales: Trick, William E., Rachman, Fred, Hinami, Keiki, Hill, Jennifer C., Conover, Craig, Diep, Lisa, Gordon, Howard S., Kho, Abel, Meltzer, David O., Shah, Raj C., Stellon, Ed, Thangaraj, Padma, Toepfer, Peter S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117275/
https://www.ncbi.nlm.nih.gov/pubmed/33985452
http://dx.doi.org/10.1186/s12889-021-10958-8
_version_ 1783691562013687808
author Trick, William E.
Rachman, Fred
Hinami, Keiki
Hill, Jennifer C.
Conover, Craig
Diep, Lisa
Gordon, Howard S.
Kho, Abel
Meltzer, David O.
Shah, Raj C.
Stellon, Ed
Thangaraj, Padma
Toepfer, Peter S.
author_facet Trick, William E.
Rachman, Fred
Hinami, Keiki
Hill, Jennifer C.
Conover, Craig
Diep, Lisa
Gordon, Howard S.
Kho, Abel
Meltzer, David O.
Shah, Raj C.
Stellon, Ed
Thangaraj, Padma
Toepfer, Peter S.
author_sort Trick, William E.
collection PubMed
description BACKGROUND: Homelessness is associated with substantial morbidity. Data linkages between homeless and health systems are important to understand unique needs across homeless populations, identify homeless individuals not registered in homeless databases, quantify the impact of housing services on health-system use, and motivate health systems and payers to contribute to housing solutions. METHODS: We performed a cross-sectional survey including six health systems and two Homeless Management Information Systems (HMIS) in Cook County, Illinois. We performed privacy-preserving record linkage to identify homelessness through HMIS or ICD-10 codes captured in electronic medical records. We measured the prevalence of health conditions and health-services use across the following typologies: housing-service utilizers stratified by service provided (stable, stable plus unstable, unstable) and non-utilizers (i.e., homelessness identified through diagnosis codes—without receipt of housing services). RESULTS: Among 11,447 homeless recipients of healthcare, nearly 1 in 5 were identified by ICD10 code alone without recorded homeless services (n = 2177; 19%). Almost half received homeless services that did not include stable housing (n = 5444; 48%), followed by stable housing (n = 3017; 26%), then receipt of both stable and unstable services (n = 809; 7%). Setting stable housing recipients as the referent group, we found a stepwise increase in behavioral-health conditions from stable housing to those known as homeless solely by health systems. Compared to those in stable housing, prevalence rate ratios (PRR) for those without homeless services were as follows: depression (PRR = 2.2; 95% CI 1.9 to 2.5), anxiety (PRR = 2.5; 95% CI 2.1 to 3.0), schizophrenia (PRR = 3.3; 95% CI 2.7 to 4.0), and alcohol-use disorder (PRR = 4.4; 95% CI 3.6 to 5.3). Homeless individuals who had not received housing services relied on emergency departments for healthcare—nearly 3 of 4 visited at least one and many (24%) visited multiple. CONCLUSIONS: Differences in behavioral-health conditions and health-system use across homeless typologies highlight the particularly high burden among homeless who are disconnected from homeless services. Fragmented and high use of emergency departments for care should motivate health systems and payers to promote housing solutions, especially those that incorporate substance use and mental health treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10958-8.
format Online
Article
Text
id pubmed-8117275
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-81172752021-05-13 Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems Trick, William E. Rachman, Fred Hinami, Keiki Hill, Jennifer C. Conover, Craig Diep, Lisa Gordon, Howard S. Kho, Abel Meltzer, David O. Shah, Raj C. Stellon, Ed Thangaraj, Padma Toepfer, Peter S. BMC Public Health Research Article BACKGROUND: Homelessness is associated with substantial morbidity. Data linkages between homeless and health systems are important to understand unique needs across homeless populations, identify homeless individuals not registered in homeless databases, quantify the impact of housing services on health-system use, and motivate health systems and payers to contribute to housing solutions. METHODS: We performed a cross-sectional survey including six health systems and two Homeless Management Information Systems (HMIS) in Cook County, Illinois. We performed privacy-preserving record linkage to identify homelessness through HMIS or ICD-10 codes captured in electronic medical records. We measured the prevalence of health conditions and health-services use across the following typologies: housing-service utilizers stratified by service provided (stable, stable plus unstable, unstable) and non-utilizers (i.e., homelessness identified through diagnosis codes—without receipt of housing services). RESULTS: Among 11,447 homeless recipients of healthcare, nearly 1 in 5 were identified by ICD10 code alone without recorded homeless services (n = 2177; 19%). Almost half received homeless services that did not include stable housing (n = 5444; 48%), followed by stable housing (n = 3017; 26%), then receipt of both stable and unstable services (n = 809; 7%). Setting stable housing recipients as the referent group, we found a stepwise increase in behavioral-health conditions from stable housing to those known as homeless solely by health systems. Compared to those in stable housing, prevalence rate ratios (PRR) for those without homeless services were as follows: depression (PRR = 2.2; 95% CI 1.9 to 2.5), anxiety (PRR = 2.5; 95% CI 2.1 to 3.0), schizophrenia (PRR = 3.3; 95% CI 2.7 to 4.0), and alcohol-use disorder (PRR = 4.4; 95% CI 3.6 to 5.3). Homeless individuals who had not received housing services relied on emergency departments for healthcare—nearly 3 of 4 visited at least one and many (24%) visited multiple. CONCLUSIONS: Differences in behavioral-health conditions and health-system use across homeless typologies highlight the particularly high burden among homeless who are disconnected from homeless services. Fragmented and high use of emergency departments for care should motivate health systems and payers to promote housing solutions, especially those that incorporate substance use and mental health treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-021-10958-8. BioMed Central 2021-05-13 /pmc/articles/PMC8117275/ /pubmed/33985452 http://dx.doi.org/10.1186/s12889-021-10958-8 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Trick, William E.
Rachman, Fred
Hinami, Keiki
Hill, Jennifer C.
Conover, Craig
Diep, Lisa
Gordon, Howard S.
Kho, Abel
Meltzer, David O.
Shah, Raj C.
Stellon, Ed
Thangaraj, Padma
Toepfer, Peter S.
Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems
title Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems
title_full Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems
title_fullStr Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems
title_full_unstemmed Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems
title_short Variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems
title_sort variability in comorbidites and health services use across homeless typologies: multicenter data linkage between healthcare and homeless systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117275/
https://www.ncbi.nlm.nih.gov/pubmed/33985452
http://dx.doi.org/10.1186/s12889-021-10958-8
work_keys_str_mv AT trickwilliame variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT rachmanfred variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT hinamikeiki variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT hilljenniferc variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT conovercraig variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT dieplisa variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT gordonhowards variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT khoabel variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT meltzerdavido variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT shahrajc variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT stelloned variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT thangarajpadma variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems
AT toepferpeters variabilityincomorbiditesandhealthservicesuseacrosshomelesstypologiesmulticenterdatalinkagebetweenhealthcareandhomelesssystems