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Latent Class Analysis of Barriers to Care Among Emergency Department Patients

INTRODUCTION: Emergency department (ED) patients experience a variety of barriers to care that can lead to unnecessary or repeated visits. By identifying the patterns of barriers experienced by subsets of the ED patient population, future researchers might effectively design interventions to circumv...

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Autores principales: Abar, Beau, Holub, Ashley, Hong, Steven, Aaserude, Eric, DeRienzo, Vincent
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Department of Emergency Medicine, University of California, Irvine School of Medicine 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404707/
https://www.ncbi.nlm.nih.gov/pubmed/30881545
http://dx.doi.org/10.5811/westjem.2018.11.40144
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author Abar, Beau
Holub, Ashley
Hong, Steven
Aaserude, Eric
DeRienzo, Vincent
author_facet Abar, Beau
Holub, Ashley
Hong, Steven
Aaserude, Eric
DeRienzo, Vincent
author_sort Abar, Beau
collection PubMed
description INTRODUCTION: Emergency department (ED) patients experience a variety of barriers to care that can lead to unnecessary or repeated visits. By identifying the patterns of barriers experienced by subsets of the ED patient population, future researchers might effectively design interventions to circumvent these barriers and improve care. This study sought to identify classes of individuals with regard to perceived barriers to care. METHODS: Over a 10-week period, two medical students distributed surveys to eligible patients ≥18 years who presented to the ED. After consent, patients provided demographics data and rated their perceived access to care on nine specific items (scored 1–5). We used latent class analysis (LCA), a parametric clustering method, to determine patient groups. Demographic characteristics were then compared across classes. RESULTS: We enrolled a total of 637 patients. Results of the LCA indicated that a six-class solution fit best: 1) low barriers (60%); 2) “work responsibility” barriers (13%); 3) economic-related barriers (10%); 4) “appointment difficulty” barriers (8%); 5) “illness and care responsibilities” barriers (6%); and 6) diverse barriers (2%). Patients in the low-barriers class were the oldest across classes (p<.001). Individuals in the low-barriers class were also more likely to be White (p=.015) and have private insurance (p<.001) than those in the “appointment difficulty,” “illness and care responsibilities,” and diverse barriers classes. CONCLUSION: LCA suggests there are six distinct classes of patients with regard to perceived access to care. These classes may be used as a potential starting point in designing targeted interventions for ED patients to improve continuity of care.
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spelling pubmed-64047072019-03-15 Latent Class Analysis of Barriers to Care Among Emergency Department Patients Abar, Beau Holub, Ashley Hong, Steven Aaserude, Eric DeRienzo, Vincent West J Emerg Med Healthcare Utilization INTRODUCTION: Emergency department (ED) patients experience a variety of barriers to care that can lead to unnecessary or repeated visits. By identifying the patterns of barriers experienced by subsets of the ED patient population, future researchers might effectively design interventions to circumvent these barriers and improve care. This study sought to identify classes of individuals with regard to perceived barriers to care. METHODS: Over a 10-week period, two medical students distributed surveys to eligible patients ≥18 years who presented to the ED. After consent, patients provided demographics data and rated their perceived access to care on nine specific items (scored 1–5). We used latent class analysis (LCA), a parametric clustering method, to determine patient groups. Demographic characteristics were then compared across classes. RESULTS: We enrolled a total of 637 patients. Results of the LCA indicated that a six-class solution fit best: 1) low barriers (60%); 2) “work responsibility” barriers (13%); 3) economic-related barriers (10%); 4) “appointment difficulty” barriers (8%); 5) “illness and care responsibilities” barriers (6%); and 6) diverse barriers (2%). Patients in the low-barriers class were the oldest across classes (p<.001). Individuals in the low-barriers class were also more likely to be White (p=.015) and have private insurance (p<.001) than those in the “appointment difficulty,” “illness and care responsibilities,” and diverse barriers classes. CONCLUSION: LCA suggests there are six distinct classes of patients with regard to perceived access to care. These classes may be used as a potential starting point in designing targeted interventions for ED patients to improve continuity of care. Department of Emergency Medicine, University of California, Irvine School of Medicine 2019-03 2019-02-04 /pmc/articles/PMC6404707/ /pubmed/30881545 http://dx.doi.org/10.5811/westjem.2018.11.40144 Text en Copyright: © 2019 Abar et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) License. See: http://creativecommons.org/licenses/by/4.0/
spellingShingle Healthcare Utilization
Abar, Beau
Holub, Ashley
Hong, Steven
Aaserude, Eric
DeRienzo, Vincent
Latent Class Analysis of Barriers to Care Among Emergency Department Patients
title Latent Class Analysis of Barriers to Care Among Emergency Department Patients
title_full Latent Class Analysis of Barriers to Care Among Emergency Department Patients
title_fullStr Latent Class Analysis of Barriers to Care Among Emergency Department Patients
title_full_unstemmed Latent Class Analysis of Barriers to Care Among Emergency Department Patients
title_short Latent Class Analysis of Barriers to Care Among Emergency Department Patients
title_sort latent class analysis of barriers to care among emergency department patients
topic Healthcare Utilization
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6404707/
https://www.ncbi.nlm.nih.gov/pubmed/30881545
http://dx.doi.org/10.5811/westjem.2018.11.40144
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