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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Main Authors: Beau Abar, Ashley Holub, Steven Hong, Eric Aaserude, Vincent DeRienzo
Format: Article
Language:English
Published: eScholarship Publishing, University of California 2019-02-01
Series:Western Journal of Emergency Medicine
Online Access:https://escholarship.org/uc/item/5862t8mx
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spelling doaj-289f35215e854f9e88e4eee1434adcc62020-11-25T02:10:14ZengeScholarship Publishing, University of CaliforniaWestern Journal of Emergency Medicine1936-90182019-02-0120210.5811/westjem.2018.11.40144wjem-20-256Latent Class Analysis of Barriers to Care Among Emergency Department PatientsBeau AbarAshley HolubSteven HongEric AaserudeVincent DeRienzoIntroduction: 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.https://escholarship.org/uc/item/5862t8mx
collection DOAJ
language English
format Article
sources DOAJ
author Beau Abar
Ashley Holub
Steven Hong
Eric Aaserude
Vincent DeRienzo
spellingShingle Beau Abar
Ashley Holub
Steven Hong
Eric Aaserude
Vincent DeRienzo
Latent Class Analysis of Barriers to Care Among Emergency Department Patients
Western Journal of Emergency Medicine
author_facet Beau Abar
Ashley Holub
Steven Hong
Eric Aaserude
Vincent DeRienzo
author_sort Beau Abar
title 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_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_sort latent class analysis of barriers to care among emergency department patients
publisher eScholarship Publishing, University of California
series Western Journal of Emergency Medicine
issn 1936-9018
publishDate 2019-02-01
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.
url https://escholarship.org/uc/item/5862t8mx
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