Comorbidity profiles of patients experiencing homelessness: A latent class analysis

Keshab Subedi and Shweta Ghimire

PLOS ONE, 2022, vol. 17, issue 5, 1-9

Abstract: Individuals experiencing homelessness are known to have increased rates of healthcare utilization when compared to the average patient population, often attributed to their complex health care needs and under or untreated comorbid conditions. With increasing focus on hospital readmissions among acute care settings, a better understanding of these comorbidity patterns and their impacts on acute care utilization could help improve quality of care. This study aims to identify distinct comorbidity profiles of homeless patients, and to explore the correlates of the identified comorbidity profiles and their impact on hospital readmission. This is a retrospective analysis using electronic health records (EHR) of patients experiencing homelessness encountered in the hospitals of ChristianaCare from 2015 to 2019 (N = 3445). Latent class analysis (LCA) was used to identify the comorbidity profiles of homeless patients. The mean age of the study population was 44-year, and the majority were male (63%). The most prevalent comorbid conditions were tobacco use (77%), followed by depression (58%), drug use disorder (56%), anxiety disorder (50%), hypertension (44%), and alcohol use disorder (43%). The LCA model identified 4 comorbidity classes—“relatively healthy” class with 31% of the patients, “medically-comorbid with SUD” class with 15% of the patients, “substance use disorder (SUD)” class with 39%, and “Medically comorbid” class with 15% of the patients. The Kaplan-Meir curves of probability of readmission against time from the index visits were significantly different for the four classes (p

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0268841

DOI: 10.1371/journal.pone.0268841

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