Abstract

Background: People experiencing homelessness face significant medical and psychiatric illness, yet few studies have characterized the effects of multimorbidity within this population. This study aimed to (a) delineate unique groups of individuals based on medical, psychiatric, and substance use disorder profiles, and (b) compare clinical outcomes across groups.Methods: We extracted administrative data from a health system electronic health record for adults referred to the Durham Homeless Care Transitions program from July 2016 to June 2020. We used latent class analysis to estimate classes in this cohort based on clinically important medical, psychiatric and substance use disorder diagnoses and compared health care utilization, overdose, and mortality at 12 months after referral.Results: We included 497 patients in the study and found 5 distinct groups: “low morbidity” (referent), “high comorbidity,” “high tri-morbidity,” “high alcohol use,” and “high medical illness.” All groups had greater number of admissions, longer mean duration of admissions, and more ED visits in the 12 months after referral compared to the “low morbidity” group. The “high medical illness” group had greater mortality 12 months after referral compared to the “low morbidity” group (OR, 2.53, 1.03–6.16; 95% CI, 1.03–6.16; p = 0.04). The “high comorbidity” group (OR, 5.23; 95% CI, 1.57–17.39; p < 0.007) and “high tri-morbidity” group (OR, 4.20; 95% CI, 1.26–14.01; p < 0.02) had greater 12-month drug overdose risk after referral compared to the referent group.Conclusions: These data suggest that distinct groups of people experiencing homelessness are affected differently by comorbidities, thus health care programs for this population should address their risk factors accordingly.

Highlights

  • Medical respite programs provide a safe place for recovery from illness or injury for people experiencing homelessness (PEH)

  • Given that PEH face high rates of complex yet modifiable illness [4], and that medical, mental health, and substance use disorders are linked to high health care utilization [5, 6], there remains a need to understand the specific risks that multimorbid health profiles portend for this population

  • This study examined data from 497 adults referred to Durham Homeless Care Transitions (DHCT), a transitional care and medical respite program for PEH, from July 1, 2016 through June 30, 2020

Read more

Summary

Introduction

Medical respite programs provide a safe place for recovery from illness or injury for people experiencing homelessness (PEH). Given that PEH face high rates of complex yet modifiable illness [4], and that medical, mental health, and substance use disorders are linked to high health care utilization [5, 6], there remains a need to understand the specific risks that multimorbid health profiles portend for this population. Population segmentation using latent class analysis (LCA) is one method to tailor integrated health care interventions to groups facing high rates of multimorbidity with the aim of reducing negative clinical outcomes and unnecessary health care utilization [7]. People experiencing homelessness face significant medical and psychiatric illness, yet few studies have characterized the effects of multimorbidity within this population. This study aimed to (a) delineate unique groups of individuals based on medical, psychiatric, and substance use disorder profiles, and (b) compare clinical outcomes across groups

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call