Background: Opioid abuse is associated with substantial morbidity and often results in hospitalization. Despite this, patient-level factors associated with opioid-related hospitalizations are not well understood.
Methods: We used the Pennsylvania Health Care Cost Containment Council dataset (2000-2014) to identify opioid-related hospitalizations using primary and/or secondary ICD-9-CM hospital discharge codes for opioid use disorder (OUD), opioid poisoning, and heroin poisoning. Latent class analyses (LCA) of patient-level factors including sociodemographic characteristics, pregnancy, alcohol, tobacco, other substance use, and psychiatric disorders were used to identify common patterns within hospitalizations.
Results: Among 28,538,499 hospitalizations, 430,569 (1.5%) were opioid-related. LCA identified five latent class (LC) patient groups associated with opioid-related hospitalizations: pregnant women with OUD (LC1); women over 65 with opioid overdose (LC2); OUD, polysubstance use and co-occurring psychiatric disorders (LC3); patients with opioid overdose without co-occurring polysubstance use (LC4); and African American patients with OUD and co-occurring cocaine use (LC5). LC3 was the largest latent class (58.2%) with annual hospitalizations doubling over time.
Discussion: Among patients with opioid-related discharges, we identified five subpopulations among this sample. These findings suggest increased outpatient OUD treatment, mental health service support for patients with co-occurring psychiatric disorders and polysubstance use to prevent overdose and hospitalization.
Keywords: Latent class analysis; Opioid overdose; Opioid use disorder; Polysubstance use.
Copyright © 2019. Published by Elsevier B.V.