# Predictors of Mortality Among Patients With Opioid Use Disorder: Insights From the Healthcare Cost and Utilization Project (HCUP) Nationwide Readmission Database

## TL;DR

This study identifies factors that increase mortality risk in patients with opioid use disorder, including severe comorbidities and hospital characteristics, suggesting the need for integrated care.

## Contribution

The study provides novel insights into specific predictors of mortality among opioid use disorder patients using a large national database.

## Key findings

- Nonsurvivors had higher rates of cardiac arrest, respiratory failure, and acute kidney injury compared to survivors.
- Multivariable analysis showed cardiac arrest and respiratory failure as the strongest predictors of mortality.
- Psychiatric conditions like depression were more common in survivors, suggesting potential protective effects.

## Abstract

Background: Opioid use disorder (OUD) is associated with significantly increased mortality rates compared to the general population, driven by overdose risk, high-risk behaviors, and comorbid conditions. While opioid agonist treatment reduces mortality, identifying risk factors for death among individuals with OUD remains critical for improving outcomes.

Methods: A retrospective analysis of the 2020 National Readmission Database identified OUD admissions using International Classification of Diseases, 10th Revision, Clinical Modification codes. Patients over 18 years of age were included, and statistical analyses, including logistic regression, assessed 30-day readmission and mortality predictors. Data were analyzed using IBM Statistical Package for the Social Sciences Statistics for Windows, version 1.0.0.1327 (IBM Corp., Armonk, NY).

Results: Nonsurvivors were generally older (median age: 58 vs. 47 years) and had a higher prevalence of severe comorbidities, including cardiac arrest (24.1% vs. 0.4%, p < 0.001), respiratory failure (83.0% vs. 16.2%, p < 0.001), and acute kidney injury (61.9% vs. 16.8%, p < 0.001). Mortality was more common among patients with Medicare (44.4% vs. 31.7%) and in larger hospitals. Psychiatric conditions, such as depression and suicidal ideation, were more frequent in survivors, suggesting potential protective effects or earlier intervention. Multivariable analysis identified cardiac arrest (odds ratio, OR: 20.210, p < 0.001), respiratory failure (OR: 9.993, p < 0.001), and liver failure (OR: 4.298, p < 0.001) as the strongest mortality predictors, while female sex and psychiatric disorders were associated with lower mortality risk.

Conclusion: Mortality among patients with OUD is influenced by age, comorbidities, hospital characteristics, and healthcare disparities. Integrated care approaches that address both medical and psychiatric conditions are essential for improving survival outcomes. Future research should focus on targeted interventions to mitigate high-risk factors and enhance harm reduction strategies for this vulnerable population.