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April 10, 2026Journal of Racial and Ethnic Health Disparities0 citationsOpen Access

Examining Ethnic and Racial Variations in Opioid-related Hospitalizations Using Western U.S. Electronic Health Records

LSLois SuhEKEuiseong KoBBBeomsu Baek

Key Points

  • The study aims to analyze racial and ethnic differences in opioid-related hospitalizations using electronic health records from the Western United States.
  • Used inpatient data from the Healthcare Cost and Utilization Project for five Western states.
  • Identified opioid-related hospitalizations through diagnosis-related group codes for drug poisoning.
  • Calculated prevalence estimates across demographic, socioeconomic, and urbanicity factors.
  • Evaluated associations using Pearson’s Chi-square tests.
  • Identified variations in hospitalization rates by race/ethnicity and household income.
  • Patterns of opioid-related hospitalizations differed across states and geographic areas.
  • Highlighted the importance of geographic context in understanding opioid-related outcomes.

Abstract

The opioid epidemic remains a major public health crisis in the United States, with growing evidence of differential burden across racial and ethnic populations. While much of the existing literature has focused on opioid use disorder and overdose outcomes in White populations, fewer studies have examined patterns among underrepresented racial and ethnic groups, particularly in relation to geographic context and regional variation. Moreover, relatively few studies have jointly examined racial and ethnic differences in opioid-related hospitalizations within the Western United States, despite the region’s distinct demographic composition and healthcare context. This observational study examines opioid-related hospitalizations across racial/ethnic groups and geographic settings in the Western United States using electronic health record-derived inpatient data from the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) for Arizona, California, Colorado, Nevada, and Utah. Opioid-related hospitalizations were identified using diagnosis-related group codes for drug poisoning and toxic effects. Prevalence estimates were calculated across demographic, socioeconomic, and urbanicity strata, and unadjusted associations were evaluated using Pearson’s Chi-square tests. The analysis identifies variation in opioid-related hospitalization prevalence by race/ethnicity, household income, and urbanicity, with patterns differing across states and geographic contexts. These findings highlight the importance of considering both population composition and place-based factors when interpreting opioid-related outcomes. In addition, this study discusses the potential role of artificial intelligence, enabled approaches, including predictive modeling and natural language processing, as future tools to enhance surveillance, early identification of risk, and resource allocation in efforts to reduce opioid-related harm. The current findings suggest the value of region-specific, equity-oriented strategies to inform public health responses to opioid-related hospitalizations in diverse populations.

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Cite This Study

Suh et al. (2026) studied this question.

synapsesocial.com/papers/69d892d16c1944d70ce03fa8https://doi.org/10.1007/s40615-026-02960-w
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