ReviewJournal of racial and ethnic health disparities2026
Examining Ethnic and Racial Variations in Opioid-related Hospitalizations Using Western U.S. Electronic Health Records.
Review in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
8 authors.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.