1704 - Racial and ethnic disparities in opioid misuse: Analysis of HCUP–NIS inpatient data from the Western United States

Friday, February 20, 2026

5:00 PM - 6:30 PM AST

Presenting Author(s)

LS

Lois Y. Suh, n/a

Medical Student
Kirk Kerkorian School of Medicine
Las Vegas, Nevada, United States

Co-Author(s)

EK

Euiseong Ko, n/a

PhD Student, Department of Computer Science
University of Nevada, Las Vegas
Las Vegas, Nevada, United States
JY

Ji Won Yoo, MD

Associate Professor of Medicine
Kirk Kerkorian School of Medicine at UNLV
Las Vegas, Nevada, United States
SL

Se-Won Lee, MD

Program Director, Physical Medicine & Rehabilitation Residency
Sunrise Health GME Consortium, HCA Healthcare
Las Vegas, Nevada, United States
JS

Jay Shen, PhD

Associate Dean, Department of Healthcare Administration & Policy
UNLV School of Public Health
Las Vegas, Nevada, United States

Corresponding Author(s)

SL

Soohyoung (Rain) Lee, PhD

Assistant Professor, Wurzweiler School of Social Work
Yeshiva University
New York, New York, United States
MK

Mingon Kang, PhD

Associate Professor, Department of Computer Science
University of Nevada, Las Vegas
Las Vegas, Nevada, United States

Submitter(s)

LS

Lois Y. Suh, N/A

Kirk Kerkorian School of Medicine
Las Vegas, Nevada, United States

Objectives: The opioid epidemic remains a major U.S. public health crisis, disproportionately affecting racial and ethnic minority populations. While much research has centered on White populations, Hispanic/Latino, Black/African American, and other minority groups are less well described. Regional differences, state policies, and systemic inequities further shape misuse and access to treatment, including in the Western United States.

Our objective was to examine disparities in opioid misuse among minority populations and identify state- and region-specific patterns in the Western U.S. (AZ, CA, CO, NV, UT). We also considered how emerging tools such as artificial intelligence (AI) could support future detection and intervention strategies.

Design: We analyzed HCUP-NIS inpatient data from 2017–2019, with years varying by state, to assess opioid-related hospitalizations across demographics, race/ethnicity, and urbanization; cases were defined using DRG codes: 917, 918, 922, 924. Variables examined included age, gender, income, and others, though only selected factors were emphasized. Literature on AI methods, including predictive modeling and natural language processing, was reviewed to explore their potential role in addressing disparities.

Results: Minority populations in the Western U.S. demonstrated higher proportions of opioid-related hospitalizations compared with White populations. Overdose ratios varied by state and urbanization level, with Black patients showing the most pronounced differences between metropolitan and smaller communities among minority groups. Analysis by substance type revealed distinct cannabis-related overdose patterns that differed across states and levels of urbanization.

Conclusions: Opioid misuse in the Western U.S. is shaped by the intersection of race, ethnicity, geography, and socioeconomic factors. HCUP-NIS data underscored disparities while also providing greater detail on overdose patterns across states and urbanization, particularly among non-White populations. These findings emphasize the need for region-specific, equity-focused strategies. Future work should examine how AI methods, applied with safeguards against bias, can enhance detection and guide interventions.