Trends and disparities in cannabis use disorder-coded inpatient discharges across 18 U.S. states, 2005–2023

Abstract

Objective Prior studies document rising cannabis use disorder (CUD) prevalence and disparities, but less is known about trends in CUD-coded inpatient discharges across populations and intersecting sociodemographic groups. We examined trends and variation in CUD-coded inpatient discharges by sociodemographic characteristics. Study design Repeated administrative dataset analysis of inpatient discharge records. Methods We analyzed 216,203,471 inpatient discharges from community hospitals in 18 U S. states (2005–2023). Logistic regression with non-linear (cubic) time trends and prespecified two-way interactions across age, sex, race/ethnicity, insurance, and state estimated the probability of CUD coding in any diagnosis position. We derived population-weighted predicted prevalence, prevalence ratios, and average marginal effect risk ratios. Secondary analyses restricted outcomes to principal diagnoses and excluded “cannabis use, unspecified” codes. Results The proportion of discharges with CUD coding increased from 1.02% in 2005 to 3.15% in 2023, with substantial and persistent disparities. In 2023, prevalence was higher among males (4.19%) than females (2.32%), highest among adolescents (10–19 years: 9.33%), and higher among non-Hispanic Black patients (5.43%). Compared with private insurance, government and other insurance were associated with a higher prevalence. State-level prevalence varied markedly (New Mexico: 4.39%; South Carolina: 1.89%), indicating geographic heterogeneity. Time-varying changes were most pronounced by age and race/ethnicity. Estimates were lower when restricted to principal diagnoses. Conclusions CUD-coded inpatient discharges increased substantially over time, with persistent sociodemographic and geographic disparities. These findings highlight the importance of screening and linkage-to-care efforts for disproportionately affected groups and of using consistent diagnosis-position definitions in surveillance.