A decade of cannabis-related hospital admissions in Victoria, Australia: A retrospective observational study.

Graham M.; Berecki-Gisolf J.; Hayman J.; Carter A.; Arunogiri S.; Nielsen S. · Addiction (Abingdon, England) · 2026

**Background & Methods** This retrospective observational study analyzed all hospital admissions in Victoria, Australia from July 2013 to June 2023 (10-year period) using the Victorian Admitted Episodes Dataset (VAED). Cannabis-related admissions were identified using ICD-10 diagnosis codes for poisoning (T40.7) and mental health/behavioural disorders (F12.0-F12.9), with crude and age-standardised rates per 100,000 population calculated using generalised linear models. **Key Findings** • Total of 39,565 cannabis-related hospital admissions occurred over the decade, with 7,263 admissions (18.4%) where cannabis-related harm was the principal diagnosis; age-standardised rate was 63.6 per 100,000 for all cannabis-related admissions and 11.7 per 100,000 for principal diagnosis cases. • Cannabis-related principal diagnosis admissions increased 49.0% when comparing 2022/2023 to baseline 2013/2014 (P<0.0001), with peak rates observed in 2020/2021 (77.3 per 100,000); psychotic disorder (F12.5) was the most common principal diagnosis (40.1%; n=2,909/7,263). • Highest admission rates occurred in males aged 15-24 years (36.9/100,000), followed by females in the same age group (20.5/100,000); females demonstrated a greater relative increase (+75.1%) compared to males (+34.6%) between study baseline and final year. **Dosage & Administration** Not reported. **Safety & Adverse Effects** Not reported. The study identified cannabis-related harms requiring hospitalization but did not specifically catalogue adverse effects or clinical presentations beyond diagnostic coding. **Evidence Quality** This is a population-based retrospective observational study with significant limitations: reliance on administrative hospital coding without validation of diagnoses, inability to assess cannabis potency/type/route of administration, potential underestimation of harm (only captures hospitalized cases), non-linear trends limiting causal inference, and lack of individual-level data on dosage or clinical severity. The non-linear pattern (peak in 2020/2021 followed by decline) suggests confounding factors not examined. Strengths include complete state-level data capture and large sample size, providing robust epidemiological trends but limited mechanistic understanding.

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