Defining Cannabis Use Disorder in Administrative Health Data: A Systematic Review of Case Definitions and Validation Approaches

Abstract

Introduction:

Reliable case definitions (CDs) for cannabis use disorder (CUD) are essential for epidemiologic surveillance, health services research, and policy evaluation. As reliance on health administrative data increases, variation in diagnostic coding practices and limited validation of CDs may undermine the comparability and accuracy of CUD estimates. This systematic review aimed to identify, describe, and critically appraise how CUD has been operationalized within administrative health data sources, with particular attention to coding strategies and validation practices.

Methods:

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we systematically searched PubMed, EMBASE, and related databases for studies using International Classification of Diseases (ICD) codes to define CUD in administrative health data. Two reviewers independently screened studies, extracted data on CD components and validation methods, and assessed methodological quality using the Newcastle–Ottawa Scale.

Results:

A total of 56 studies met the inclusion criteria. Most relied on ICD-9 or ICD-10 diagnostic codes to identify CUD, typically using a one-or-more-code rule, although operational details varied by jurisdiction, coding framework, and observation window. No included study explicitly reported internal or external validation of its CD. Reported prevalence estimates ranged widely, from 0.06% in large administrative cohorts to 76.9% in highly selected clinical populations, reflecting differences in CD construction and study populations.

Conclusions:

CDs for CUD in administrative data vary substantially and lack empirical validation, limiting their reliability for surveillance and comparative research. The development and validation of standardized, transparent CDs are needed to strengthen cannabis epidemiology and to support reproducible research, health-system planning, and policy decision-making.