Evidence-Based Framework for Identifying Opioid Use Disorder in Administrative Data: A Systematic Review and Methodological Development Study

Citation

Hurley RW, Bland KT, Chaskes MD, Guth D, Hill EL, Adams MCB. Evidence-based framework for identifying opioid use disorder in administrative data: A systematic review and methodological development study. Pain Med. 2026 Feb 1;27(2):145-159. doi: 10.1093/pm/pnaf116. PMID: 40854117; PMCID: PMC12865102.

Article Type

Systematic Review and Methodological Development

Topic Area

Opioid Use and Misuse; Health Services Research; Implementation Science

Population

Administrative claims and electronic health record data; systematic review of published OUD identification algorithms

Summary

Accurate identification of opioid use disorder (OUD) in administrative datasets is essential for epidemiologic research, health services evaluation, and policy analysis, yet no consensus exists on the optimal approach. This systematic review and methodological development study synthesized existing algorithms for identifying OUD in administrative claims and electronic health record data. The authors cataloged the ICD diagnosis codes, procedure codes, and medication indicators used across published studies to define OUD cases in administrative databases. The review revealed substantial heterogeneity in how OUD is operationalized across the research literature, with varying sensitivity and specificity depending on the codes and criteria employed. Based on the synthesis, the authors developed an evidence-based framework intended to standardize OUD identification for research purposes. This framework has direct implications for health services research examining opioid prescribing patterns, treatment access, and overdose outcomes, as inconsistent case definitions can bias study findings and limit comparability across studies. Standardized identification methods are particularly important for Medicaid and Medicare claims analyses where OUD prevalence and treatment access are active areas of policy research.

Background

Administrative data, including insurance claims and EHR-derived billing records, are widely used to study OUD epidemiology, treatment utilization, and outcomes. However, the definition of OUD in these datasets varies widely across studies, leading to inconsistent estimates of disease burden and treatment effectiveness.

Methods

A systematic review was conducted to identify published studies that used administrative data to identify OUD cases. The authors extracted and categorized the specific diagnosis codes, medication codes, and algorithmic criteria used in each study. An evidence-based framework was developed based on the synthesis of these approaches.

Key Findings

The review found substantial heterogeneity in OUD identification methods across the literature. Differences in code sets, inclusion and exclusion criteria, and lookback periods produced meaningfully different case populations. The proposed framework provides a standardized, evidence-based approach for OUD identification that can improve consistency and comparability across studies.

Implications for Practice and Policy

Standardized OUD identification in administrative data supports more reliable surveillance, outcomes research, and policy evaluation. Health systems, payers, and government agencies conducting OUD-related analyses should consider adopting validated, standardized coding frameworks to ensure consistency.

Keywords

opioid use disorder, administrative data, case identification, systematic review, ICD codes, health informatics, health services research, claims data, opioid misuse, epidemiology