Mapping Different Versions of the International Classification of Diseases: A Scoping Review - Ahmed, Nasiba; Nouredanesh, Mina; Lix, Lisa; Hamad, Amani (International Journal of Population Data Science, 2026)
Introduction The International Classification of Diseases (ICD) is used to report medical diagnoses and procedures in most electronic health databases. Periodic revisions and region/country-specific adaptations reflect advances in medical knowledge and local needs. Therefore, health databases often include multiple ICD versions. Comprehensive and accurate mapping between different ICD versions and adaptations is necessary to facilitate research over time and across regions and populations. Objective This scoping review describes published literature about methods to map diagnosis codes between different versions or adaptations of the ICD system. Methods A systematic search across MEDLINE, EMBASE, Scopus and Web of Science Core Collection from inception until June 21, 2024, was performed. Primary research and review articles describing the mapping methods were included. Information was extracted on article characteristics, data characteristics (e.g., versions of ICD codes mapped), mapping methods, and measures to assess mapping quality. Study data were descriptively analysed using frequencies and percentages. Results Among 1359 articles identified from the search, 25 were included in the review; 13 (52%) articles were published between 2020 and 2023. Two-thirds of the articles used US electronic health databases. Mappings were most frequently (48%) created between ICD-9-CM (i.e., 9th revision, clinical modification) and ICD-10-CM (i.e., 10th revision, clinical modification). Mapping methods were mostly (88%) manual, relying primarily on expert review and existing resources to generate mappings and assess their quality. Only 36% of the articles implemented at least two or more strategies to mitigate loss of information due to mapping. Conclusion We identified several methods to map different ICD version, all methods relied on expert review to assess accuracy of the mappings. The application of automated approaches through the utilization of AI tools could represent an opportunity for future research.