Eastwood, Cathy A.Khair, ShahreenSouthern, Danielle A.2022-06-122022-06-122022-06-07BMC Medical Informatics and Decision Making. 2022 Jun 07;21(Suppl 6):380http://hdl.handle.net/1880/114722https://doi.org/10.11575/PRISM/44443Abstract Accurate data collection of healthcare-related adverse events provides a foundation for quality and health system improvement. The International Classification of Diseases for Mortality and Morbidity Statistics, 11th revision (ICD-11 MMS) includes new codes to identify harm or injury and the events or actions leading to the adverse events. However, it is difficult to choose the correct codes without in-depth understanding of which event may be classified as an injury or harm. A 3-part model will be available in the ICD-11 MMS to cluster the codes for the harm or injury that occurred, the causal factors, and the mode (mechanism) involved. While field testing coding of adverse events, our team developed a decision tree (algorithm), which guides when to use the 3-part model. The decision tree now resides in the ICD-11 Reference Guide. This paper is part of a special ICD-11 paper series and outlines the steps used in the decision-tree (algorithm) and provides examples to help understand the process. While it may take coders some time to gain experience to use the 3-part model and decision-tree, the ICD-11 Reference Guide and this paper can be helpful resources to help clarify the process.Journal Article2022-06-12enThe Author(s)https://doi.org/10.1186/s12911-022-01887-6