- Southern, Danielle A;
- Pincus, Harold A;
- Romano, Patrick S;
- Burnand, Bernard;
- Harrison, James;
- Forster, Alan J;
- Moskal, Lori;
- Quan, Hude;
- Droesler, Saskia E;
- Sundararajan, Vijaya;
- Colin, Cyrille;
- Gurevich, Yana;
- Brien, Susan E;
- Kostanjsek, Nenad;
- üstün, Bedirhan;
- Ghali, William A;
- Ghali, William;
- Pincus, Harold;
- Allen, Marilyn;
- Brien, Susan;
- Drösler, Saskia;
- Forster, Alan;
- Harrison, James E;
- Munier, William;
- Pickett, Donna;
- Romano, Patrick;
- Spaeth-Rublee, Brigitta;
- Southern, Danielle;
- Van der Zwaag, David;
- Chute, Christopher;
- Hogan, Eileen;
- Cox, Ginger
The World Health Organization (WHO) plans to submit the 11th revision of the International Classification of Diseases (ICD) to the World Health Assembly in 2018. The WHO is working toward a revised classification system that has an enhanced ability to capture health concepts in a manner that reflects current scientific evidence and that is compatible with contemporary information systems. In this paper, we present recommendations made to the WHO by the ICD revision's Quality and Safety Topic Advisory Group (Q&S TAG) for a new conceptual approach to capturing healthcare-related harms and injuries in ICD-coded data. The Q&S TAG has grouped causes of healthcare-related harm and injuries into four categories that relate to the source of the event: (a) medications and substances, (b) procedures, (c) devices and (d) other aspects of care. Under the proposed multiple coding approach, one of these sources of harm must be coded as part of a cluster of three codes to depict, respectively, a healthcare activity as a 'source' of harm, a 'mode or mechanism' of harm and a consequence of the event summarized by these codes (i.e. injury or harm). Use of this framework depends on the implementation of a new and potentially powerful code-clustering mechanism in ICD-11. This new framework for coding healthcare-related harm has great potential to improve the clinical detail of adverse event descriptions, and the overall quality of coded health data.