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In this article, we reflect on what the ICD-11 Reference Guide provides on coding for causation and judging when relationships between clinical concepts are causal. Based on the use of different types of codes and the development of a new mechanism for coding potential causal relationships, the ICD-11 provides an in-depth transformation of coding expectations as compared to ICD-10. An essential part of the causal relationship interpretation relies on the presence of \u201cconnecting terms,\u201d key elements in assessing the level of certainty regarding a potential relationship and how to proceed in coding a causal relationship using the new ICD-11 coding convention of postcoordination (i.e., clustering of codes). In addition, determining causation involves using documentation from healthcare providers, which is the foundation for coding health information. The coding guidelines and examples (taken from the quality and patient safety domain) presented in this article underline how new ICD-11 features and coding rules will enhance future health information systems and healthcare.<\/jats:p>","DOI":"10.1186\/s12911-023-02363-5","type":"journal-article","created":{"date-parts":[[2023,11,16]],"date-time":"2023-11-16T14:01:38Z","timestamp":1700143298000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Interpreting and coding causal relationships for quality and safety using ICD-11"],"prefix":"10.1186","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5857-6553","authenticated-orcid":false,"given":"Jean-Marie","family":"Januel","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Danielle A.","family":"Southern","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"William A.","family":"Ghali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,16]]},"reference":[{"issue":"10","key":"2363_CR1","doi-asserted-by":"publisher","first-page":"e0223129","DOI":"10.1371\/journal.pone.0223129","volume":"14","author":"A Parolini","year":"2019","unstructured":"Parolini A, Tan WW, Shlonsky A. Decision-based models of the implementation of interventions in systems of healthcare: Implementation outcomes and intervention effectiveness in complex service environments. PLoS ONE. 2019;14(10):e0223129. https:\/\/doi.org\/10.1371\/journal.pone.0223129.","journal-title":"PLoS ONE"},{"issue":"10\u201311","key":"2363_CR2","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1177\/0962280218799540","volume":"28","author":"G Cafri","year":"2019","unstructured":"Cafri G, Wang W, Chan PH, Austin PC. A review and empirical comparison of causal inference methods for clustered observational data with application to the evaluation of the effectiveness of medical devices. 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