Interpreting and coding causal relationships for quality and safety using ICD-11.


Journal

BMC medical informatics and decision making
ISSN: 1472-6947
Titre abrégé: BMC Med Inform Decis Mak
Pays: England
ID NLM: 101088682

Informations de publication

Date de publication:
16 Nov 2023
Historique:
received: 06 04 2021
accepted: 02 11 2023
medline: 20 11 2023
pubmed: 17 11 2023
entrez: 17 11 2023
Statut: epublish

Résumé

Many circumstances necessitate judgments regarding causation in health information systems, but these can be tricky in medicine and epidemiology. 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 "connecting terms," 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.

Identifiants

pubmed: 37974148
doi: 10.1186/s12911-023-02363-5
pii: 10.1186/s12911-023-02363-5
pmc: PMC10655490
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

385

Subventions

Organisme : Agence Nationale de la Recherche
ID : ANR-19-P3IA-0003

Informations de copyright

© 2023. The Author(s).

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Auteurs

Jean-Marie Januel (JM)

Department of Biomedical Informatics, Rouen University Hospital, 37 Boulevard Gambetta, Rouen, 76000, France. jean-marie.januel@hotmail.com.
Translational Innovation in Medicine and Complexity (TIMC) Laboratory, Deep Care research chair, Multidisciplinary Institute in Artificial Intelligence, Université Grenoble Alpes (UGA) and Centre National de Recherche Scientifique (CNRS), Grenoble, France. jean-marie.januel@hotmail.com.

Danielle A Southern (DA)

Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Canada.

William A Ghali (WA)

Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Canada.
Department of Medicine, University of Calgary, Calgary, Canada.

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