Evaluating Quality of Care and Patient Safety with ICD-11: Opportunities for the French National Health Data System (SNDS).

Fiche publication

Date publication

mars 2026

Journal

Journal of epidemiology and population health

Auteurs

Membres identifiés du Cancéropôle Est :
Pr QUANTIN Catherine

Tous les auteurs :
Boussat B, Boyer L, Quantin C, Southern DA, Ghali WA, Guéant S, Danjou F, Mokaddem Y, Mercier G, Duclos A,

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/41880979

Résumé

Administrative health databases are widely used to evaluate healthcare quality and patient safety at the population level. In France, the French National Health Data System (SNDS) integrates hospital discharge data coded using the 10th revision of the International Classification of Diseases (ICD-10), enabling large-scale analyses of care pathways, outcomes, and health system performance. The transition to the 11th revision of the International Classification of Diseases (ICD-11) introduces structural and digital features that may modify how routinely collected data can be analyzed for quality and safety purposes. This article describes how selected characteristics of ICD-11 could influence the use of SNDS for evaluating quality of care and patient safety. Four dimensions are examined: clinical representation through postcoordination and extension codes; the three-part model for describing healthcare-related adverse events; coding of diagnosis timing in relation to hospital admission and procedures; and risk adjustment using comorbidities, severity, and sequelae. For each dimension, practical coding examples are used to illustrate potential analytical implications for population-based indicators. The analysis suggests that ICD-11 enables more explicit representation of clinical context, healthcare-related events, and temporal information within administrative data. These features may support more precise construction and interpretation of quality and safety indicators derived from the SNDS. The extent to which these possibilities translate into measurable improvements will depend on implementation conditions, including coding practices, training, and the integration of ICD-11 into existing information systems and analytical frameworks.