Forensic mortality in northern Tunisia in 2023: a cross-sectional study comparing ICD-11 and ICD-10 coding
- Journal
- BMJ open (Q1)
- Published
- 22 September 2026
- Study design
- Cross-sectional study
- Evidence level
- Level 3, Low (CEBM 3b)
- Authors
- Ons Hmandi, Alaaeddine Marai, Mariem Zribi, Nada Zoghlami, Hajer Aounallah-Skhiri, Mohamed Allouche
- PMID
- 42772890
- DOI
- 10.1136/bmjopen-2026-121065
Why clinicians should know about it
- Picked for Pathology and Forensic Medicine (paper of the day, 23 September 2026): ICD‑11 vs ICD‑10 coding in forensic mortality
Abstract
OBJECTIVES: To classify causes of death in northern Tunisia in 2023 according to the International Classification of Diseases, 11th Revision (ICD-11) and ICD-10, and to compare the two classifications in a forensic context. DESIGN: Descriptive cross-sectional study of causes of death in a forensic setting in 2023. Demographic data and causes of death were retrospectively extracted and coded using ICD-11 and ICD-10, applying ICD-11 post-coordination where relevant. SETTING: A forensic medicine department in a university hospital in Tunis, Tunisia, accounting for eight northern governorates of Tunisia. PARTICIPANTS: All deaths examined or autopsied during 2023 were included. Cases involving aborted fetuses, stillbirths, exhumed remains with death occurring before 2023 and skeletal remains were excluded. RESULTS: A total of 2214 deaths were included, of whom 73.6% were male, with a mean age of 53.3 years. The most frequent ICD-11 chapters were External Causes (41.2%) and Diseases of the Circulatory System (32.8%). ICD-11 identified 216 unique underlying causes, compared with 219 using ICD-10. ICD-11 post-coordination was applied in 88.5% of cases, providing additional details for road traffic accidents, assaults and poisonings. Overall distributions were similar, but ICD-11 allowed a more specific coding of causes of death. CONCLUSIONS: ICD-11 enhances medicolegal mortality reporting by improving specificity, flexibility and the ability to capture multiple circumstances of death. Its adoption will strengthen national mortality statistics.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.