Using SNOMED-CT to Help the Transition from Microbiological Data to ICD-10 Sepsis Codes.

Iris Ternois (1) , Typhaine Billard-Pomares (2) , Etienne Carbonelle (2) , Loriane Franchinard (3) , Catherine Duclos (1, 2)

1 LIMICS - Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé
2 Hôpital Avicenne [AP-HP]
3 CHU Trousseau [APHP]

Assigning ICD-10 code of sepsis in regard of a pathogenic bacterium found in an haemoculture requires knowledge of microbiology because of the difference of granularity. The aim of this paper is to automate this coding thanks to the use of SNOMED-CT. A dichotomous classification of bacteria causing sepsis has been generated in respect of ICD-10. Our algorithm follows this and explores SNOMED-CT to assign the right ICD-10 code of the sepsis. Applied to a list of 164 bacteria, the system has an error rate of 1.22 %.

Mots clés: International Classification of Diseases; Medical coding; Systematized Nomenclature of Medicine

Domaines: Informatique et langage [cs.CL]; Santé publique et épidémiologie

Iris Ternois, Typhaine Billard-Pomares, Etienne Carbonelle, Loriane Franchinard, Catherine Duclos. Using SNOMED-CT to Help the Transition from Microbiological Data to ICD-10 Sepsis Codes.. Studies in Health Technology and Informatics, 2019, 264, pp.1604-1605. ⟨10.3233/SHTI190556⟩. ⟨hal-03479359⟩