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

Stud Health Technol Inform. 2019 Aug 21;264:1604-1605. doi: 10.3233/SHTI190556.

Abstract

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 %.

Keywords: International Classification of Diseases; Medical coding; Systematized Nomenclature of Medicine.

MeSH terms

  • Humans
  • International Classification of Diseases
  • Sepsis*
  • Systematized Nomenclature of Medicine*