Name
Title | ||
|---|---|---|
Using SNOMED-CT to Help the Transition from Microbiological Data to ICD-10 Sepsis Codes. |
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%. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3233/SHTI190556 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
Medical coding,International Classification of Diseases,Systematized Nomenclature of Medicine | Radiology,Sepsis,SNOMED CT,Medicine,ICD-10 | Conference |
Volume | ISSN | Citations |
264 | 0926-9630 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Iris Ternois | 1 | 0 | 0.34 |
| Typhaine Billard-Pomares | 2 | 0 | 0.34 |
| Etienne Carbonelle | 3 | 0 | 0.34 |
| Loriane Franchinard | 4 | 0 | 0.34 |
| Catherine Duclos | 5 | 87 | 15.08 |