Proposed Algorithm with Standard Terminologies (SNOMED and CPT) for Automated Generation of Medical Bills for Laboratory Tests.
10.4258/hir.2010.16.3.185
- Author:
Shine Young KIM
1
;
Hyung Hoi KIM
;
In Keun LEE
;
Hwa Sun KIM
;
Hune CHO
Author Information
1. Department of Laboratory Medicine and Biomedical Informatics, College of Medicine, Pusan National University, Busan, Korea.
- Publication Type:Original Article
- Keywords:
Logical Observation Identifiers Names and Codes;
Systematized Nomenclature of Medicine;
Current Procedural Terminology;
Health Insurance
- MeSH:
Current Procedural Terminology;
Insurance, Health;
Logic;
Logical Observation Identifiers Names and Codes;
Systematized Nomenclature of Medicine;
Translating
- From:Healthcare Informatics Research
2010;16(3):185-190
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVES: In this study, we proposed an algorithm for mapping standard terminologies for the automated generation of medical bills. As the Korean and American structures of health insurance claim codes for laboratory tests are similar, we used Current Procedural Terminology (CPT) instead of the Korean health insurance code set due to the advantages of mapping in the English language. METHODS: 1,149 CPT codes for laboratory tests were chosen for study. Each CPT code was divided into two parts, a Logical Observation Identifi ers Names and Codes (LOINC) matched part (matching part) and an unmatched part (unmatched part). The matching parts were assigned to LOINC axes. An ontology set was designed to express the unmatched parts, and a mapping strategy with Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) was also proposed. Through the proceeding analysis, an algorithm for mapping CPT with SNOMED CT arranged by LOINC was developed. RESULTS: 75% of the 1,149 CPT codes could be assigned to LOINC codes. Two hundred and twenty-five CPT codes had only one component part of LOINC, whereas others had more than two parts of LOINC. The system of LOINC axes was found in 309 CPT codes, scale 555, property 9, method 42, and time aspect 4. From the unmatched parts, three classes, 'types', 'objects', and 'subjects', were determined. By determining the relationship between the classes with several properties, all unmatched parts could be described. Since the 'subject to' class was strongly connected to the six axes of LOINC, links between the matching parts and unmatched parts were made. CONCLUSIONS: The proposed method may be useful for translating CPT into concept-oriented terminology, facilitating the automated generation of medical bills, and could be adapted for the Korean health insurance claim code set.
