Incorporation of Korean Electronic Data Interchange Vocabulary into Observational Medical Outcomes Partnership Vocabulary
2
조회
0
다운로드
3
인용
0
참고문헌
키워드
초록
Objectives: We incorporated the Korean Electronic Data Interchange (EDI) vocabulary into Observational Medical OutcomesPartnership (OMOP) vocabulary using a semi-automated process. The goal of this study was to improve the KoreanEDI as a standard medical ontology in Korea. Methods: We incorporated the EDI vocabulary into OMOP vocabularythrough four main steps. First, we improved the current classification of EDI domains and separated medical services intoprocedures and measurements. Second, each EDI concept was assigned a unique identifier and validity dates. Third, we builta vertical hierarchy between EDI concepts, fully describing child concepts through relationships and attributes and linkingthem to parent terms. Finally, we added an English definition for each EDI concept. We translated the Korean definitions ofEDI concepts using Google.Cloud.Translation.V3, using a client library and manual translation. We evaluated the EDI using11 auditing criteria for controlled vocabularies. Results: We incorporated 313,431 concepts from the EDI to the OMOP StandardizedVocabularies. For 10 of the 11 auditing criteria, EDI showed a better quality index within the OMOP vocabularythan in the original EDI vocabulary. Conclusions: The incorporation of the EDI vocabulary into the OMOP StandardizedVocabularies allows better standardization to facilitate network research. Our research provides a promising model for mappingKorean medical information into a global standard terminology system, although a comprehensive mapping of officialvocabulary remains to be done in the future.
Abstract
Objectives: We incorporated the Korean Electronic Data Interchange (EDI) vocabulary into Observational Medical OutcomesPartnership (OMOP) vocabulary using a semi-automated process. The goal of this study was to improve the KoreanEDI as a standard medical ontology in Korea. Methods: We incorporated the EDI vocabulary into OMOP vocabularythrough four main steps. First, we improved the current classification of EDI domains and separated medical services intoprocedures and measurements. Second, each EDI concept was assigned a unique identifier and validity dates. Third, we builta vertical hierarchy between EDI concepts, fully describing child concepts through relationships and attributes and linkingthem to parent terms. Finally, we added an English definition for each EDI concept. We translated the Korean definitions ofEDI concepts using Google.Cloud.Translation.V3, using a client library and manual translation. We evaluated the EDI using11 auditing criteria for controlled vocabularies. Results: We incorporated 313,431 concepts from the EDI to the OMOP StandardizedVocabularies. For 10 of the 11 auditing criteria, EDI showed a better quality index within the OMOP vocabularythan in the original EDI vocabulary. Conclusions: The incorporation of the EDI vocabulary into the OMOP StandardizedVocabularies allows better standardization to facilitate network research. Our research provides a promising model for mappingKorean medical information into a global standard terminology system, although a comprehensive mapping of officialvocabulary remains to be done in the future.
참고문헌 (19)
- 박현애, "전자의무기록의 의미론적 상호운용성 확보에서 임상 용어체계의 역할", 대한의사협회지, 55(8), pp.720~728 (2012), 대한의사협회[DOI]
- "Healthcare Information Standard" (2017)[URL]
- Kim M, "A study on a comparison of diagnostic domain between SNOMED CT and Korea standard terminology of medicine", Int J Database Theory Appl, 9(11), pp.49~60 (2015)
- 정보경, "Report on the Project for Establishment of the Standardized Korean Laboratory Terminology Database, 2015", Journal of Korean Medical Science, 32(4), pp.695~699 (2017), 대한의학회
- Hwang EJ, "Mapping Korean EDI medical procedure code to SNOMED CT", Stud Health Technol Inform, 264, pp.178~182 (2019)
- Hripcsak G, "Observational Health Data Sciences and Informatics(OHDSI) : opportunities for observational researchers", Stud Health Technol Inform, 216, pp.574~578 (2015)
- Garza M, "Evaluating common data models for use with a longitudinal community registry", J Biomed Inform, 64, pp.333~341 (2016)
- Cimino JJ, "Desiderata for controlled medical vocabularies in the twenty-first century", Methods Inf Med, 37(4-5), pp.394~403 (1998)
- "EdiToOmop: the package to convert Korean EDI code to the OMOP vocabulary" (2020)[URL]
- Chute CG, "A framework for comprehensive health terminology systems in the United States: development guidelines, criteria for selection, and public policy implications. ANSI Healthcare Informatics Standards Board Vocabulary Working Group and the Computer-Based Patient Records Institute Working Group on Codes and Structures", J Am Med Inform Assoc, 5(6), pp.503~510 (1998)
- Rosenbloom ST, "Interface terminologies : facilitating direct entry of clinical data into electronic health record systems", J Am Med Inform Assoc, 13(3), pp.277~288 (2006)
- Lee KC, "A study on enhancing terminology & its major issues", pp.2012
- "ATHENA: OHDSI vocabularies repository" (2018)[URL]
- 이민호, "Implementation of Medical Information Exchange System Based on EHR Standard", Healthcare Informatics Research, 16(4), pp.281~289 (2010), 대한의료정보학회
- Tae Gon Kim, "Endovascular Treatments Performed Collaboratively by the Society of Korean Endovascular Neurosurgeons Members : A Nationwide Multicenter Survey", 대한신경외과학회지, 62(5), pp.502~518 (2019), 대한신경외과학회[DOI]
- You SC, "Rate control and clinical outcomes in patients with atrial fibrillation and obstructive lung disease", Heart Rhythm, 15(12), pp.1825~1832 (2018)
- Burn E, "Deep phenotyping of 34,128 patients hospitalised with COVID-19 and a comparison with 81,596 influenza patients in America", Europe and Asia:an international network study (2020)[DOI]
- "Korean OMOP Vocabulary" (2019)[URL]
- "OHDSI-Korea" (2019)[URL]
