Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies
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Objectives: An increasing emphasis has been placed on the integration of clinical data and patient-generated health data(PGHD), which are generated outside of hospitals. This study explored the possibility of using standard terminologies torepresent PGHD for data integration. Methods: We chose the 2020 general health checkup questionnaire of the KoreanHealth Screening Program as a resource. We divided every component of the questionnaire into entities and values, whichwere mapped to standard terminologies—Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) version2020-07-31 and Logical Observation Identifiers Names and Codes (LOINC) version 2.68. Results: Eighty-nine items werederived from the 17 questions of the 2020 health examination questionnaire, of which 76 (85.4%) were mapped to standardterms. Fifty-two items were mapped to SNOMED CT and 24 items were mapped to LOINC. Among the items mapped toSNOMED CT, 35 were mapped to pre-coordinated expressions and 17 to post-coordinated expressions. Forty items had oneto-one relationships, and 17 items had one-to-many relationships. Conclusions: We achieved a high mapping rate (85.4%) byusing both SNOMED CT and LOINC. However, we noticed some issues while mapping the Korean general health checkupquestionnaire (i.e., lack of explanations, vague questions, and overly narrow concepts). In particular, items combining two ormore concepts into a single item were not appropriate for mapping using standard terminologies. Although it is not the casethat all items need to be expressed in standard terminology, essential items should be presented in a way suitable for mappingto standard terminology by revising the questionnaire in the future.
Abstract
Objectives: An increasing emphasis has been placed on the integration of clinical data and patient-generated health data(PGHD), which are generated outside of hospitals. This study explored the possibility of using standard terminologies torepresent PGHD for data integration. Methods: We chose the 2020 general health checkup questionnaire of the KoreanHealth Screening Program as a resource. We divided every component of the questionnaire into entities and values, whichwere mapped to standard terminologies—Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) version2020-07-31 and Logical Observation Identifiers Names and Codes (LOINC) version 2.68. Results: Eighty-nine items werederived from the 17 questions of the 2020 health examination questionnaire, of which 76 (85.4%) were mapped to standardterms. Fifty-two items were mapped to SNOMED CT and 24 items were mapped to LOINC. Among the items mapped toSNOMED CT, 35 were mapped to pre-coordinated expressions and 17 to post-coordinated expressions. Forty items had oneto-one relationships, and 17 items had one-to-many relationships. Conclusions: We achieved a high mapping rate (85.4%) byusing both SNOMED CT and LOINC. However, we noticed some issues while mapping the Korean general health checkupquestionnaire (i.e., lack of explanations, vague questions, and overly narrow concepts). In particular, items combining two ormore concepts into a single item were not appropriate for mapping using standard terminologies. Although it is not the casethat all items need to be expressed in standard terminology, essential items should be presented in a way suitable for mappingto standard terminology by revising the questionnaire in the future.
참고문헌 (28)
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