Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies
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 to represent PGHD for data integration. Methods We chose the 2...
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| Format: | Article |
| Language: | English |
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The Korean Society of Medical Informatics
2021-10-01
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| Series: | Healthcare Informatics Research |
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| Online Access: | http://e-hir.org/upload/pdf/hir-2021-27-4-287.pdf |
| _version_ | 1819282799752904704 |
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| author | Ji Eun Hwang Hyeoun-Ae Park Soo-Yong Shin |
| author_facet | Ji Eun Hwang Hyeoun-Ae Park Soo-Yong Shin |
| author_sort | Ji Eun Hwang |
| collection | DOAJ |
| description | 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 to represent PGHD for data integration. Methods We chose the 2020 general health checkup questionnaire of the Korean Health Screening Program as a resource. We divided every component of the questionnaire into entities and values, which were mapped to standard terminologies—Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) version 2020-07-31 and Logical Observation Identifiers Names and Codes (LOINC) version 2.68. Results Eighty-nine items were derived from the 17 questions of the 2020 health examination questionnaire, of which 76 (85.4%) were mapped to standard terms. Fifty-two items were mapped to SNOMED CT and 24 items were mapped to LOINC. Among the items mapped to SNOMED CT, 35 were mapped to pre-coordinated expressions and 17 to post-coordinated expressions. Forty items had one-to-one relationships, and 17 items had one-to-many relationships. Conclusions We achieved a high mapping rate (85.4%) by using both SNOMED CT and LOINC. However, we noticed some issues while mapping the Korean general health checkup questionnaire (i.e., lack of explanations, vague questions, and overly narrow concepts). In particular, items combining two or more concepts into a single item were not appropriate for mapping using standard terminologies. Although it is not the case that all items need to be expressed in standard terminology, essential items should be presented in a way suitable for mapping to standard terminology by revising the questionnaire in the future. |
| first_indexed | 2024-12-24T01:21:20Z |
| format | Article |
| id | doaj.art-0b70db69a57f48e7ac86d095ff3098e0 |
| institution | Directory Open Access Journal |
| issn | 2093-3681 2093-369X |
| language | English |
| last_indexed | 2024-12-24T01:21:20Z |
| publishDate | 2021-10-01 |
| publisher | The Korean Society of Medical Informatics |
| record_format | Article |
| series | Healthcare Informatics Research |
| spelling | doaj.art-0b70db69a57f48e7ac86d095ff3098e02022-12-21T17:22:38ZengThe Korean Society of Medical InformaticsHealthcare Informatics Research2093-36812093-369X2021-10-0127428729710.4258/hir.2021.27.4.2871089Mapping the Korean National Health Checkup Questionnaire to Standard TerminologiesJi Eun Hwang0Hyeoun-Ae Park1Soo-Yong Shin2 Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea College of Nursing, Seoul National University, Seoul, Korea Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, KoreaObjectives 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 to represent PGHD for data integration. Methods We chose the 2020 general health checkup questionnaire of the Korean Health Screening Program as a resource. We divided every component of the questionnaire into entities and values, which were mapped to standard terminologies—Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) version 2020-07-31 and Logical Observation Identifiers Names and Codes (LOINC) version 2.68. Results Eighty-nine items were derived from the 17 questions of the 2020 health examination questionnaire, of which 76 (85.4%) were mapped to standard terms. Fifty-two items were mapped to SNOMED CT and 24 items were mapped to LOINC. Among the items mapped to SNOMED CT, 35 were mapped to pre-coordinated expressions and 17 to post-coordinated expressions. Forty items had one-to-one relationships, and 17 items had one-to-many relationships. Conclusions We achieved a high mapping rate (85.4%) by using both SNOMED CT and LOINC. However, we noticed some issues while mapping the Korean general health checkup questionnaire (i.e., lack of explanations, vague questions, and overly narrow concepts). In particular, items combining two or more concepts into a single item were not appropriate for mapping using standard terminologies. Although it is not the case that all items need to be expressed in standard terminology, essential items should be presented in a way suitable for mapping to standard terminology by revising the questionnaire in the future.http://e-hir.org/upload/pdf/hir-2021-27-4-287.pdfstandardspatient generated health datasurveys and questionnairessystematized nomenclature of medicine clinical terms (snomed ct)logical observation identifiers names and codes (loinc) |
| spellingShingle | Ji Eun Hwang Hyeoun-Ae Park Soo-Yong Shin Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies Healthcare Informatics Research standards patient generated health data surveys and questionnaires systematized nomenclature of medicine clinical terms (snomed ct) logical observation identifiers names and codes (loinc) |
| title | Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies |
| title_full | Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies |
| title_fullStr | Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies |
| title_full_unstemmed | Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies |
| title_short | Mapping the Korean National Health Checkup Questionnaire to Standard Terminologies |
| title_sort | mapping the korean national health checkup questionnaire to standard terminologies |
| topic | standards patient generated health data surveys and questionnaires systematized nomenclature of medicine clinical terms (snomed ct) logical observation identifiers names and codes (loinc) |
| url | http://e-hir.org/upload/pdf/hir-2021-27-4-287.pdf |
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