Hwang Ji Eun, Park Hyeoun-Ae, Shin Soo-Yong
Department of Digital Health, SAIHST, Sungkyunkwan University, Seoul, Korea.
Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon, Korea.
Healthc Inform Res. 2021 Oct;27(4):287-297. doi: 10.4258/hir.2021.27.4.287. Epub 2021 Oct 31.
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.
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.
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.
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.
临床数据与患者生成的健康数据(PGHD,在医院外部生成)的整合受到越来越多的重视。本研究探讨了使用标准术语来表示PGHD以进行数据整合的可能性。
我们选择了韩国健康筛查计划2020年的一般健康检查问卷作为资源。我们将问卷的每个组成部分分为实体和值,并将其映射到标准术语——2020年7月31日版的医学临床术语系统命名法(SNOMED CT)和2.68版的逻辑观察标识符名称和代码(LOINC)。
从2020年健康检查问卷的17个问题中得出了89个项目,其中76个(85.4%)被映射到标准术语。52个项目被映射到SNOMED CT,24个项目被映射到LOINC。在映射到SNOMED CT的项目中,35个被映射到先组式表达,17个被映射到后组式表达。40个项目具有一对一关系,17个项目具有一对多关系。
通过使用SNOMED CT和LOINC,我们实现了较高的映射率(85.4%)。然而,在映射韩国一般健康检查问卷时我们注意到了一些问题(即缺乏解释、问题模糊和概念过于狭窄)。特别是,将两个或更多概念合并为一个项目的项目不适合使用标准术语进行映射。虽然并非所有项目都需要用标准术语表达,但未来应通过修订问卷,以适合映射到标准术语的方式呈现基本项目。