Evidence map›Paper›PMID 37071456›Full record

ArticleJMIR medical informatics2023

A SNOMED CT Mapping Guideline for the Local Terms Used to Document Clinical Findings and Procedures in Electronic Medical Records in South Korea: Methodological Study.

Sumi Sung, Hyeoun-Ae Park, Hyesil Jung, Hannah Kang

Abstract read
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Article in JMIR medical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sumi SungBiomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-3897-4698
Hyeoun-Ae ParkCollege of Nursing, Seoul National University, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-3770-4998
Hyesil JungDepartment of Nursing, Inha University, Incheon, Republic of Korea.ORCID https://orcid.org/0000-0002-8346-9343
Hannah KangKakao Healthcare Corp, Seongnam-si, Gyeonggi-do, Republic of Korea.ORCID https://orcid.org/0000-0001-6567-6894

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSouth Korea joined SNOMED International as the 39th member country. To ensure semantic interoperability, South Korea introduced SNOMED CT (Systemized Nomenclature of Medicine-Clinical Terms) in 2020. However, there is no methodology to map local Korean terms to SNOMED CT. Instead, this is performed sporadically and independently at each local medical institution. The quality of the mapping, therefore, cannot be guaranteed.

objectiveThis study aimed to develop and introduce a guideline to map local Korean terms to the SNOMED CT used to document clinical findings and procedures in electronic health records at health care institutions in South Korea.

methodsThe guidelines were developed from December 2020 to December 2022. An extensive literature review was conducted. The overall structures and contents of the guidelines with diverse use cases were developed by referencing the existing SNOMED CT mapping guidelines, previous studies related to SNOMED CT mapping, and the experiences of the committee members. The developed guidelines were validated by a guideline review panel.

resultsThe SNOMED CT mapping guidelines developed in this study recommended the following 9 steps: define the purpose and scope of the map, extract terms, preprocess source terms, preprocess source terms using clinical context, select a search term, use search strategies to find SNOMED CT concepts using a browser, classify mapping correlations, validate the map, and build the final map format.

conclusionsThe guidelines developed in this study can support the standardized mapping of local Korean terms into SNOMED CT. Mapping specialists can use this guideline to improve the mapping quality performed at individual local medical institutions.

Indexed as

guidelinehealth terminteroperabilityinteroperablelocal termsmappingmapping guidelinemedical termnomenclatureontologiessemantic interoperabilitySNOMEDSystematized Nomenclature of Medicine–Clinical Termsterminologiesterminology

Identifiers

PMID37071456
PMCPMC10155087

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.