Evidence map›Paper›PMID 33611874›Full record

ArticleHealthcare informatics research2021

Incorporation of Korean Electronic Data Interchange Vocabulary into Observational Medical Outcomes Partnership Vocabulary.

Yeonchan Seong, Seng Chan You, Anna Ostropolets, Yeunsook Rho, Jimyung Park, Jaehyeong Cho, Dmitry Dymshyts, Christian G Reich, Yunjung Heo, Rae Woong Park

Abstract read
In one paragraph

Article in Healthcare informatics research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Patient Factors Associated with Different Hospice Programs in Korea: Analyzing Healthcare Big Data.International journal of environmental research and public health · 2022
    Article
  10. Article
  11. Factors of Hospitals Associated With an Independent Hospice Care Unit: A Quantitative Empirical Study.Journal of hospice and palliative nursing : JHPN : the official journal of the Hospice and Palliative Nurses Association · 2021
    Article
4 · The record

Corrections and comments

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

10 authors.

Yeonchan SeongDepartment of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
Seng Chan YouDepartment of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.
Anna OstropoletsDepartment of Biomedical Informatics, Columbia University, New York, NY, USA.
Yeunsook RhoHealth Insurance Review & Assessment Service, Wonju, Korea.
Jimyung ParkDeparment of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea.
Jaehyeong ChoDeparment of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea.
Dmitry DymshytsOdysseus Data Services Inc., Cambridge, MA, USA.
Christian G ReichReal Wolrd Solutions, IQVIA, Cambridge, MA, USA.
Yunjung HeoDepartment of Medical Humanities and Social Medicine, Ajou University School of Medicine, Suwon, Korea.
Rae Woong ParkDepartment of Biomedical Informatics, Ajou University School of Medicine, Suwon, Korea.

Funding

Health Insurance Review and Assessment Service
6 · The paper itself

Abstract

objectivesWe incorporated the Korean Electronic Data Interchange (EDI) vocabulary into Observational Medical Outcomes Partnership (OMOP) vocabulary using a semi-automated process. The goal of this study was to improve the Korean EDI as a standard medical ontology in Korea.

methodsWe incorporated the EDI vocabulary into OMOP vocabulary through four main steps. First, we improved the current classification of EDI domains and separated medical services into procedures and measurements. Second, each EDI concept was assigned a unique identifier and validity dates. Third, we built a vertical hierarchy between EDI concepts, fully describing child concepts through relationships and attributes and linking them to parent terms. Finally, we added an English definition for each EDI concept. We translated the Korean definitions of EDI concepts using Google.Cloud.Translation.V3, using a client library and manual translation. We evaluated the EDI using 11 auditing criteria for controlled vocabularies.

resultsWe incorporated 313,431 concepts from the EDI to the OMOP Standardized Vocabularies. For 10 of the 11 auditing criteria, EDI showed a better quality index within the OMOP vocabulary than in the original EDI vocabulary.

conclusionsThe incorporation of the EDI vocabulary into the OMOP Standardized Vocabularies allows better standardization to facilitate network research. Our research provides a promising model for mapping Korean medical information into a global standard terminology system, although a comprehensive mapping of official vocabulary remains to be done in the future.

Indexed as

Biological OntologiesControlled VocabularyKnowledge BasesMedical InformaticsNational Health Programs

Identifiers

PMID33611874
PMCPMC7921574

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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.