Evidence map›Paper›PMID 31429750›Full record

ArticleBMC medical informatics and decision making2019

Clinical MetaData ontology: a simple classification scheme for data elements of clinical data based on semantics.

Hye Hyeon Kim, Yu Rang Park, Kye Hwa Lee, Young Soo Song, Ju Han Kim

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Understanding the Nature of Metadata: Systematic Review.Journal of medical Internet research · 2022
    Pooled it
  2. Trends in Clinical Information Systems Research in 2019.Yearbook of medical informatics · 2020
    Pooled it
  3. Article
  4. Article
  5. Article
  6. COVID term: a bilingual terminology for COVID-19.BMC medical informatics and decision making · 2021
    Article
  7. 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

5 authors.

Hye Hyeon KimSeoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
Yu Rang ParkDepartment of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea.
Kye Hwa LeePrecision Medicine Center, Seoul National University Hospital, Seoul, 03080, Republic of Korea.
Young Soo SongDepartment of Pathology, Hanyang University College of Medicine, Seoul, 04763, Republic of Korea. lifen@hanyang.ac.kr.
Ju Han KimSeoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul, 03080, Republic of Korea. juhan@snu.ac.kr.ORCID 0000-0003-1522-9038

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe increasing use of common data elements (CDEs) in numerous research projects and clinical applications has made it imperative to create an effective classification scheme for the efficient management of these data elements. We applied high-level integrative modeling of entire clinical documents from real-world practice to create the Clinical MetaData Ontology (CMDO) for the appropriate classification and integration of CDEs that are in practical use in current clinical documents.

methodsCMDO was developed using the General Formal Ontology method with a manual iterative process comprising five steps: (1) defining the scope of CMDO by conceptualizing its first-level terms based on an analysis of clinical-practice procedures, (2) identifying CMDO concepts for representing clinical data of general CDEs by examining how and what clinical data are generated with flows of clinical care practices, (3) assigning hierarchical relationships for CMDO concepts, (4) developing CMDO properties (e.g., synonyms, preferred terms, and definitions) for each CMDO concept, and (5) evaluating the utility of CMDO.

resultsWe created CMDO comprising 189 concepts under the 4 first-level classes of Description, Event, Finding, and Procedure. CMDO has 256 definitions that cover the 189 CMDO concepts, with 459 synonyms for 139 (74.0%) of the concepts. All of the CDEs extracted from 6 HL7 templates, 25 clinical documents of 5 teaching hospitals, and 1 personal health record specification were successfully annotated by 41 (21.9%), 89 (47.6%), and 13 (7.0%) of the CMDO concepts, respectively. We created a CMDO Browser to facilitate navigation of the CMDO concept hierarchy and a CMDO-enabled CDE Browser for displaying the relationships between CMDO concepts and the CDEs extracted from the clinical documents that are used in current practice.

conclusionsCMDO is an ontology and classification scheme for CDEs used in clinical documents. Given the increasing use of CDEs in many studies and real-world clinical documentation, CMDO will be a useful tool for integrating numerous CDEs from different research projects and clinical documents. The CMDO Browser and CMDO-enabled CDE Browser make it easy to search, share, and reuse CDEs, and also effectively integrate and manage CDEs from different studies and clinical documents.

Indexed as

Common Data ElementsMetadataSemanticsHumansResearch DesignSoftwareClassificationCommon data elementISO/IEC 11179Ontology

Identifiers

PMID31429750
PMCPMC6701018

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.