ArticleJMIR medical informatics2019
Common Data Elements for Acute Coronary Syndrome: Analysis Based on the Unified Medical Language System.
Article in JMIR medical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Medical researchers' perception of sharing of metadata from case report forms.Learning health systems · 2025Article
- Europe's Largest Research Infrastructure for Curated Medical Data Models with Semantic Annotations.Methods of information in medicine · 2024Article
- Recording of Social Determinants in Computerized Medical Records in Primary Care Consultations: Quasi-Experimental Study.JMIR formative research · 2023Article
- ELaPro, a LOINC-mapped core dataset for top laboratory procedures of eligibility screening for clinical trials.BMC medical research methodology · 2022Article
- Common Data Elements for Meaningful Stroke Documentation in Routine Care and Clinical Research: Retrospective Data Analysis.JMIR medical informatics · 2021Article
- Pragmatic MDR: a metadata repository with bottom-up standardization of medical metadata through reuse.BMC medical informatics and decision making · 2021Article
- Automated Identification of Common Disease-Specific Outcomes for Comparative Effectiveness Research Using ClinicalTrials.gov: Algorithm Development and Validation Study.JMIR medical informatics · 2021Article
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Authors and funding
5 authors.
Funding
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Abstract
backgroundStandardization in clinical documentation can increase efficiency and can save time and resources.
objectiveThe objectives of this work are to compare documentation forms for acute coronary syndrome (ACS), check for standardization, and generate a list of the most common data elements using semantic form annotation with the Unified Medical Language System (UMLS).
methodsForms from registries, studies, risk scores, quality assurance, official guidelines, and routine documentation from four hospitals in Germany were semantically annotated using UMLS. This allowed for automatic comparison of concept frequencies and the generation of a list of the most common concepts.
resultsA total of 3710 forms items from 86 sources were semantically annotated using 842 unique UMLS concepts. Half of all medical concept occurrences were covered by 60 unique concepts, which suggests the existence of a core dataset of relevant concepts. Overlap percentages between forms were relatively low, hinting at inconsistent documentation structures and lack of standardization.
conclusionsThis analysis shows a lack of standardized and semantically enriched documentation for patients with ACS. Efforts made by official institutions like the European Society for Cardiology have not yet been fully implemented. Utilizing a standardized and annotated core dataset of the most important data concepts could make export and automatic reuse of data easier. The generated list of common data elements is an exemplary implementation suggestion of the concepts to use in a standardized approach.
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