ArticleJournal of the American Medical Informatics Association : JAMIA2020
Formal representation of patients' care context data: the path to improving the electronic health record.
Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Supporting clinical reasoning through visual summarization and presentation of patient data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- Identifying false-positive drug allergy alerts based on drug tolerance assertions: a retrospective study.JAMIA open · 2026Article
- Applications of Natural Language Processing in Otolaryngology: A Scoping Review.The Laryngoscope · 2025Article
- How do Clinicians Use Electronic Health Records for Respiratory Support Decisions? A Qualitative Study in Critical Care.ACI open · 2025Article
- A Visualization Method of Knowledge Graphs for the Computation and Comprehension of Ultrasound Reports.Biomimetics (Basel, Switzerland) · 2023Article
- Semantically oriented EHR navigation with a patient specific knowledge base and a clinical context ontology.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- Knowledge Representation and Management: Interest in New Solutions for Ontology Curation.Yearbook of medical informatics · 2021Review
- Capturing Clinician Reasoning in Electronic Health Records: An Exploratory Study of Under-Treated Essential Hypertension.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
- The anatomy of clinical documentation: an assessment and classification of narrative note sections format and content.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop a collection of concept-relationship-concept tuples to formally represent patients' care context data to inform electronic health record (EHR) development. MATERIALS AND
methodsWe reviewed semantic relationships reported in the literature and developed a manual annotation schema. We used the initial schema to annotate sentences extracted from narrative note sections of cardiology, urology, and ear, nose, and throat (ENT) notes. We audio recorded ENT visits and annotated their parsed transcripts. We combined the results of each annotation into a consolidated set of concept-relationship-concept tuples. We then compared the tuples used within and across the multiple data sources.
resultsWe annotated a total of 626 sentences. Starting with 8 relationships from the literature, we annotated 182 sentences from 8 inpatient consult notes (initial set of tuples = 43). Next, we annotated 232 sentences from 10 outpatient visit notes (enhanced set of tuples = 75). Then, we annotated 212 sentences from transcripts of 5 outpatient visits (final set of tuples = 82). The tuples from the visit transcripts covered 103 (74%) concepts documented in the notes of their respective visits. There were 20 (24%) tuples used across all data sources, 10 (12%) used only in inpatient notes, 15 (18%) used only in visit notes, and 7 (9%) used only in the visit transcripts.
conclusionsWe produced a robust set of 82 tuples useful to represent patients' care context data. We propose several applications of our tuples to improve EHR navigation, data entry, learning health systems, and decision support.
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