ArticleJournal of the American Medical Informatics Association : JAMIA2025
Semi-automated pipeline to accelerate multi-site flowsheet alignment and concept mapping in electronic health records.
Article in Journal of the American Medical Informatics Association : JAMIA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Development and Validation of Human-AI Collaborative Workflow in SNOMED CT Mapping of Bilingual Clinical Text.Journal of medical systems · 2026Article
- Mapping ICU nursing intervention notes to clinical care classification using a large language model: an evaluation study.BMC nursing · 2026Article
- A neural-symbolic AI agent system for biomedical concept mapping.NPJ digital medicine · 2026Article
- Biomedical and health informatics Potpourri.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Mapping Documentation Burden: Analyzing Centrality and Clusters among Flowsheet Measures and Templates Through Network Analysis.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
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Authors and funding
6 authors.
Funding
Abstract
objectivesHealth-care institutions customize electronic health record (EHR) configurations to reflect their unique workflows and patient care priorities. Ensuring EHR alignment across sites facilitates seamless information exchange. We developed a pipeline for EHR flowsheet alignment between health-care organizations. The pipeline is augmented by mapping flowsheet data fields to concepts in the Clinical Care Classification (CCC) nursing terminology. MATERIALS AND
methodsFlowsheet templates and measures from 2 study sites were transformed into template-measure (T-M) pairs. They were aligned through exact, lexical, or semantic matching. Lexical matches were assessed using Jaccard similarity and fuzzy matching methods. Semantic alignment was determined using cosine similarity between large language model-generated embeddings of T-M pairs and CCC concepts to rank and recommend the top n concepts in CCC. Concept mappings were evaluated based on whether concepts were mapped consistently within the CCC hierarchy.
resultsWe totally aligned 31 255 unique T-M pairs in acute care units and 27 012 T-M pairs in intensive care units from 2 study sites. When restricted to the top-ranked CCC concept (n = 1), we achieved a 63% flowsheet alignment rate with a 53% concept mapping rate. Expanding to the top 3 concepts (n = 3) improved alignment to 96.5% and concept mapping to 96%. DISCUSSION AND
conclusionElectronic health record data field alignment with concept mapping offers opportunities to standardize data elements presented in flowsheets across health-care sites. We demonstrated the feasibility of leveraging a semi-automated pipeline to streamline the EHR flowsheet alignment and accelerate the manual concept mapping process.
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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.