ArticleInternational journal of medical informatics2020
Identifying nurses' concern concepts about patient deterioration using a standard nursing terminology.
Article in International journal of medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 23 citations in OpenAlex.
- Mapping ICU nursing intervention notes to clinical care classification using a large language model: an evaluation study.BMC nursing · 2026Article
- Automated Identification of Nursing Diagnoses and Interventions From Nursing Records Using a Retrieval-Augmented Large Language Model Approach: Quantitative Study.Journal of medical Internet research · 2026Article
- Use of clinical care classification terminology in the nursing field: A scoping review.International journal of nursing studies advances · 2025Review
- Indicators of clinical deterioration in adult general ward patients from nurses' perspectives: a mixed-methods systematic review.BMC nursing · 2024Article
- Examining the Generalizability of Pretrained De-identification Transformer Models on Narrative Nursing Notes.Applied clinical informatics · 2024Article
- Diagnostic concordance among nursing clinical decision support system users: a pilot study.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Factors Influencing Clinician Trust in Predictive Clinical Decision Support Systems for In-Hospital Deterioration: Qualitative Descriptive Study.JMIR human factors · 2022Article
- Healthcare Process Modeling to Phenotype Clinician Behaviors for Exploiting the Signal Gain of Clinical Expertise (HPM-ExpertSignals): Development and evaluation of a conceptual framework.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Detecting Language Associated With Home Healthcare Patient's Risk for Hospitalization and Emergency Department Visit.Nursing researchArticle
Corrections and comments
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Authors and funding
13 authors at 5 institutions in 1 country.
Funding
Abstract
objectivesNurse concerns documented in nursing notes are important predictors of patient risk of deterioration. Using a standard nursing terminology and inputs from subject-matter experts (SMEs), we aimed to identify and define nurse concern concepts and terms about patient deterioration, which can be used to support subsequent automated tasks, such as natural language processing and risk predication.
methodsGroup consensus meetings with nurse SMEs were held to identify nursing concerns by grading Clinical Care Classification (CCC) system concepts based on clinical knowledge. Next, a fundamental lexicon was built placing selected CCC concepts into a framework of entities and seed terms to extend CCC granularity.
resultsA total of 29 CCC concepts were selected as reflecting nurse concerns. From these, 111 entities and 586 seed terms were generated into a fundamental lexicon. Nursing concern concepts differed across settings (intensive care units versus non-intensive care units) and unit types (medicine versus surgery units).
conclusionsThe CCC concepts were useful for representing nursing concern as they encompass a nursing-centric conceptual framework and are practical in lexicon construction. It enabled the codification of nursing concerns for deteriorating patients at a standardized conceptual level. The boundary of selected CCC concepts and lexicons were determined by the SMEs. The fundamental lexicon offers more granular terms that can be identified and processed in an automated fashion.
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