ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2019
Leveraging Clinical Expertise as a Feature - not an Outcome - of Predictive Models: Evaluation of an Early Warning System Use Case.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 19 citations in OpenAlex.
- Applications of the Early Warning Score as an outcome measure: a systematic review of methodologies.BMJ health & care informatics · 2026Pooled it
- Development and validation of early warning score system: A systematic literature review.Journal of biomedical informatics · 2020Pooled it
- Article
- Enhancing prediction of inpatient deterioration by combining clinical and nurse concern features, with or without temporal clustering.JAMIA open · 2026Article
- Conceptual framework for prediction models of patient deterioration based on nursing documentation patterns: reproducibility and generalizability with a large number of hospitals across the United States.Journal of biomedical informatics · 2025Article
- Reimagining clinical AI: from clickstreams to clinical insights with EHR use metadata.npj health systems · 2025Review
- Multisite Pragmatic Cluster-Randomized Controlled Trial of the CONCERN Early Warning System.medRxiv : the preprint server for health sciences · 2024Article
- Article
- Exploratory analysis of novel electronic health record variables for quantification of healthcare delivery strain, prediction of mortality, and prediction of imminent discharge.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- The Communicating Narrative Concerns Entered by Registered Nurses (CONCERN) Clinical Decision Support Early Warning System: Protocol for a Cluster Randomized Pragmatic Clinical Trial.JMIR research protocols · 2021Article
- Real-time electronic health record mortality prediction during the COVID-19 pandemic: a prospective cohort study.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Identifying nursing documentation patterns associated with patient deterioration and recovery from deterioration in critical and acute care settings.International journal of medical informatics · 2021Article
- 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
- Transforming clinical data into wisdom: Artificial intelligence implications for nurse leaders.Nursing management · 2020Article
- Nursing Surveillance from Invisible to Measurable to Indispensable: The CONCERN Early Warning System Trial.Nursing economic$Article
- Empirical Findings on the Role of Structured Data, Unstructured Data, and their Combination for Automatic Clinical Phenotyping.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational ScienceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 5 institutions in 1 country.
Funding
Abstract
Identifying patients at risk of deterioration in the hospital and intervening more quickly to prevent adverse events is a top patient safety priority. Early warning scores (EWS) identify at risk patients, but there is much opportunity for improvement particularly related to increasing lead time - the time from an alert trigger to adverse event (e.g., cardiac arrest, death). Our team develops healthcare process models of clinical concern (HPM-CC) and in this work has identified documentation signals that are proxies of nurses concern and can be used to predict patient risk earlier than current EWS systems that rely only on physiological data. We compared the performance of a validated EWS - the MEWS - to our novel model (MEWS-CC) comprised of MEWS criteria plus 3 proxy variables of nursing concern. MEWS-CC performed similarly to MEWS, with the added benefit of increased the time from EWS trigger to event by 5-26 hours.
Indexed as
Identifiers
32308825PMC7153052W3027121256What OpenQuestion holds
Registered trials
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.