ArticleJMIR research protocols2021
The Communicating Narrative Concerns Entered by Registered Nurses (CONCERN) Clinical Decision Support Early Warning System: Protocol for a Cluster Randomized Pragmatic Clinical Trial.
Article in JMIR research protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03911687 (Communicating Narrative Concerns Entered by RNs), which is not on this map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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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.
Communicating Narrative Concerns Entered by RNs (CONCERN) Clinical Decision Support (CDS) System
Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Automated Features, Algorithms, and Technologies of Electronic Early Warning/Track-and-Trigger Systems: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial.Nature medicine · 2025Trial
- Identifying Barriers to The Implementation of Communicating Narrative Concerns Entered by Registered Nurses, An Early Warning System SmartApp.Applied clinical informatics · 2024Trial
- Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Trial
- Reporting of Cohort and Routinely Collected Data in Randomised Controlled Trial Protocols (SPIRIT-ROUTINE): extension checklist with explanation and elaboration.BMJ (Clinical research ed.) · 2026Article
- Enhancing prediction of inpatient deterioration by combining clinical and nurse concern features, with or without temporal clustering.JAMIA open · 2026Article
- Exploring nurses' documentation prioritization strategies to alleviate EHR documentation burden: a phenomenological study.JAMIA open · 2026Article
- Innovative Technologies: Optimizing Nursing Practice.Computers, informatics, nursing : CIN · 2026Article
- Interdisciplinary systems may restore the healthcare professional-patient relationship in electronic health systems.Journal of the American Medical Informatics Association : JAMIA · 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
- Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice.European journal of cardiovascular nursing · 2025Article
- Designing and testing clinical simulations of an early warning system for implementation in acute care settings.JAMIA open · 2024Article
- Virtual Reality in Acute and Chronic Pain Medicine: An Updated Review.Current pain and headache reports · 2024Review
- The Role of Virtual Reality and Artificial Intelligence in Cognitive Pain Therapy: A Narrative Review.Current pain and headache reports · 2024Review
- Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions.PLOS digital health · 2024Article
- Advancing Data Science Competencies for Nursing PhD Students.Studies in health technology and informatics · 2024Article
- Multisite Pragmatic Cluster-Randomized Controlled Trial of the CONCERN Early Warning System.medRxiv : the preprint server for health sciences · 2024Article
- Exploring the Implementation Experience and Use of CONCERN Early Warning System in a Rural Community Hospital: A Mixed Method Convergent Approach.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Natural Language Processing Applied to Clinical Documentation in Post-acute Care Settings: A Scoping Review.Journal of the American Medical Directors Association · 2024Article
- Machine learning applied to electronic health record data in home healthcare: A scoping review.International journal of medical informatics · 2023Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
backgroundEvery year, hundreds of thousands of inpatients die from cardiac arrest and sepsis, which could be avoided if those patients' risk for deterioration were detected and timely interventions were initiated. Thus, a system is needed to convert real-time, raw patient data into consumable information that clinicians can utilize to identify patients at risk of deterioration and thus prevent mortality and improve patient health outcomes. The overarching goal of the COmmunicating Narrative Concerns Entered by Registered Nurses (CONCERN) study is to implement and evaluate an early warning score system that provides clinical decision support (CDS) in electronic health record systems. With a combination of machine learning and natural language processing, the CONCERN CDS utilizes nursing documentation patterns as indicators of nurses' increased surveillance to predict when patients are at the risk of clinical deterioration.
objectiveThe objective of this cluster randomized pragmatic clinical trial is to evaluate the effectiveness and usability of the CONCERN CDS system at 2 different study sites. The specific aim is to decrease hospitalized patients' negative health outcomes (in-hospital mortality, length of stay, cardiac arrest, unanticipated intensive care unit transfers, and 30-day hospital readmission rates).
methodsA multiple time-series intervention consisting of 3 phases will be performed through a 1-year period during the cluster randomized pragmatic clinical trial. Phase 1 evaluates the adoption of our algorithm through pilot and trial testing, phase 2 activates optimized versions of the CONCERN CDS based on experience from phase 1, and phase 3 will be a silent release mode where no CDS is viewable to the end user. The intervention deals with a series of processes from system release to evaluation. The system release includes CONCERN CDS implementation and user training. Then, a mixed methods approach will be used with end users to assess the system and clinician perspectives.
resultsData collection and analysis are expected to conclude by August 2022. Based on our previous work on CONCERN, we expect the system to have a positive impact on the mortality rate and length of stay.
conclusionsThe CONCERN CDS will increase team-based situational awareness and shared understanding of patients predicted to be at risk for clinical deterioration in need of intervention to prevent mortality and associated harm.
trial registrationClinicalTrials.gov NCT03911687; https://clinicaltrials.gov/ct2/show/NCT03911687. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/30238.
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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.