ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2011
Toward a two-tier clinical warning system for hospitalized patients.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 3 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
19 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Automated Features, Algorithms, and Technologies of Electronic Early Warning/Track-and-Trigger Systems: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain.Journal of the American Medical Informatics Association : JAMIA · 2024Pooled it
- Patient centred variables with univariate associations with unplanned ICU admission: a systematic review.BMC medical informatics and decision making · 2019Pooled it
- A randomized trial of real-time automated clinical deterioration alerts sent to a rapid response team.Journal of hospital medicine · 2014Trial
- Determining a Clinically Applicable Cutoff in AI Algorithms for Predicting Clinical Deterioration: A Workload-Constrained, Alarm-Based Approach.Journal of clinical medicine · 2026Article
- Digital health platforms for intrinsic capacity monitoring in community-based integrated care for older adults: a scoping review.Frontiers in public health · 2026Article
- Early Warning Systems for Critical Illness Outside the Intensive Care Unit.Critical care clinics · 2024Review
- Using Machine Learning to Predict Likelihood and Cause of Readmission After Hospitalization for Chronic Obstructive Pulmonary Disease Exacerbation.International journal of chronic obstructive pulmonary disease · 2022Article
- Predicting Patient Deterioration: A Review of Tools in the Digital Hospital Setting.Journal of medical Internet research · 2021Review
- Attitudes of Patients and Health Professionals Regarding Screening Algorithms: Qualitative Study.JMIR formative research · 2021Article
- The potential of artificial intelligence to improve patient safety: a scoping review.NPJ digital medicine · 2021Article
- Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock.Critical care medicine · 2019Observational
- A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice.Critical care medicine · 2019Article
- Article
- Implementation of an automated early warning scoring system in a surgical ward: Practical use and effects on patient outcomes.PloS one · 2019Article
- Article
- Real-time automated clinical deterioration alerts predict thirty-day hospital readmission.Journal of hospital medicine · 2016Article
- Multicenter development and validation of a risk stratification tool for ward patients.American journal of respiratory and critical care medicine · 2014Article
- Mortality and Length of Stay Trends Following Implementation of a Rapid Response System and Real-Time Automated Clinical Deterioration Alerts.American journal of medical quality : the official journal of the American College of Medical QualityArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Clinical study has found early detection and intervention to be essential for preventing clinical deterioration in patients at general hospital units. In this paper, we envision a two-tiered early warning system designed to identify the signs of clinical deterioration and provide early warning of serious clinical events. The first tier of the system automatically identifies patients at risk of clinical deterioration from existing electronic medical record databases. The second tier performs real-time clinical event detection based on real-time vital sign data collected from on-body wireless sensors attached to those high-risk patients. We employ machine-learning techniques to analyze data from both tiers, assigning scores to patients in real time. The assigned scores can then be used to trigger early-intervention alerts. Preliminary study of an early warning system component and a wireless clinical monitoring system component demonstrate the feasibility of this two-tiered approach.
Indexed as
Identifiers
22195105PMC3243239What 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.