SynthesisJournal of the American Medical Informatics Association : JAMIA2024
Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain.
Synthesis in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
22 citing papers in PubMed, 4 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
- Alert fatigue measurement in clinical decision support: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2026Pooled it
- Effects of Real-Time Automated Clinical Deterioration Alert and Trigger Systems on Clinical Outcomes in Adult General Ward Patients: A Systematic Review and Meta-Analysis.Critical care medicine · 2026Pooled it
- Factors underpinning the performance of implemented artificial intelligence-based patient deterioration prediction systems: reasons for selection and implications for hospitals and researchers.Journal of the American Medical Informatics Association : JAMIA · 2025Pooled it
- A Health Informatics System in the South Australian Public Health Network: Implementation Report.JMIR medical informatics · 2026Article
- Determining a Clinically Applicable Cutoff in AI Algorithms for Predicting Clinical Deterioration: A Workload-Constrained, Alarm-Based Approach.Journal of clinical medicine · 2026Article
- Implementation of an AI-Based Clinical Decision Support System Predicting In-Hospital Cardiac Arrest in General Wards: A Multicenter Staggered-Implementation Study in Secondary Hospitals in Korea.Diagnostics (Basel, Switzerland) · 2026Article
- Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026Review
- Advancing Psychiatric Safety With the Predictive Risk Identification for Mental Health Events Tool: Retrospective Cohort Study.JMIR mental health · 2026Article
- A novel, standardised approach to balancing effectiveness, efficiency and utility of surveillance AI prediction models for hospitalised patients using sepsis prediction as an exemplar.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- WHF Roadmap for Integrated Care in People Living with - or at Risk of - Cardiovascular Disease and Multiple Long-Term Conditions.Global heart · 2026Review
- 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
- Implementation of Passive Deterioration Index Alerts in an Intermediate Care Unit: A Failed Early Warning System Strategy.Applied clinical informatics · 2025Article
- Prediction cardiovascular deterioration in a paediatric intensive care unit (PicEWS): a machine learning modelling study of routinely collected health-care data.EClinicalMedicine · 2025Article
- Challenges for implementing generative artificial intelligence (GenAI) into clinical healthcare.Internal medicine journal · 2025Review
- Comparison of Multimodal Deep Learning Approaches for Predicting Clinical Deterioration in Ward Patients: Observational Cohort Study.Journal of medical Internet research · 2025Observational
- BOBM: an adaptive deep learning framework for extended-window sepsis prediction with cross-institutional generalizability.Frontiers in medicine · 2025Article
- Clinical evaluation of a machine learning-based early warning system for patient deterioration.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2024Article
- Clinician perspectives and recommendations regarding design of clinical prediction models for deteriorating patients in acute care.BMC medical informatics and decision making · 2024Article
- Prioritising deteriorating patients using time-to-event analysis: prediction model development and internal-external validation.Critical care (London, England) · 2024Article
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.
Funding
Abstract
objectiveTo identify factors influencing implementation of machine learning algorithms (MLAs) that predict clinical deterioration in hospitalized adult patients and relate these to a validated implementation framework. MATERIALS AND
methodsA systematic review of studies of implemented or trialed real-time clinical deterioration prediction MLAs was undertaken, which identified: how MLA implementation was measured; impact of MLAs on clinical processes and patient outcomes; and barriers, enablers and uncertainties within the implementation process. Review findings were then mapped to the SALIENT end-to-end implementation framework to identify the implementation stages at which these factors applied.
resultsThirty-seven articles relating to 14 groups of MLAs were identified, each trialing or implementing a bespoke algorithm. One hundred and seven distinct implementation evaluation metrics were identified. Four groups reported decreased hospital mortality, 1 significantly. We identified 24 barriers, 40 enablers, and 14 uncertainties and mapped these to the 5 stages of the SALIENT implementation framework. DISCUSSION: Algorithm performance across implementation stages decreased between in silico and trial stages. Silent plus pilot trial inclusion was associated with decreased mortality, as was the use of logistic regression algorithms that used less than 39 variables. Mitigation of alert fatigue via alert suppression and threshold configuration was commonly employed across groups.
conclusions: There is evidence that real-world implementation of clinical deterioration prediction MLAs may improve clinical outcomes. Various factors identified as influencing success or failure of implementation can be mapped to different stages of implementation, thereby providing useful and practical guidance for implementers.
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What 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.