Background: Physiological monitoring systems, like Masimo, used during inpatient hospitalisation, offer a non-invasive approach to capture critical vital signs data. These systems trigger alarms when measurements deviate from preset parameters. However, often non-urgent or potentially false alarms contribute to 'alarm fatigue,' a form of sensory overload that can have adverse effects on both patients and healthcare staff. The Joint Commission, in 2021, announced a target to mitigate alarm fatigue-related fatalities through improved alarm management. Yet, no established guidelines are presently available. This study aims to address alarm fatigue at the Mayo Clinic to safeguard patient safety, curb staff burnout and improve the sensitivity of oxygen saturation monitoring to promptly detect emergencies.
Methods: A quality improvement project was conducted to combat minimise the false alarm burden, with data collected 2 months prior to intervention commencement. The project's goal was to decrease the total alarm value by 20% from 55%-85% to 35%-75% within 2 months, leveraging quality improvement methodologies.
Interventions: February to April 2021, we implemented a two-pronged intervention: (1) instituting a protocol to evaluate patients' continuous monitoring needs and discontinuing it when appropriate, and (2) introducing educational signage for patients and Mayo Clinic staff on monitoring best practices.
Results: Baseline averages of red alarms (158.6), manual snoozes (37.8) and self-resolves (120.7); the first postintervention phase showed reductions in red alarms (125.5), manual snoozes (17.8) and self-resolves (107.8). Second postintervention phase recorded 138 red alarms, 13 manual snoozes and 125 self-resolves. Baseline comparison demonstrated an average of 16.92% reduction of alarms among both interventions (p value: 0.25).
Conclusion: Simple interventions like education and communication techniques proved instrumental in lessening the alarm burden for patients and staff. The findings underscore the practical use and efficacy of these methods in any healthcare setting, thus contributing to mitigating the prevalent issue of alarm fatigue.
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http://dx.doi.org/10.1136/bmjoq-2023-002262 | DOI Listing |
Br J Anaesth
January 2025
Perioperative Outcomes and Informatics Collaborative, Winston-Salem, NC, USA; Outcomes Research Consortium, Houston, TX, USA; Department of Anesthesiology, Center of Anesthesiology and Intensive Care Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Most postoperative deaths occur on general wards, often linked to complications associated with untreated changes in vital signs. Monitoring in these units is typically intermittent checks each shift or maximally every 4-6 h, which misses prolonged periods of subtle changes in physiology that can herald a critical downstream event. Continuous monitoring of vital signs is therefore intuitively necessary for patient safety.
View Article and Find Full Text PDFJ Electrocardiol
December 2024
Emory University, Atlanta, GA, USA. Electronic address:
Over the past sixty years, telemetry monitoring has become integral to hospital care, offering critical insights into patient health by tracking key indicators like heart rate, respiratory rate, blood pressure, and oxygen saturation. Its primary application, continuous electrocardiographic (ECG) monitoring, is essential in diverse settings such as emergency departments, step-down units, general wards, and intensive care units for the early detection of cardiac rhythms signaling acute clinical deterioration. Recent advancements in data analytics and machine learning have expanded telemetry's role from observation to prognostication, enabling predictive models that forecast inhospital events indicative of patient instability.
View Article and Find Full Text PDFJ Med Internet Res
December 2024
Shanghai Engineering Research Center of Intelligence Pediatrics, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Background: Previous studies have shown that electrocardiographic (ECG) alarms have high sensitivity and low specificity, have underreported adverse events, and may cause neonatal intensive care unit (NICU) staff fatigue or alarm ignoring. Moreover, prolonged noise stimuli in hospitalized neonates can disrupt neonatal development.
Objective: The aim of the study is to conduct a nationwide, multicenter, large-sample cross-sectional survey to identify current practices and investigate the decision-making requirements of health care providers regarding ECG alarms.
Introduction: Frequent and long-term exposure to clinical alarms can cause emergency nurses to lose their trust in alarms, delay their response, and even disable or mute these alarms.
Methods: A cross-sectional study was conducted to assess emergency nurses' knowledge, perceptions, and practices toward clinical alarm fatigue and investigate the perceived obstacles they face when managing clinical alarms.
Results: Less than half of emergency nurses were unfamiliar with the term "alarm fatigue" (40.
Diagnostics (Basel)
December 2024
Research Center CHU Ste-Justine Centre Hospitalier Universitaire Mère-Enfant, 3175 Boulevard de la Côte-Sainte-Catherine Drive, Montréal, QC H3T 1C5, Canada.
Background/objectives: This study develops machine learning (ML) models to predict hypoxemia severity during emergency triage, particularly in Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) scenarios, using physiological data from medical-grade sensors.
Methods: Tree-based models (TBMs) such as XGBoost, LightGBM, CatBoost, Random Forests (RFs), Voting Classifier ensembles, and sequential models (LSTM, GRU) were trained on the MIMIC-III and IV datasets. A preprocessing pipeline addressed missing data, class imbalances, and synthetic data flagged with masks.
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