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Journal of Medical Systems

Erschienen in:

01.12.2023 | Original Paper

Alert-Grouping: Smart Personalization of Monitoring System Thresholds to Help Healthcare Teams Struggle with Alarm Fatigue in Intensive Care

verfasst von: Shai Rozenes, Adi Fux, Ilya Kagan, Moran Hellerman, Boaz Tadmor, Arriel Benis

Erschienen in: Journal of Medical Systems | Ausgabe 1/2023

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Abstract

In Intensive Care Units (ICUs), patients are monitored using various devices that generate alerts when specific metrics, such as heart rate and oxygen saturation, exceed predetermined thresholds. However, these alerts can be inaccurate and lead to alert fatigue, resulting in errors and inaccurate diagnoses. We propose Alert grouping, a “Smart Personalization of Monitoring System Thresholds to Help Healthcare Teams Struggle Alarm Fatigue in Intensive Care” model. The alert grouping looks at patients at the individual and cluster levels, and healthcare-related constraints to assist medical and nursing teams in setting personalized alert thresholds of vital parameters. By simulating the function of ICU patient bed devices, we demonstrate that the proposed alert grouping model effectively reduces the number of alarms overall, improving the alert system’s validity and reducing alarm fatigue. Implementing this personalized alert model in ICUs boosts medical and nursing teams’ confidence in the alert system, leading to better care for ICU patients by significantly reducing alarm fatigue, thereby improving the quality of care for ICU patients.

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Titel: Alert-Grouping: Smart Personalization of Monitoring System Thresholds to Help Healthcare Teams Struggle with Alarm Fatigue in Intensive Care
verfasst von: Shai Rozenes
Adi Fux
Ilya Kagan
Moran Hellerman
Boaz Tadmor
Arriel Benis
Publikationsdatum: 01.12.2023
Verlag: Springer US
Erschienen in: Journal of Medical Systems / Ausgabe 1/2023
Print ISSN: 0148-5598
Elektronische ISSN: 1573-689X
DOI: https://doi.org/10.1007/s10916-023-02010-6

Springer Medizin

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