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

Shai Rozenes, Adi Fux*, Ilya Kagan, Moran Hellerman, Boaz Tadmor, Arriel Benis*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number113
JournalJournal of Medical Systems
Volume47
Issue number1
DOIs
StatePublished - Dec 2023

Keywords

  • Alarm fatigue
  • Alert fatigue
  • Intensive care units
  • Patient safety
  • Personalized medicine
  • Quality of health care

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