Novel ways to analyse and cope alert-fatigue phenomenon in intensive care units

In Intensive Care Units (ICUs), patient monitoring relies on many devices configured to trigger alarms when specific physiological parameters surpass pre-established thresholds, including metrics like heart rate and oxygen saturation. Nevertheless, these alerts are susceptible to fallibility and frequently contribute to a common issue called “alert fatigue,” wherein healthcare practitioners become desensitized to the alarms due to their frequent occurrence, often with questionable accuracy. This research introduces an innovative model to mitigate the alert fatigue phenomenon in ICUs by diminishing the overall requirement for medical interventions. The model is developed following the system dynamics (SD) methodology framework. The initial phase of the study encompasses the development of a current-state model, which, when implemented, was validated by medical and nursing professionals in the ICU. The subsequent phase involves a simulated implementation of our novel model, resulting in a reduction in the total number of interventions, thereby, based on the common assumption, reducing the alert fatigue phenomenon. This simulated SD model lays the groundwork for the prospective design of Internet of Medical Things (IoMT) systems, which are poised to contribute significantly to mitigate alert fatigue and enhance patient safety.

Duke Scholars

Author Arriel Benis Biomedical Engineering