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Fatigue-recovery simulation model to analyze the impact of nursing activities on fatigue level in an intensive care unit
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[EMBARGOED UNTIL 6/1/2023] Although nursing is physically and mentally strenuous, not many studies have been done yet to find the impact of the key groups of tasks on nurses' average fatigue level and workflow. So, this study aims to understand the relationships among the key activities that impact the nurses' average fatigue level in an Intensive Care Unit (ICU). Nurses' time-study and real-time location data have been used to develop a simulation model in two different periods: February to March 2020 and July 2020. Two Hierarchical Task Analysis charts were generated from the collected data, one for each period, and used as the foundation for the fatigue-recovery simulation model. Both simulation models have been statistically tested and validated by comparing the time study observation data. Different scenarios of all nursing activities' frequencies (number of conducted tasks during a shift) and task sequences (number of times tasks are conducted continuously prior to a break) were simulated as independent variables. The dependent variable is their impacts on the nurses' predicted average fatigue levels during a shift. The main contribution of this work is that the model could provide a new way to estimate the nurses' fatigue levels in different workload conditions and to establish specific nursepatient ratios dynamically to improve patient care in a medical ICU. In this study, it was found that the major drivers for nurses' fatigue in an ICU shift is the number of times nurses conduct tasks in sequence without a break (number of task sequences), followed by the number of patient care or procedures, and peer support activities conducted in shift. However, the limitations in this study are the lack of the ratio number of nurses/number of patients during the shifts, the number of patients assigned to the assessed nurses, and regarding to the fatigue and recovery indexes. In this study, it is assumed three levels for the indexes, low, medium, and high, depending on the nature of the activity. It is recommended that, for the sake of more accurate results, in future studies, fatigue is monitored by a real-time method, in that way, there will be an estimated fatigue and/or recovery index for every single nurse task.
Title: Fatigue-recovery simulation model to analyze the impact of nursing activities on fatigue level in an intensive care unit
Description:
[EMBARGOED UNTIL 6/1/2023] Although nursing is physically and mentally strenuous, not many studies have been done yet to find the impact of the key groups of tasks on nurses' average fatigue level and workflow.
So, this study aims to understand the relationships among the key activities that impact the nurses' average fatigue level in an Intensive Care Unit (ICU).
Nurses' time-study and real-time location data have been used to develop a simulation model in two different periods: February to March 2020 and July 2020.
Two Hierarchical Task Analysis charts were generated from the collected data, one for each period, and used as the foundation for the fatigue-recovery simulation model.
Both simulation models have been statistically tested and validated by comparing the time study observation data.
Different scenarios of all nursing activities' frequencies (number of conducted tasks during a shift) and task sequences (number of times tasks are conducted continuously prior to a break) were simulated as independent variables.
The dependent variable is their impacts on the nurses' predicted average fatigue levels during a shift.
The main contribution of this work is that the model could provide a new way to estimate the nurses' fatigue levels in different workload conditions and to establish specific nursepatient ratios dynamically to improve patient care in a medical ICU.
In this study, it was found that the major drivers for nurses' fatigue in an ICU shift is the number of times nurses conduct tasks in sequence without a break (number of task sequences), followed by the number of patient care or procedures, and peer support activities conducted in shift.
However, the limitations in this study are the lack of the ratio number of nurses/number of patients during the shifts, the number of patients assigned to the assessed nurses, and regarding to the fatigue and recovery indexes.
In this study, it is assumed three levels for the indexes, low, medium, and high, depending on the nature of the activity.
It is recommended that, for the sake of more accurate results, in future studies, fatigue is monitored by a real-time method, in that way, there will be an estimated fatigue and/or recovery index for every single nurse task.
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