Increasing patient complexity, staffing shortages, and administrative burdens have intensified nurses' workloads, contributing to burnout and reduced job satisfaction. These challenges were particularly evident in the intensive care units (ICU) during the COVID-19 outbreak. With the growing healthcare demand in front of us, it is essential to understand and manage perceived workload effectively to maintain high-quality care and promote staff well-being. A real-time overview of nursing workload may facilitate the identification of patients requiring additional support and enable more effective distribution of workload among nurses during shifts. A dashboard has therefore been developed for use in the ICU to provide an overview of the patients at the unit and their corresponding nursing workload. To assess whether this dashboard is fit for purpose, this study aims to evaluate nurses' perspectives on its implementation, focusing on acceptance, adoptability, appropriateness, and fidelity. Additionally, the model for the calculation of the nursing workload will be assessed in terms of its alignment with ICU nurses' perceived workload and its potential for automation with artificial intelligence (AI).
Study Type
OBSERVATIONAL
Enrollment
60
Implementation outcomes acceptance, adoptability, appropriateness and fidelity
The mean scores and standard deviations of the 5-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = undecided, 4 = agree, 5 = strongly agree) closed-ended questions of the survey on the nurses' perspectives will be calculated.
Time frame: 1 and 3 months after implementation
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