The Impact of AI on Nursing Workload and Stress Levels in Critical Care Settings

Abstract

AI has the potential to revolutionize the healthcare system, particularly in the intensive care unit, by streamlining processes and improving patient outcomes. This study investigates the impact of AI tools, such as clinical decision support systems and electronic health records with AI capabilities, on nursing workload and stress levels in intensive care units (ICUs). A cross-sectional survey design was employed, utilizing a questionnaire to gather data from a sample of 150 ICU nurses. Quantitative analysis, including descriptive statistics and inferential tests, examined the relationship between AI implementation, workload perception, and stress levels, aiming to answer the following questions: Does AI implementation affect nurses' perceived workload in ICUs? Does AI implementation influence nurses' stress levels in ICUs? Preliminary findings suggest that AI implementation is associated with both positive and negative effects on nursing workload. While AI tools streamline certain tasks, such as data collection and documentation, they may introduce new challenges and demands, potentially contributing to increased stress levels. Additionally, the study explores the nuances of AI integration in critical care, including nurses' perceptions of AI, its perceived benefits and drawbacks, and the need for adequate training and support. Thus, this research expands the knowledge base on AI in healthcare and provides valuable insights for health sector policymakers. Understanding the complex interplay between AI, nursing workload, and stress is crucial for optimizing the use of AI in critical care settings, informing policies for successful AI integration, and ensuring the well-being of healthcare professionals.