AI in the Preoperative Environment: Evaluating Trust and Reliability among Anesthesia Providers
Keywords:
Artificial Intelligence; Preoperative Anesthesia; Medication Optimization; Anesthesia Providers; Clinical Decision Support; Perioperative Care; Technology AdoptionAbstract
Background: Artificial intelligence (AI) is increasingly being explored in anesthesia to support clinical decision-making and enhance patient safety. However, limited data exist regarding anesthesia providers’ familiarity with AI and their perceptions of its role in preoperative care.
Objective: This study aimed to assess anesthesia providers’ familiarity with AI applications in preoperative care, perceptions of AI-assisted medication optimization, and willingness to adopt AI tools in clinical practice.
Methods: A cross-sectional survey was conducted using a structured questionnaire among 60 anesthesia providers. Data were analyzed descriptively to evaluate levels of familiarity, perceived usefulness, and acceptance of AI in preoperative anesthesia care.
Results: Most participants demonstrated moderate familiarity with AI applications in preoperative care. A majority perceived AI as a useful tool for medication optimization, and more than half expressed willingness to adopt AI-based systems in routine practice. Only a small proportion reported reluctance toward AI use.
Conclusion: Anesthesia providers showed moderate awareness and generally positive perceptions of AI in preoperative care, with favorable acceptance of AI-assisted medication optimization. These findings suggest growing readiness for AI integration in anesthesia practice, highlighting the need for structured education, clinical validation, and ethical implementation to support safe and effective adoption.
