Automation in perioperative medicine: perceptions, requirements and boundaries - a mixed methods study

Jeffrey David Iqbal1, Maximilian Lindholz1, Stefan J Schaller1

  • 1From the Faculty of Medicine, University of Zurich, Zurich, Switzerland (JDI, MS), Berlin Institute of Health at Charité (BIH), Berlin, Germany (ML), Charité - Universitätsmedizin Berlin, Institute of Medical Informatics, Berlin, Germany (SJS), University Hospital Zurich, Institute of Anesthesiology and Perioperative Medicine, Zurich, Switzerland (JDI, MS), Charité - Universitätsmedizin Berlin, Department of Anesthesiology and Intensive Care Medicine (CCM/CVK), Chariteplatz 1, Berlin, Germany (ML, SJS), Charité - Universitätsmedizin Berlin, Department of Radiology, Berlin, Germany (ML), Medical University of Vienna, Department of Anaesthesia, Intensive Care Medicine and Pain Medicine, Division of General Anaesthesia and Intensive Care Medicine, Vienna, Austria (SJS).

Summary

Artificial intelligence (AI) and automation in anaesthesia are welcomed by professionals for error reduction and improved care. However, full replacement of anaesthesiologists by machines is unlikely due to adoption barriers and required changes in roles.

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