The attitude of anesthesia assistants towards Artificial Intelligence-assisted patient monitoring in the Operating Room

Abstract

Research on the possibilities to use Artificial Intelligence (AI) at the Operating Room (OR) is rising, although there is no implementation yet. AI-assisted monitoring could provide support to anesthesia assistants in their task of patient monitoring, by making predictions on the future occurrence of deviating events in the vital parameter values of the patient. As AI-assisted monitoring would come close the profession of anesthesia assistants, this explorative, qualitative research investigates the attitude of anesthesia assistants towards the use of AI in their task of patient monitoring. Furthermore, it investigates the motivational factors that are important for their motivation in their monitoring task as well as the expected impact of AI on their motivation. This design-based research subsequently describes how these results are incorporated into the development of an educational module about AI and motivation for anesthesia assistants. Gaining as well as giving insight in the motivation of anesthesia assistants is important, as their motivation is of impact on their professional behaviour while their decisions and actions are directly related to the safety of the patient.

Through literature research and semi-structured interviews, it was found that among anesthesia assistants there is little knowledge on the possibilities of AI at the OR, but that their attitude towards AI-assisted monitoring is positive as long as only suggestions are given. Only two out of eight anesthesia assistants are cautiously positive towards the possibility of AI to automate the monitoring process. Furthermore, it was found that the motivational factors of autonomy, relatedness, competence, self-efficacy, and self-actualisation are all important to very important in the motivation of anesthesia assistants. Overall, none of these factors stands out in being most or least important. The expected impact of AI on these motivational factors among anesthesia assistants varies from negative to positive and is highly dependent on the form of AI-assisted monitoring. As various forms of interrelatedness between all these motivational factors are identified by the anesthesia assistants, specific to their working practice and environment, the impact on one motivational factor might indirectly also impact others.

These results on attitude and motivation are incorporated in the design of an educational module for anesthesia assistants. The module consists of two parts. One part regarding AI-assisted monitoring and one part regarding the motivational factors that are important for their motivation and the impact of AI on motivation. Design requirements by the anesthesia assistants, as well as an expert validation by an anesthesia educator, are used to finalise the design of the module. This module can help anesthesia assistants to develop awareness and understanding of how AI-assisted monitoring, in the form of giving suggestions, can support them in their patient monitoring task. Furthermore, it helps them to develop awareness and understanding on their own motivation and the impact that the use of AI-assisted monitoring may have on their motivation, guiding them towards becoming deliberate professionals.