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Breaking point or turning point? Harnessing artificial intelligence to combat burnout

2025·0 Zitationen·AnaesthesiaOpen Access
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2025

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Abstract

I read with interest the article by Gale et al. which identifies several factors that contribute to the high levels of stress and burnout among anaesthesia residents [1]. Burnout, as outlined by the World Health Organisation's International Classification of Diseases, is recognised as an occupational phenomenon and is characterised by three key domains: energy depletion; job-related negativity and reduced professional efficacy [2]. Fatigue among anaesthetists has been shown to affect both clinician well-being and patient safety negatively. It results in diminished alertness, slower decision-making and a higher risk of errors, all of which compromise patient safety [3]. With the rapid advancement of artificial intelligence (AI) in healthcare, one must question whether there is now a unique and unprecedented opportunity to combat the impending global crisis of burnout and workforce attrition in the healthcare system, specifically among anaesthesia residents. A major concern raised by Gale et al. was difficulty with rostering, including limited flexibility and challenges in accommodating leave for important life events, even when requests were made in advance, resulting in unnecessary stress and anxiety for residents [1]. The introduction of a ‘request rota’ was a positive adjunct for residents where implemented, although, notably, added an increased rostering workload. A recent initiative has highlighted the instrumental role that AI can play in generating a fair and balanced roster, addressing the specific requirements of an anaesthetic department promptly [4]. Therefore, could AI potentially reduce the stress linked to rostering and service provision by creating a reliable and supportive schedule in a timely manner that benefits residents? Artificial intelligence has the potential to allocate working hours and training time appropriately whilst facilitating requested leave, ensuring residents have the necessary time with their support networks [4]. A common issue among healthcare providers is low morale from the perception of being overworked and burdened excessively in the workplace [1]. Residents often face difficulty in balancing clinical commitments with non-clinical tasks, such as completing examinations and expanding their portfolios, which can leave them feeling overwhelmed and undervalued. Artificial intelligence enhances documentation by using speech recognition and natural language processing to capture physician-patient interactions and summarise them in electronic patient records automatically. Artificial intelligence-driven diagnostic tools enhance the accuracy and efficiency of patient care. They also reduce the cognitive load on healthcare providers when making decisions, helping to lower workplace stress [5]. Artificial intelligence has the potential to unburden a massive cognitive load through its unparalleled ability to process vast amounts of healthcare data and summarise it efficiently to enhance comprehension and decision-making. Furthermore, the predictive capabilities of AI are increasingly identifying patient deteriorations, which may be beneficial given the potential patient safety concerns related to physician fatigue, particularly out of hours. Therefore, this suggests a potential for AI to support clinical practice, improve workplace morale and, possibly, alleviate the heavy cognitive load experienced by physicians, affording a more favourable balance between clinical and non-clinical commitments. While the use of AI may seem distant from current clinical practice, its integration into healthcare is likely imminent. Exploring ways to introduce AI to support healthcare providers and residents will be crucial in helping to combat burnout, improve staff retention and enhance wellbeing, and should be considered when developing future strategies and programmes.

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Artificial Intelligence in Healthcare and EducationHealthcare professionals’ stress and burnoutResilience and Mental Health
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