A Scoping Review of the Role of Artificial Intelligence in Physician Burnout

Physician burnout is an increasingly prevalent issue affecting many physicians across all specialties and, by proxy, their patient outcomes. One key factor is associated with excessive medical record documentation. Maintaining patient records can be time-consuming, cumbersome, and complicated for some physicians. As such, artificial intelligence (AI) such as ChatGPT or newer programs may provide an effective solution, which may provide reduced human work efforts, including administrative tasks such as documentation. With advances in natural language processing (NLP) tied to AI approaches, the medical field has been open to adopting AI to improve efficiencies tied to documentation and other repetitive clerical duties. This scoping review aimed to examine the impact of AI on physician burnout in the context of medical charting and administrative tasks, excluding its role in diagnosis or patient treatment. Specifically, it aimed to explore existing research to understand the influence of using AI on physician burnout and determine how AI has influenced the experiences of physicians. A thorough search of the peer-reviewed literature, following Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping review (PRISMA-ScR) guidelines, was conducted across three databases (EMBASE, Ovid Medline, and Web of Science) for articles published in English between 2014 and 2024, focusing exclusively on physicians using AI technologies in clinical settings. The initial search yielded 663 articles, which were refined to eight articles after a systemized, rigorous search and selection process. The findings indicate a potential for AI to mitigate physician burnout by decreasing documentation time, improving physician-patient interactions, and enhancing clinical workflow efficiency. Challenges such as overreliance on AI and insufficient familiarity with technology may be tied to misinformation or misuse. These issues highlight areas of further development and research to advance AI technology integration into clinical practice.