Artificial intelligence (AI) has rapidly ingratiated itself in the health care landscape, emerging as a powerful tool with the potential to revolutionize various aspects of clinical practice. From enhancing diagnostic precision to streamlining administrative workflows, AI is touted as a solution to many of health care’s long-standing inefficiencies. Yet, the transformative power of AI is a double-edged sword, and its integration may bear unintended repercussions for not only patients but also physicians.
Physician burnout, a pervasive issue characterized by emotional exhaustion, depersonalization, and a sense of reduced personal accomplishment, remains an escalating concern within the health care industry. This syndrome is particularly pronounced in high-mortality specialties such as oncology and veterinary medicine, where the emotional toll of the practice is exacerbated by the more frequent reality of patient loss (and daily within veterinary medicine). With its potential to enhance efficiency, support physicians in simpler cases, and automate certain aspects of their workflows, AI is widely regarded as a possible solution to address the burnout crisis in health care. It could alleviate some of the burden on physicians, freeing them to see more patients, focus on other relevant tasks, or spend time on wellness.
Though we are optimistic about the future of AI in health care, it is worth considering, could AI potentially increase physician burnout instead? As AI evolves and improves, physicians may find themselves confronting an escalating amount of time spent on complex, high-risk tasks without the mental breaks of simpler cases. This shift could inadvertently increase emotional and cognitive load as they grapple with a greater frequency of complex cases and interactions. Could AI, in mitigating one aspect of physicians’ stress, inadvertently amplify another, leading to an overall intensification of burnout rates?
Take, for instance, the field of oncology. Oncologists already face emotionally difficult work and have high burnout rates; they guide several patients and families each day who have a difficult road ahead without a true guarantee of what lies after. If AI systems can successfully help decrease the amount of time spent on more straightforward cases, it would be a daunting task to meet with patient after patient, truly facing mortality and suffering day after day for the rest of their careers. Such a scenario could amplify the emotional burden these physicians already shoulder, potentially triggering a surge in burnout.
A similar situation could be envisaged in veterinary medicine. The evolution of AI could lead to more frequent encounters with complex and high-risk cases. Combined with the existing challenges of the profession, including the frequent necessity of euthanasia and the emotionally-charged conversations with grieving pet owners, could AI integration inadvertently raise the stakes in an already high-pressure profession?
Looking to radiology, a field that has actively adopted AI, some studies have found that radiologists report an increase in workload when AI is integrated into their workflow. In a survey among members of the European Society of Radiology (ESR), 49 percent of radiologists reported that they expected an increase in workload as AI is adopted more in their field. In yet another survey with the ESR, 70 percent of radiologists who actively use AI reported no reduction in their workload when using AI. Moreover, for specialties that interact directly with patients, given there are long patient wait times, would physicians who use AI simply see more patients per day? Would their workload actually decrease? There is a need for further research on this topic, especially across different specialties; it is possible that AI will not reduce workload but rather make the existing workload tougher.
However, given studies on AI and workload are still nascent, it may be possible that AI will eventually significantly reduce workload for physicians. It is possible that over time, more physicians may grow to embrace AI and utilize it as a major part of their daily routine. Could this reduce workload overall and potentially allow for more time toward resources and experiences that decrease burnout, such as stronger support systems, mental health resources, and peer support networks?
As AI in health care evolves and improves, numerous researchers and organizations are taking steps to ensure that new technology is only implemented safely. For instance, the EU General Data Protection Regulation (GDPR) enforces rules in regard to processing personal data and protecting data subjects from solely automated decision-making. It is important that we remain keen to follow suit and devise strategies that ensure all affected groups–whether patients or physicians or other health care entities–are kept safe as the main priority.
One approach might involve the deliberate distribution of case mix, ensuring that physicians encounter a balanced variety of cases. This could involve utilizing AI tools to manage a portion of both simple and complex cases, ensuring that physicians are not isolated from the range of patient experiences. In addition, involving physicians in the development and implementation of AI tools could be beneficial. This would help ensure the technology serves to support rather than overwhelm its users, thereby fostering a sense of agency and mastery rather than exacerbating stress.
In conclusion, while AI possesses immense potential to transform and enhance health care, its integration is not without potential challenges. The inadvertent impact of AI on clinician well-being necessitates careful consideration and strategic planning. Balancing the benefits of AI against the necessity of maintaining compassionate, human-centered care will be a defining challenge of the digital health care era. The management of this balance will ultimately determine whether AI serves as a boon or a burden for those at the heart of health care: our physicians.
Tatum R. Dam is a health care AI researcher. Joshua I. Leaston, Diana A. Hla, and Ank A. Agarwal are medical students.
