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If surgeons don鈥檛 step up to integrate artificial intelligence (AI) into their work, what defines a successful surgery will be decided by others. 鈥淪urgeons need to take the lead in integrating AI, defining how it affects their practice, and how they can use it to define and influence what good patient care means,鈥� said Carla Pugh, MD, PhD, FACS, the Thomas Krummel Professor of Surgery at the Stanford School of Medicine in California. Dr. Pugh also is The Joint Commission鈥檚 first awardee of The President鈥檚 Fellowship for Healthcare Quality and Safety, a program for a highly qualified healthcare professional to collaborate with The Joint Commission to advance healthcare outcomes globally.

In the era of minimally invasive and robotic surgery, the psychomotor mechanical actions of the surgeon performing the procedure are recorded by the robotic platform. In addition, the moment-to-moment flow of the surgical procedure is recorded and archived. These technical motions and visual images can be evaluated to determine if the procedure was completed successfully. There are important questions that need to be asked and answered by surgeons regarding these assessments, including:

• Who determines the performance standard for procedures captured and evaluated on a robotic platform?
• Who evaluates and correlates the 鈥渃orrectness鈥� of the procedure with the outcome of the patient?
• Does a 鈥渃orrect鈥� procedure always result in a positive patient outcome, and does a technically 鈥渋ncorrect鈥� procedure result in a negative outcome?
• What are the consequences to these questions for the patient, surgeon, and the future of surgery?

Surgeons need to consider these and other questions related to the skill evaluations, and ideally they should be in positions of leadership going forward to help develop policy and standards, especially in the era of AI. It also is important to develop an ongoing awareness that the data are available to industry instrument manufacturers, insurance companies, and legal professionals.

As the director of the Technology Enabled Clinical Improvement Center at Stanford University, Dr. Pugh studies the use of simulation and advanced engineering technologies to develop new approaches for assessing and defining competency in clinical procedural skills. I recently spoke to Dr. Pugh about AI, robotics, and expectations for the future of surgery. In setting the stage for our discussion, Dr. Pugh started by stressing the need to assess minimum competency and mastery in surgery, and provide appropriate measurement for both levels. 鈥淲e have to determine what the measures are, and we, as surgeons, need to lead the effort,鈥� she said. 鈥淲e need to give manufacturers guidance on what we need for our practice. If we don鈥檛 take the lead on which variables are important to use鈥攆or example, anatomical complexity or the synergy of the surgical team鈥攖hose assessments will be missed.鈥�

Dr. Pugh added, 鈥淭here are lots of data streams that can give us insight into mastery in surgery and how we test mastery. No one wants to be minimally competent, but we can assess both鈥攁nd we should. There is work to be done to quantify both. And we have a framework to guide us, which is the Olympics.鈥� She explained how standards of excellence are evolving in the Olympics: 鈥淲hat was a 10 in the 1970s is different than what was a 10 in 2024. The measurement hasn鈥檛 changed, but mastery performance has; therefore, the expectations for mastery have changed. In surgery, the metrics will likely arise out of a combination of human-derived and digital data. What will define mastery today will differ from what it was in 1980, and what it will be in 2040. If you don鈥檛 have explicit mastery metrics, you鈥檒l never achieve a standard benchmark that can be used globally for accountability. This is the goal we want to achieve as a profession.鈥�

I asked Dr. Pugh to share more about competency, privileges, and what evaluations will be based on moving forward. 鈥淚t would hurt our profession to have a very narrow view of mastery. Privileges should be based on minimal competency, not mastery. Not all surgeons need to be gold medal winners. What about silver and bronze? They are still winners. Competency may mean a 90% success rate for most patients for a specific disease process,鈥� she said. Dr. Pugh also reminds us that mastery should be defined at the team level such as with the Chicago Bulls basketball team. 鈥淎s an example, Michael Jordan and Scottie Pippen each had different expertise, but together, as part of a team, it worked because they had a mix of mastery that was complementary. You need a variety of mastery to achieve great patient outcomes. However, if we start focusing on mastery as the sole paradigm to judge surgeons and not teams and systems, insurance companies鈥攁nd patients鈥攚ill start cherry-picking surgeons, and this will hurt everyone. There is also a need to align surgeons鈥� skills with the metrics for specific disease processes,鈥� explained Dr. Pugh.

鈥淐ompetency is a base standard. You don鈥檛 need to win the Olympics to be a good athlete. And surgeons don鈥檛 have to perform at an Olympian level to be a good, quality physician. Industry should not define what affects our practice and how we define good patient care. That鈥檚 our job,鈥� she said. To get involved in the integration of AI in surgery, Dr. Pugh urges surgeons to educate themselves and look for opportunities to participate in their surgical field. 鈥淔ind out who is talking about AI, and if robotics is applicable in your field, find out who is talking about the data and metrics,鈥� she said. 鈥淪urgeons need to understand the science, the barriers, and potential uses of AI and robotics,鈥� Dr. Pugh said. 鈥淪urgeons need to be at the table, because AI will affect your practice.鈥�

Disclaimer

The thoughts and opinions expressed in this column are solely those of Dr. Jacobs and do not necessarily reflect those of The Joint Commission or the 糖心网页版.

Dr. Lenworth Jacobs Jr. is a professor of surgery at the University of Connecticut in Farmington and director of the Trauma Institute at Hartford Hospital, CT.

Bibliography

Korndorffer Jr JR, Hawn MT, Spain DA, et al. Situating artificial intelligence in surgery: A focus on disease severity. Ann Surg. 2020;272(3).

Mohamadipanah H, Perumalla CA, Kearse LE, et al. Do individual surgeon preferences affect procedural outcomes? Ann Surg. 2022;276(4):701-710.