How ChatGPT can improve the clinician experience.


Over the past few years, artificial intelligence (AI) has made significant advancements in the healthcare industry. One of the most prominent AI-powered tools is ChatGPT, a natural language processing model developed by OpenAI.

Of the many applications, most are directed at improving clinical, operational and financial outcomes. When it comes to sales and experience, most have focused on patient experience. But what about the clinician experience and the possible burnout impact factor?

Sick care professionals assume distinct roles including as clinicians taking care of patients, doing research, educating, and training medical students and residents, serving as editors, reviewers, and members of editorial boards of biomedical and scientific journals, serving as advisors, consultants, and members of startup teams and more. Each has its own experience journey offering opportunities for technology like large language models to remove friction in their workflow.

How could ChatGPT improve the clinician experience?

  1. Virtual assistants
  2. A guide on the side providing clinical decision support
  3. Medical record keeping and input into the electronic medical record
  4. Facilitating response to prior authorization requests
  5. Medical translation
  6. Patient visit clinical summaries
  7. Patient education materials
  8. Clinical trial recruitment and retention
  9. Patient intake history
  10. Referral and consultation letters
  11. Managing digital front door patient correspondence including overflowing patient emails on the electronic medical records patient portals
  12. Responding to patients about normal lab tests or images
  13. Scheduling
  14. Operating room and outpatient visit productivity and flow
  15. Reducing dropped handoffs and referral leaks

So far, these applications are merely hypothetical and have not been widely deployed or measured to see if they achieved their intended use. It is unlikely we will see widespread dissemination and implementation of large language models in the near term because medical professionals are very resistant to change, the costs of implementation v the benefits are unknown, digital transformation is a long, multistep process, and the value proposition and incentives for clinicians to use it, including getting paid to do so, is not convincing enough to change their behavior. Is GPT transformative or terrifying?

In addition, the effects of technology are exaggerated in the near term and underestimated in the long term and Solow’s paradox tells us the counterintuitive conclusion that deployment of technology leads to a decrease, not increase, in productivity in the near term and that is impossible to predict when and how it will have a lasting beneficial impact in the future.

Given the rates of clinician burnout, drop out, and many trying to figure it out, the sooner we can help clinicians push the rock up the hill with clinically and operationally validated technology the better. Someday, maybe, it can even help me figure out how to administer all those new-fangled drugs.

At least that’s been my experience.

Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs