In 2018, San Antonio urologist Ronald Rodriguez, MD, predicted medicine would soon see the widespread use of artificial intelligence (AI) technologies in health care – a change he feared would mirror the implementation woes of electronic health records (EHRs) years prior.
Worried that leaving physicians out of the creation of health care technologies would negatively impact patient care, the University of Texas Health Science Center at San Antonio professor of medical education met with colleagues to develop a program that could integrate emerging AI technology into the education of Texas’ future doctors.
“We had a vision that AI was going to become a dominant player in how health care research administration, education, and eventually treatment was going to move forward,” he said.
Faculty from both the UT Health San Antonio Long School of Medicine and the University of Texas at San Antonio (UTSA) then spent the next five years developing what has now become the first known degree program in the country to combine medicine and AI.
Dr. Rodriguez, a director of the joint program, says it is designed to prepare the next generation of physicians to understand and utilize evolving AI technology by providing comprehensive training in computer science, data analytics, and ethics – all tenets necessary to both develop AI technology and to understand its implications on health care.
The five-year program – which launched in 2023 following a 2021 pilot program that saw two UT Health San Antonio Long School of Medicine students graduate this spring – allows medical students to earn a combined doctor of medicine degree from UT Health San Antonio and a master of science degree in AI from UTSA.
The latter trains students in three tracks: data analytics, computer science, and intelligent and autonomous systems, which focuses on AI theory and applications.
Other core elements of the master of science degree include understanding AI terminology like machine learning, neural networks, deep learning, convolutional neural networks, and natural language processing, Dr. Rodriguez says.
Dr. Rodriguez says the program’s tailored curriculum enables physicians trained in Texas to “uniquely lead in the use of AI to improve [diagnostic and treatment] outcomes.”
“If we don’t have medical professionals leading the charge ... the implementation of AI into health care is going to be driven largely by [those] who don’t have a fundamental understanding of medicine and who may actually cause a worsening of health disparities,” he said.
Positive developments
AI technology has been integrated into multiple EHR systems, including EPIC, Doximity, eClinicalWorks, and Athenahealth, whose chatbot-based platforms can format clinical documentation and common medical correspondence, among other benefits.
And while still in the early stages of development and use, a 2019 report from the National Academy of Medicine identified three potential benefits of clinical-based AI: enhancing outcomes for both patients and clinical teams, lowering health care costs, and bettering population health.
Dallas emergency physician and ChatGPT health care adviser Harvey Castro, MD, shared with Texas Medicine that many of his colleagues say their AI-integrated EHR systems are now providing “better medical record or discharge summaries” than manual compilation, such as handwritten or typed notes, lab results, and other pertinent information clinicians often spend a significant amount of time organizing and summarizing.
Dr. Castro was recently appointed as an AI consultant to the Texas Medical Association’s Committee on Health Information Technology (HIT), which TMA expanded to better encompass AI as the technology evolves in health care, says TMA President G. Ray Callas, MD.
“Physicians and TMA need to be [at the forefront] of AI,” Dr. Callas told Texas Medicine. “This is a topic we have to wrap our arms around to ensure AI technology is being properly used to take care of patients.”
Dr. Callas says consultants will be tapped for information on:
- Their knowledge of regulatory standards;
- Their understanding of medical ethics, especially in relation to AI; and
- Their experience with policy development, risk management, or medical technology implementation.
TMA’s HIT Committee adopted related AI policy in 2022, which the House of Delegates updated in May.
The committee will continue to work on AI issues during next year’s legislative session, which starts in January. Manish M. Naik, MD, chair of TMA’s HIT Committee, says one of the key focus areas for the committee next session will be to examine legislation that addresses data concerns regarding AI.
“There’s [no] transparency about what’s happening with data that these tools are ingesting,” he said. “There are no controls over who’s using that data or how that data is being used. As a committee, we will examine legislative action that could create more transparency about the security of the data and transparency about the algorithms that underpin the AI solutions.”
“It’s important to understand the data inputs that lead to the AI outputs to validate the accuracy of the tools,” the Austin internist said.
Dr. Naik adds that the committee will continue to ensure legislation mirrors TMA’s policy, which outlines AI should be used as an augmented tool set. Whereas artificial intelligence uses internet data to drive its decisions, augmented intelligence is used as an enhancement aid, and defers to human knowledge to validate its responses.
“We’re seeing a lot of activity in the health care space with relation to AI. But if you don’t understand health care and the clinical perspective, you may be building tools that are not relevant or meaningful to medicine,” he said. “There is, however, a huge opportunity to leverage AI for automation of repetitive tasks and assistance with administrative burdens in health care.”
Leading the way
San Antonio radiologist and faculty member for the dual degree program Kal L. Clark, MD, agrees that AI has the potential to reduce health care challenges that plague physicians. He says the new AI degree program was created in part to do just that.
“How do we … improve the efficiency of the health care system, reduce administrative burden, and also deliver compassionate care?” the UT Health San Antonio associate professor said. “This program is a unique way to do that. We can attract and train technically efficient students who will one day solve these problems.”
Dr. Clark is a member of the UTSA MATRIX AI Consortium for Human Well-Being – a research-intensive group focused on sustainable and comprehensive AI uses – and the UT System Consortium for AI in Diagnostics.
He says that students enrolled in the dual-degree program have an opportunity to conduct research alongside himself and other faculty members in these groups in the areas of computer science, mathematics, statistics, and electrical and computer engineering.
Dr. Clark is hopeful this research will aid Texas medical students in someday creating AI systems that are “curated and engineered appropriately to perform as a physician extender” and that will also reduce burdens like prior authorization.
“It is possible to use generative AI to identify the hidden rules that different payers use to hold or prevent payment,” he said. “AI can then give that information to a physician as they’re conducting a patient session and writing their notes.”
“It would be an interesting project for future students to take on,” he added.
Medical students who are accepted to the dual-degree program are required take a leave of absence from their medical education to complete two semesters of AI coursework at UTSA.
Subsequently, students must take elective AI courses at UT Health San Antonio devoted to a capstone project, which includes a thesis on an original AI research idea that utilizes clinical data from the university.
That thesis will then be submitted for publication to a peer reviewed journal. Mentors from UT Health San Antonio and UTSA will be available on both campuses to provide input on student capstone projects.
Dr. Rodriguez says teaching the next generation of doctors about AI should begin “as soon as possible to [ensure] physicians are the driving force behind medical AI.”
“I would like to see [AI education] implemented in all medical schools,” he said. “If we as medical professionals don’t step up and take control of [AI’s] direction, we’ll be left behind.”