Health science faculty share how AI is re-shaping today’s health care

Health science faculty share how AI is re-shaping today's health care

Through research and a speaker series, faculty keep Lipscomb abreast of the latest AI use in healthcare.

Janel Shoun-Smith | 615-966-7078 | 05/14/2026

Artificial intelligence has already transformed the healthcare world in ways both big and small, and Lipscomb's health science professionals of the future will be prepared to navigate that world thanks to research and initiatives by College of Health Sciences (CHS) faculty going on today.

Faculty in the Department of Kinesiology and in the Health Sciences Simulation Lab are exploring ways that AI can be used to enhance health science education, while other health science faculty are researching ways it is already used in the healthcare industry today and bringing their findings to colleagues and students on campus.

Faculty share today's AI trends in the industry

In fall 2024, Lipscomb began instructing students in its new Master of Applied Artificial Intelligence degree. Within that program is an elective course, Applied Artificial Intelligence in Health Care, developed by a team of CHS and College of Pharmacy faculty.

In fall 2025, that team came together to be the first speakers in the inaugural CHS Healthcare Horizons Speaker Series, sharing their expertise on the intersection of AI and healthcare delivery over the course of the 2025-26 school year.

"We are all trying to look at what is currently possible and actively used in clinical situations and also spend some time thinking about what the future might hold as well," said Matt Steidl (BS '00), lead faculty for the health sciences track in the master's program and associate professor in the physician assistant studies program.

Speakers in the 2025-26 series included:

• Steidl, who spoke on "Smart Care, Human Touch: Integrating AI into PA-Delivered Healthcare";
• Jay Dorris (LA '07, Pharm.D. '14), assistant professor in the College of Pharmacy and healthcare informatics program, spoke on "Scripting Logic: AI, Informatics and the Future of Medication Management";
• Meagan Spencer, director of communication sciences and disorders, and Amy Staggs Draper, assistant professor of nutrition, spoke on "Kit Upgraded: The AI Toolkit for Nutrition and Speech Pathology"; and
• Jenna Sissom (LA '03), assistant professor in the School of Nursing, will discuss "AI in Nursing: How AI can Assist Nurses in Trending Data and Continuity of Care" in April.
  

In his talk, Steidl described the history of the medical scribe and how AI is often taking on that role now. After the rise of electronic medical records in the 2000s, doctors began hiring medical scribes so that they could continue their personal interaction with patients, without being trapped behind a computer screen, said Steidl. But turnover in scribe positions is high, and not all patients like having a third person in the room during their examination.

AI-powered scribes overcome both those disadvantages, and in the Applied Artificial Intelligence in Health Care course, summer 2025 students developed their own AI-powered patient advocate bots and treatment support bots, said Steidl, who gave a live demonstration of that AI bot at the Horizons series lecture.

He also discussed AI-powered, searchable databases of peer-reviewed medical literature, and how such platforms can provide more details on the patient's condition for health care providers. In a live demonstration of the platform Open Evidence, ChatGPT acted as the "patient," and the platform caught errors intentionally made by Steidl (portraying the medical provider), corrected the errors, drew attention to them and had a transcript ready in
mere seconds, he said.

Through her co-teaching of the AI in Healthcare course, Sissom explored AI's use in nursing, acknowledging that AI has already been operating in the background of many clinical systems for a number of years, she said.

"One significant application involves using AI to aggregate and synthesize data from patient charts into comprehensive summaries, reducing the time nurses spend on documentation and data review," said Sissom. "Beyond summarization, AI-powered prompts can be designed to identify trends within patient data, enabling nurses to recognize potential problems earlier and conduct more focused assessments."

In addition, AI programs can support patients during the critical transition periods of discharge and post-discharge care by identifying resources for which patients may qualify and assisting them in completing applications, said Sissom.

"This capability is particularly valuable for patients who face barriers to accessing resources, such as limited health literacy or difficulty navigating complex systems," she said. "By connecting patients with appropriate community resources, we can reduce preventable hospital readmissions for chronic conditions."

At the April, speaker series talk, Sissom discussed how to effectively teach health science students about AI and their professional responsibility to ensure patient safety, emphasizing that nursing educators must be able "to not only to use these tools competently but also to critically evaluate their outputs, recognize limitations and maintain patient-centered care as the foundation of their practice," she said.

"While AI offers tremendous promise in addressing healthcare challenges, its implementation must be guided by careful consideration of ethical principles and legal compliance to ensure equitable, safe and responsible use in clinical practice," Sissom said.

Spencer, who is currently developing a communication sciences and disorders bachelor's degree program to debut this fall, has included various AI topics and practice into the new curriculum for the program. In fact, recent research shows that nearly 68% of academicians in audiology and speech-language therapy already use AI tools in their practice, she said.

At the speaker series, Spencer introduced listeners to augmentative and alternative communication devices, tools ranging from simple picture boards to advanced speech-generating tablets that support or replace verbal speech for individuals with communication difficulties. These AI-powered devices can adapt in real-time or could include voice banking technology to preserve a person's unique voice, said Spencer.

These technologies are particularly impactful in K-12 environments, where they help remove learning barriers for students with disabilities, multilingual learners and those facing temporary challenges, she said.

"Our students need to understand not just how AI works, but how it can be leveraged ethically to improve patient outcomes and expand access to care," said Spencer. "There's concern among some healthcare workers and academics that AI accommodations might compromise rigor, but I believe true rigor isn't about doing everything without support. It's about the ability to perform critical thinking and problem-solving. AI can be an excellent tool for enhancing those skills."

Researching AI in health science education

Other AI research is ongoing in CHS classes, such as kinesiology Professor Zach Droll's innovative teaching project, in his Strength and Conditioning Program Design course, where his students have coded an AI platform to provide assessments using a teaching principle called varied repetition. Using this principle, the AI system randomly presents test questions from curriculum units covered earlier in the semester, creating spaced and randomized retrieval across the semester.

"The AI system is also adaptive," said Droll. "As students consistently answer questions correctly, those questions are gradually phased out and replaced with more difficult ones that extend the same concepts. When questions are expanded, the AI is instructed to incorporate research from the past five years in leading journals such as the Journal of Strength and Conditioning Research and publications from the International Society of Sports Nutrition."
Students track their usage of the system, and that data is anonymously compared with course performance. Each student serves as their own control by completing the first half of the semester without the AI system, allowing the students to evaluate whether AI-supported spaced retrieval improves learning outcomes.

Jeffrey Adams, director of Lipscomb's Health Sciences Simulation Lab (who literally wrote the book on AI in health simulation: Engaging Minds: Rethinking Student Assignments in the Age of AI), also enacted a research project this spring semester focused on verifying if AI platforms provide consistent results when used to grade health sciences students' work in documenting patient care.

Adams, co-principal investigator Steidl and student intern Charlotte Ran are inputting a set of 60 SOAP (Subjective Objective Assessment and Plan) notes that various faculty provide students after observing and grading their actions during a health care simulation. They are testing to see if AI can take SOAP notes provided by different faculty and grade them all the same way, providing a consistent grading method.

"I think that is a big question in education right now: How do we know that AI is giving each student a grade based on consistent requirements, and whether that grade relates to what the instructor is teaching students as well," said Adams.

The study intends to compare the grading consistency on several AI platforms and to compare the AI's grading based on various control settings within the platform. If proven reliable, AI grading of SOAP notes could save faculty a great deal of time that could be re-focused on students, he said.