Along with potentially shortchanging experts and discounting their effort, the current model also could erode trust between doctors and their patients. It forces doctors to make billing decisions without reliable methods to measure their work.
“Doctors don’t measure response time with a stopwatch, and some questions may require multiple sessions to address, making billing decisions even more complex,” said Ko, who created the first research lab at the Lindner College of Business.
Additionally, the uncertainty of whether patients will get billed may discourage them from contacting a medical professional. That breaks down continuity of care, delaying treatment and potentially leading to worse health outcomes.
“We need balance,” said Ko. “Both time and medical expertise must be considered in billing.”
Ko anticipates telehealth billing challenges will grow as generative AI becomes more integrated into medical practice. While AI can deliver faster solutions, doctors will still need to validate its responses and invest time in maintaining and operating these systems — efforts that must be compensated to avoid increasing burnout among medical professionals, Ko said.
“At the early stages, validating AI-assisted responses will be critical,” Ko said.
Ko’s AI system can use doctors’ behaviors to better understand and measure their expertise, offering a framework for fairer compensation. His tests of machine learning models have delivered consistent results, demonstrating the potential to more accurately evaluate doctors’ expertise and time spent on patient inquiries.
“This time-based metric is constrained, and this model is not sustainable, especially with generative AI coming into the picture,” Ko said.
Looking ahead, Ko envisions broader applications for his research. He aims to create a system that predicts whether a patient will be billed before submitting a question and to uncover insights from patient data to improve care outcomes.
By combining AI and innovative research, Ko’s work could transform telehealth billing, ensuring fair compensation for doctors while improving patient outcomes. He plans to pilot his program with health systems in 2025.
Featured image at top/National Cancer Institute/Unsplash