When Dr. Andrew Taylor treats patients in the emergency room at UVA Health in Charlottesville, Virginia, he sees the promise of artificial intelligence every day. AI tools could help doctors diagnose faster, catch mistakes and save money. But Taylor knows they could also cause harm if hospitals aren't careful about how they use them.
So Taylor and a colleague at Clemson University created something hospitals desperately need: a clear guide for deciding which AI tools to use and how. They call it the Total Mission Value framework, and it just got published in a medical journal called npj Digital Medicine.
The core idea is simple: patient care should always come first.
The framework arranges priorities like a pyramid. Patient care sits at the very top. Below it, ethics holds everything up. Economic sustainability forms the wide base at the bottom that keeps the whole system running. Five priorities sit between the top and bottom: patient care, staff experience, hospital operations, economic impact, and education and research.
The doctors built this because hospitals have been making these decisions the wrong way. "Typical approaches tend to measure cost, because cost is the easiest thing to measure," Taylor said. "We built this framework to give organizations a structured way to also weigh what an AI tool does for patients, for staff and for the quality of care."
Taylor and Declan acknowledge that AI has real risks. Tools can carry hidden bias, make decisions doctors cannot understand, replace workers unfairly, and damage the trusting relationship between patients and their doctors. Those problems often hide when hospital administrators only look at the price tag.
"The challenge is to figure out which ones actually will," Declan said of the many AI tools now being sold to hospitals. "That requires weighing an AI tool's impact across clinical, operational and financial dimensions, while keeping patient care at the center of every decision."
Taylor puts it plainly: "Technology should help us take better care of people. If we keep that as the goal, the efficiency and the savings tend to follow."
The hope is that this framework will actually help AI spread faster in health care, not slower. When patients and doctors trust that new technology serves them rather than just the bottom line, adoption becomes easier. The framework gives hospitals a shared language for making these choices together.
As AI increasingly enters exam rooms and hospital hallways, tools like this could mean the difference between technology that helps patients and technology that simply cuts corners. For Taylor, the answer has never been more obvious: care for people first, and let everything else follow.