As many health systems have deployed enterprise AI at scale — signing vendor contracts, rolling out ambient documentation tools and expanding predictive analytics across clinical workflows — the University of Nebraska System has been building its own.
“We’ve now implemented 63 homegrown AI platforms across the health system,” Jeffrey Gold, MD, president of the Lincoln, Neb.-based University of Nebraska System, said in an interview with the “Becker’s Healthcare Podcast.” “Anything from women’s health to cancer to congestive heart failure — we just put one out into the area of maternal health, in the specific area of predicting preeclampsia and early treatment.”
Other academic medical centers are pursuing vendor partnerships to accelerate AI deployment in precision medicine, and some major systems have signed sweeping enterprise deals to get tools in front of clinicians faster. Nebraska’s approach runs in a different direction — and the rationale Dr. Gold offers for it comes not from healthcare but from agriculture.
As a land-grant institution, the University of Nebraska has long applied precision agriculture principles to the crops and farming communities its research supports: calibrating irrigation, fertilizer and management, treating each parcel of land according to its specific conditions. Dr. Gold argues the same logic should govern clinical AI.
“We talk a lot about precision agriculture — how you grow corn and soybeans and alfalfa not by the acre or by the square mile, but by the square meter or square yard, and taper how much irrigation, how much fertilizer, how do you handle those plants,” Dr. Gold said. “We need to do the same thing for healthcare and we have been on that journey for a very long time with precision medicine. I’m proud of the work we’ve done in those areas, but we need to do more of it.”
The implication is that a vendor tool designed for broad deployment may not be the right tool for every patient, every community or every clinical context and that an AI built for a specific population or condition will outperform a standardized one in that setting. For a health system serving communities as different as metropolitan Omaha and a rural county with a thousand residents and a million head of cattle, that specificity has direct clinical stakes.
“The more we can individualize care and customize it and make that customized approach more accessible and egalitarian, the better we will be in the long term and that will make it more affordable,” said Dr. Gold. “If the same shoe has to fit everybody, it’s not going to be affordable, and it’s not going to be as high quality and accessible as if we can treat people differently.”
The build-first approach requires infrastructure most health systems don’t have. University of Nebraska’s position as a comprehensive university system, integrating engineers, computer scientists and clinical faculty under one institutional roof, is what makes internal AI development viable at scale. The 63 tools exist because the institution can draw on experts that most standalone health systems cannot.
“I’m hoping that because of our large university approach to this — engineers, computer scientists, as well as health care professionals — we can continue to lead and be at the forefront,” Dr. Gold said.
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