As demand for clinical informatics and AI expertise accelerates, UChicago Medicine is extending its training model beyond its own workforce — aiming to help build a global pipeline of clinical IT leaders.
The health system recently partnered with Taiwan’s Ministry of Health and Welfare to train a new generation of physician informaticists, a move the system’s leaders say reflects both a growing talent gap and a shift in how health systems must approach workforce development.
“There’s a lot of need for more talent in this area, because we have a lot to do,” Cheng-Kai Kao, MD, CMIO of UChicago Medicine, told Becker’s.
The partnership emerged from a mix of personal connections and broader industry pressures. Dr. Kao, who trained in Taiwan before building his career in the U.S., had ongoing relationships with health leaders there. At the same time, both countries were facing a similar reality: Healthcare systems are being reshaped by AI, data and digital transformation, but the workforce has not kept pace.
Taiwan’s government approached UChicago Medicine to help train a cohort of clinicians to become future CMIOs, launching a program designed to go beyond traditional education and into hands-on leadership development.
For Dr. Kao, that distinction is critical — and often where existing training models fall short.
“You need to see it actually happening and be participating in order for you to learn,” he said.
While the U.S. offers formal clinical informatics fellowships, the new program compresses that model into a more accelerated pipeline. Taiwanese clinicians begin with online coursework covering core concepts like data use, privacy and security, then transition into a six-month onsite rotation in Chicago.
During that time, participants are embedded within UChicago Medicine’s informatics and IT operations — attending leadership meetings, observing governance processes and working directly on digital transformation initiatives. Each trainee is assigned at least one project, with expectations to contribute meaningfully and present outcomes at the system’s quality and safety symposium.
The structure is intentional: exposure alone is not enough. Participants are expected to return to Taiwan and implement similar projects within their home institutions, creating a feedback loop that connects training to real-world impact.
The approach also reflects a broader shift in how clinical IT leadership is evolving.
Dr. Kao described the CMIO role in phases — from early EHR implementation to optimization, and now to a third stage centered on enterprisewide digital transformation. In this phase, leaders are expected not only to manage systems, but to guide how technologies like AI reshape clinical workflows and care delivery.
That shift is also driving new workforce pressures.
Healthcare systems face ongoing staffing shortages, while the complexity of digital tools continues to grow. In that environment, Dr. Kao sees AI not just as a technology investment, but as a way to extend the capacity of existing staff — allowing one clinician or employee to oversee multiple automated processes.
“Everyone’s a team lead, and you work with maybe 10 AI agents under you to accomplish your task,” he said.
But building that kind of workforce requires more than a small group of specialists. It also demands broader AI literacy across clinical teams, along with leaders who can bridge clinical care, data and technology.
That’s where the pipeline model becomes critical.
Rather than training isolated experts, UChicago Medicine is working to create a system that produces both dedicated informatics leaders and a wider network of clinicians who understand and can champion digital tools.
The Taiwan partnership is the first iteration of that model — but likely not the last. Dr. Kao said the program has already drawn interest from other countries, signaling a broader global demand for structured informatics training.
Long term, he sees the initiative as part of a larger infrastructure for workforce development, one that extends beyond a single partnership.
“I’m hoping what we establish is not only applicable to external candidates, but really an important infrastructure for continuing training,” he said. “We already got a lot of requests from other countries so there’s a strong need there.”
For health systems facing similar workforce gaps, the model offers a potential blueprint: combine foundational education with embedded, project-based experience — and tie training directly to implementation.
As AI adoption accelerates, that kind of pipeline may become less of an innovation and more of a necessity.
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