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How AI, Digital Transformation in Health Care Compare Around the World

HHS and EU officials contrasted the different frameworks for emerging technology and the challenges that remain.

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Greg during an interview at HIMSS in Orlando, Florida, March 12, 2024.
Department of Health and Human Services Chief Artificial Intelligence Officer Greg Singleton speaks during an interview at HIMSS in Orlando, Florida, March 12, 2024. Photo Credit: GovCIO Media & Research

ORLANDO — Artificial intelligence and digital transformation are hot button topics as government agencies nationally and globally begin to adopt them into their new IT strategies. While government officials, health care professionals and industry partners attended HIMSS in Orlando, Florida, the European Union adopted the Artificial Intelligence Act on the heels of the U.S.’s own White House executive order on AI.

A Different Approach to AI, Digital Transformation

Senior Advisor of European Health Policy & EU Affairs Petra Wilson and U.S. Department of Health and Human Services (HHS) Chief AI Officer Greg Singleton discussed the different approaches each are taking toward AI after they enacted AI regulations.

Out of the executive order, we have a number of programs, including a task force. It’s truly shaping up as a whole HHS effort, a whole government effort, as we look at the future and try to steer us towards healthy, manageable, responsible ways of leveraging these technologies,” Singleton said.

Wilson said the EU’s Artificial Intelligence Act operates through a risk-based approach, with the top being unacceptable risks down to the minimal or no risk use of AI. High-risk examples include using AI to interfere with transportation information and includes biometric data, chatbots being an example of limited risk use and AI in video games designated as limited or no risk.

“We’ve developed this hierarchy of risk and we are trying to approach it in a flexible way that is actually able to be agile within a rapidly changing environment,” Wilson said.

At the Centers for Medicare and Medicaid Services (CMS), Chief Digital Strategy Officer and Director of the Digital Services Andrea Fletcher noted that more 50 countries are using open framework tools for digital transformation. Most importantly, Fletcher said, the countries are developing national strategies and implementing them. CMS is working through the unique structure of the federal government to create opportunities for these tools.

“Our team has launched the first open-source program office in the federal government. It is a new opportunity for us to think about how we can fundamentally change the way that we build software. What does that look like to do it completely differently?” Fletcher said. “We’ve actually had open-source laws and open-source policies in the federal government for 20 years and use those policies to our advantage.”

Putting People Before Technology

Despite the differences in approach to digital transformation and AI policy, the U.S. and other countries are prioritizing people before the use of new technologies. Wilson said many people have a fear of AI taking over jobs or taking care of people in health care settings. Policy needs to approach that fear in a new way instead of an “old fashioned, top-down way,” she added.

“I think there’s going to be quite an interesting transition, which will start with this law, … where we move to a more dynamic way of legislating where we actually bring in the industry, the users who are going to be affected by the legislation to help shape it, to help make it more usable so that ideally we have to consume less litigation time, less clarification time to actually make the legislation workable,” Wilson said.

Both Wilson and Singleton emphasized the challenge of lacking a strong workforce to test AI and mitigate issues that may arise as new technologies and policies develop. Singleton said agencies will need to put training programs and educational materials in place, along with opening jobs to those who don’t have a degree or strong background in data analytics.

“We don’t have a stable of AI workers hanging out and ready and just waiting, so it’s going to be a little bit of a learning by doing the process. It’s going to be an evolutionary process,” Singleton said. “We’re going to start with foundational materials, start with training … to encourage new developments and models, new approaches, and go towards that pathway to where we’re able to comfortably use these tools throughout the system.”

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