HHS 5-Year Health Data Strategy Prioritizes ‘Responsible’ AI

The Biden administration is heavily counting on “responsibly” leveraging AI as part of a strategy that aims to harness data to enhance the health and wellness of Americans. That includes ambitions to drastically improve cancer care and reduce cancer deaths, among other top goals.

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The five-year data strategy from the U.S. Department of Health and Human Services supports the Biden Cancer Moonshot initiative – which aims to cut the cancer death rate of Americans in half over the next 25 years. The moonshot initiative was first launched while Biden was vice president during the Obama administration (see: 21st Century Cures Act Awaits President’s Signature).

Another critical top goal is improving HHS’ preparedness and incident response for situations ranging from severe respiratory illnesses to natural disasters.

Overall, HHS said its data strategy is built around five top data priorities to improve departmentwide data capabilities and infrastructure.

Other priorities are cultivating data talent within HHS, fostering data sharing, integrating administrative data into program operations and using data to establish “a whole-person and whole-family view” of wellness and health needs of Americans.

“By harnessing the power of information and leveraging recent technological advancements, we’re better equipped to meet the evolving needs of the people and communities we serve,” said Andrea Palm, HHS deputy secretary.

The department has already embraced AI for uses such as research and discovery in pharmaceuticals, medical care delivery and public health, but “2023 represents a historically unique moment, calling for leadership in AI,” the strategy said. A convergence of factors, including growth in cloud computing infrastructures, new technologies and pandemic investment has accelerated the path to widespread adoption, HHS said.

“AI offers the opportunity to rapidly advance scientific discovery, such as the creation of novel vaccines and therapeutics through new chemical formulations or expedited clinical trials by identifying right populations and running synthetic trials on pre-existing compounds,” HHS wrote.

AI in healthcare also has the potential to dramatically drive efficiencies, especially in administrative processes, and improve clinical decision support, among other benefits.

“However, AI also presents significant risks – including discrimination, bias, fraud, disinformation, cybersecurity, biosecurity, privacy, and inappropriate uses – that must be thoughtfully addressed to ensure that we are able to reap the benefits of these new technologies and not stifle innovation, while also protecting our core values,” HHS wrote.

The document pledges to establish an AI Task Force responsible for creating policies and frameworks on responsible use of AI in the health sector and tap HHS funding to advance responsible use of AI.

Separately this week, HHS’ Office of the National Coordinator for Health IT emphasized AI in a final rule related to health data interoperability and the agency’s latest iteration of its health IT certification program.

HHS ONC said the new health IT regulations establish “first of its kind transparency requirements” for AI and other predictive algorithms that are part of certified health IT.

On Thursday the White House announced that two dozen healthcare organizations pledged to deploy AI responsibly in a bid to improve health outcomes for Americans while protecting their security and shielding patients against bias (see: White House Obtains Safe AI Pledges From 28 Healthcare Firms).

Many healthcare industry experts are also carefully but optimistically anticipating how the evolving use of AI in medicine can advance clinical discoveries, care and outcomes for patients, as well as streamline administrative processes.

“There is a lot of low-hanging fruit” that medical institutions can currently tap for applying AI to make improvements on both the clinical and administrative sides, said Nawar Shara, director of the health research institute at MedStar, a large healthcare provider in the Washington, D.C. area, during an AI conference this week hosted by the World Bank and Georgetown University (see: Addressing Privacy and Data-Sharing Hurdles in Healthcare AI).