FDA Commissioner Robert Califf on the agency’s new digital health committee
The commissioner detailed the goals for the new committee during a session at CES.
FDA Commissioner Robert Califf. Drew Angerer/Getty Images
The commissioner detailed the goals for the new committee during a session at CES.
FDA Commissioner Robert Califf. Drew Angerer/Getty Images
If there’s one thing the FDA loves, it’s an advisory committee.
FDA Commissioner Robert Califf outlined the agency’s plans for the new Digital Health Advisory Committee during a January 10 session at the 2024 Consumer Electronics Show (CES) conference. The FDA had announced the committee in October, adding it to the agency’s list of at least 49 other advisory committees.
The FDA has said the committee will “help the agency explore the complex, scientific, and technical issues related to digital health technologies, such as artificial intelligence/machine learning (AI/ML), augmented reality, virtual reality, digital therapeutics, wearables, remote patient monitoring, and software.”
Speaking at CES, Califf clarified that the committee is designed to give the FDA advice rather than make any decisions or approve individual digital health products.
The commissioner plans to select nine voting members to make up the committee. Though Califf hasn’t announced any of his selections, he said he’s looking for a “heterogeneous group of experts with different perspectives to give the FDA advice about the field.”
One of the main issues the committee will advise the agency on is bias in AI algorithms. Califf said that looking for biases “should be part of the standard assessment of any algorithm applied in healthcare.”
Biases in AI algorithms can be based on factors such as gender, sex, race, and ethnicity, but there are other types of biases as well, such as those affecting patients living in rural areas, Califf noted.
“Rural people have biases against them and their proximity to care and access to the [digital health] tools we’re talking about,” he said.
Such biases, Califf noted, can lead health systems to choose to open clinics in areas where the profits would be the greatest—not where the need is the highest.
“We have a health system in the US which is structurally designed to advantage people with money and power,” Califf said. “An AI algorithm, or any algorithm, is only going to be as good as the system in which it’s deployed.”
