AI transparency in medical devices is achievable and imperative, according to new guidance jointly promoted by the FDA, Health Canada and the U.K.’s Medicines and Healthcare products Regulatory Agency.
Issued June 13, the document updates and builds on principles the three bodies outlined in 2021.
The guidance defines transparency in “MLMDs”—for machine learning-enabled medical devices—as “the degree to which appropriate information about a MLMD … is clearly communicated to relevant audiences.”
The guidance asks healthcare AI developers and marketers to consider their technology’s full range of ramifications for patient safety and, by extension, population health. It lays out six questions to help conduct these pre-deployment probes.
Q. To whom is MLMD transparency relevant?
A. Transparency is relevant to those who use the device, such as healthcare professionals, patients and caregivers, and to those who receive healthcare with the device, such as patients, the new guidance states. More:
It’s also relevant to additional parties, including those who make decisions about the device to support patient outcomes, such as support staff, administrators, payers and governing bodies.’
Q. Why is transparency essential to patient-centered care and for the safety and effectiveness of a device?
A. Because the transparent and consistent presentation of information, including known gaps in information, can have many benefits. For starters, transparency “builds fluency and efficiency in the use of MLMDs.”
Further, transparency can foster trust and confidence in the technology. It encourages adoption of and access to beneficial technologies.
Q. What information should be shared?
A. The type of information deemed appropriate to share will vary across the range of MLMDs, the new guidance allows. Appropriateness will depend on the benefits and risks of each MLMD and the needs of intended users.
It’s good practice to provide information that enhances understanding of the device and its intended use. A clear and accurate description of a device generally includes information about its medical purpose and function, the diseases or conditions it’s meant to address, and intended users, use environments and target populations.
Q. Where is this information best placed?
A. Optimally, through the user interface. This should include “all elements of the device that the user sees, hears and touches.” For example, training, physical controls, display elements, packaging, labelling and alarms are all part of the user interface.
A good practice is to optimize use of the software user interface so that the information it conveys is responsive to the user. User needs may be addressed with a variety of modalities, including audio, video, on-screen text, alerts, diagrams, software safeguards and document libraries.
Q. At what point in the MLMD’s implementation should the communication be aimed?
A. “Considering the information needs throughout each stage of the total product lifecycle can support successful transparency,” the document reads. “It may also be helpful to provide timely notifications when the device is updated or modified, or when new information about the device is discovered.”
It may be appropriate to provide targeted information, such as on-screen instructions or warnings at a specific stage in the workflow, such as during high-risk steps, and upon specific triggers, such as when certain input or output features are present.
Q. How best to support the long-term transparency of any given MLMD?
A. Communicating information about MLMDs requires a holistic understanding of users, environments and workflows. These can be addressed by applying human-centered design principles, the guidance maintains.
Transparency-supporting information is optimally accessible and usable when it provides the appropriate level of detail for the intended audience. Plain language may be appropriate in some cases for understanding and usability. In other cases, technical language may be relevant for specialized clinical users.
Read the whole document.
