Healthcare and medical devices

Healthcare professionals:

Canadian privacy laws and the policies and standards of health regulatory authorities apply to healthcare professionals using AI in their health practices.
Healthcare professionals using AI are responsible for ensuring appropriate safeguards are in place to protect patient data and may be required to obtain express patient consent prior to using AI products in their healthcare practice.

Medical devices:

Health Canada has issued guidance for manufacturers of machine learning-enabled medical devices (MLMDs) when demonstrating the safety and effectiveness of their MLMD as part of an MLMD licence application.
The onus is on manufacturers of MLMDs applying to Health Canada for a medical device licence to declare the use of machine learning in their device and to classify their MLMD as a class II, III or IV medical device.
Health Canada does not prescribe specific supporting information that must form a part of an MLMD application and will apply a risk-based approach to determine compliance with the evidence-based safety and effectiveness requirements.

Health professionals who use AI:

Understand the applicable legal and professional obligations relating to the privacy and confidentiality of patient data when using AI, how patient data will be transferred, stored and used and whether reasonable safeguards are in place to protect patient data.
Be aware of the limitations of certain AI products, such as AI scribes, and review all information generated by AI for accuracy and completeness.
Ensure patients are informed about how AI is used by the healthcare practice and obtain patient consent to use AI when necessary.

Manufacturers of MLMDs:

Abide by “good machine learning practice” when designing, developing, evaluating, deploying and maintaining an MLMD.
Use data to develop an MLMD that is representative of the Canadian population and clinical practice.
Consider whether a predetermined change control plan will be included in the MLMD licence application to provide a mechanism for Health Canada to address cases where the regulatory pre-authorization of planned changes to machine learning systems is needed to address a known risk.
Continue to observe the safety and effectiveness requirements applicable to MLMDs following the pre-market phase throughout the entire product lifecycle.
Develop post-market monitoring plans and include in MLMD licence applications a description of the processes, surveillance and performance monitoring plans, and risk mitigation strategies to ensure ongoing performance.

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