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Ai and virtual-care workflows: a practical guide collection

Explore AI and virtual-care workflows through four focused guides for Canadian readers. Start with a defined question, examine the method and keep its limitations visible.

Ai and virtual-care workflows learning and planning

Define the intended use

Distinguish administrative support from a tool intended to inform clinical decisions. The task, users and setting determine what evidence and review are needed.

Keep qualified people responsible

Describe who reviews an output and how an uncertain or unsuitable result is escalated. A technical demonstration is not proof that a system is appropriate for patient care.

Plan for practical constraints

Review connectivity, accessibility, training and the handoff between remote and in-person services. Test an operational fallback before a workflow depends on it.

Protect information throughout

Map what information is collected, where it is processed and who can access it. Applicable requirements depend on the organisation and jurisdiction, including relevant health-information rules.

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Primary reference: Health Canada: good machine learning practice for medical devices.