Asynchronous care can improve convenience and access, but a successful model extends beyond adding a new tool. Health systems must design workflows that identify which patients and conditions are appropriate for async care, what data is needed, and how requests are routed. Artificial intelligence can support these processes by automating triage, pre-visit data collection, and routing decisions. Clinicians still determine when a live encounter is warranted, with clear escalation criteria if symptoms require in-person assessment.
The article emphasizes governance, integration with EHRs, privacy, and clinician workload. It notes the need for reliable service-level agreements, timely responses, and audit trails as care shifts from async to live visits. The result should be scalable, patient-centered care that preserves clinical accuracy while expanding reach.
