醫療智能體工作流程中的故障偵測與復原

Agentic healthcare systems often coordinate several dependent operations. A failure in one step can prevent the entire workflow from reaching its intended outcome.

Examples include rejected referrals, unavailable services, missing authorization, incomplete records, and repeated communication failures.

A robust agent architecture should distinguish between transient errors, recoverable failures, and conditions that require human intervention.

Transient errors may justify bounded retries with appropriate backoff. Recoverable failures may require additional information or an alternative authorized pathway. Persistent or clinically consequential failures should trigger escalation.

Workflow state should remain observable throughout this process. The system should record completed steps, failed operations, outstanding requirements, and actions already attempted. This reduces the risk of duplicate execution and helps the receiving professional understand what remains to be done.

Most importantly, technical failure should not automatically be treated as resolution of the underlying task. If a patient referral cannot be completed, the system should preserve the unresolved status and route it appropriately.

Call to action: Healthcare AI engineers and clinical informaticians, what failure-handling patterns have you found effective for reliable, auditable agentic workflows?