CareThread: Clinical Handoffs with Context

When clinical teams change shifts, unfinished work can lose its owner, timing or context. A pending scan result may be misunderstood as complete, leaving the next team unclear about what still needs attention. CareThread is a voice-guided clinical handoff simulation that turns spoken conversations into a shared, reviewable plan. It captures unfinished tasks, clinician-stated owners, timing, conditions and uncertainty, with each detail linked to its source statement. Missing information stays unresolved until someone clarifies it. The receiving participant reviews and acknowledges the plan. Acknowledging responsibility does not mark the task complete. When important information changes, CareThread creates a new revision and requires renewed acknowledgment. AssemblyAI's managed Voice Agent API handles speech and conversation. Final transcripts pass to a server-side AssemblyAI LLM Gateway planner, which proposes structured updates. Application rules check these proposals against source statements and current revisions before saving them. Built with Next.js, React and TypeScript and hosted on Vercel, the prototype includes a guided synthetic scenario, live voice interaction, revision history, source evidence, JSON export and printable handoffs. Our initial audience is clinical educators and simulation centers practicing clearer team communication. The project passes 80 automated software checks and one synthetic spoken integration test. Browser microphone-device testing and clinical evaluation remain outstanding. CareThread is a training prototype using synthetic data. It does not diagnose, prescribe or authorize discharge.