Aftercare

• 

• 

  landing page

• 

  ai voice call

• 

  dashboard

Inspiration

1 in 5 hospital patients are readmitted within 30 days of leaving the hospital, and Medicare has been fining hospitals for it since 2012. The fix is obvious: just call patients after they leave. After discharge, someone still needs to Identify patients who need follow-up.

What it does

Once a patient is discharged - the AI calls with a follow-up call on day 1, day 3, and day 7, asking structured questions shaped to their specific procedure. A knee replacement patient gets asked different questions than a cardiac patient. If we hear any red flags—like a patient mentioning chest tightness, scoring their pain an 8, or saying they've stopped their medication—that's where we bring in the professionals for an immediate callback. For everyone else, it’s a smooth and reassuring check-in, all neatly logged in their record, without using up any staff time. Every call syncs to the hospital's software - giving clinical teams a complete post-discharge picture.

How we built it

Created Backend Agent in google Cloud run

• Call scheduling agent: - . Used Gemini, and the tools available from the Call-E MCP server
• end call transcription gemini and call-e, conversation agent

Challenges we ran into

enrolling patients in a follow-up sequence. Dockerization of agents on cloud run was tricky .coordination of real time response to app layer involved managing agents get run call . Turning discharge int follow-up calls.

Accomplishments that we're proud of

A working prototype with a full frontend. backend deployed on cloud run deploy.

What we learned

Building taught us that healthcare AI lives or dies on followups.

What's next for Aftercare

Built With

• call-e
• cloud-run
• fastapi
• gemini-3.5
• google-adk
• python
• react