The bottleneck in health system AI is the front door.
Governance committees are set up to review a handful of vendor tools a quarter. Once staff can build and request agents, they get hundreds of ideas written in hallway language. Front Door turns each one into a decision-ready packet in minutes.
The problem
- Requests arrive as emails and meeting asides. Committee time goes to reconstructing what was asked for, not deciding.
- Risk review is inconsistent. The same idea gets a different answer depending on who reads it first.
- Teams rebuild things the system already has, because nobody checked the library.
- No one captures a baseline at intake, so six months later nobody can prove the value.
The design choice that matters
The AI reads and drafts. The rules decide. Claude turns free text into structured facts and explains its reasoning, but the risk tier comes from a deterministic rubric the governance committee owns and versions. That keeps every decision auditable and consistent, which is what a Chief AI Officer needs to defend to a board or a regulator.
Where it plugs into the Qualified Health platform
Solution LibraryEvery request is matched against validated solutions first. Strong matches take a reuse fast track.
Agent & Workflow BuilderApproved net-new ideas hand off with a structured spec, not an email thread.
Governance & OversightTier sets the guardrails: audit trails, role-based access, human sign-off, post-deployment monitoring.
Outcomes TrackingBaselines and success metrics are captured at intake, so realized value can be compared to what was predicted.
What I'd measure
- Days from request to decision (north star). Target: under 10 business days median.
- Share of requests routed to reuse. Every reuse is a build the system didn't pay for.
- Packet completeness at first committee read. Fewer "come back next month with more info".
- Predicted vs. realized value at 90 days, per requester and per tier. This keeps the value estimates honest.
What I'd build next
- Two-way clarification: the agent asks the requester its missing-info questions in chat before routing.
- Duplicate detection across requests, so five units asking for the same thing become one pilot.
- Committee feedback loop: every override of a tier becomes a proposed rubric change for the committee to accept or reject.
The risk rubric here is illustrative and simplified. Regulatory flags point to where a human review is needed. They are not a legal determination.