FILE.003 // HEALTHCARE//LABS
Governed AI for the LIS
Built the governance framework first — roles, review gates, audit logging — then took scoped AI use-cases into a live laboratory information system.
A MEDICAL LABORATORY GROUP // DIAGNOSTICS // AI IN PRODUCTION
CHALLENGE
The group wanted AI inside its laboratory information system, but every initiative stalled at the same wall: no framework said who approves a model, how a decision gets reviewed, or what has to be logged. Without those answers, nothing was allowed near production.
QUOTE
"They didn't start with the model. They started with who signs off — and that's why this one made it to production."
APPROACH
- > Built the governance frame before any model: roles, review gates, and audit logging agreed with quality and clinical leadership.
- > Scoped the first AI use-cases deliberately narrow, each with a named owner and a defined escalation path.
- > Instrumented every AI-touched decision with the audit trail the framework demands, end to end through the LIS.
OUTCOME
- > AI runs in production with a sign-off trail behind every use-case.
- > Clinicians keep final authority — the system recommends, people decide.
- > New AI proposals now follow a repeatable intake process instead of restarting the debate.