Everything that has to be true before a new patient's first visit.
New-patient registration fails in predictable places: an insurance detail nobody verified, a referral requirement discovered at check-in, a consent that was never signed. Each is individually small and each delays the visit or the payment.
What goes wrong today
New-patient registration fails in predictable places: an insurance detail nobody verified, a referral requirement discovered at check-in, a consent that was never signed. Each is individually small and each delays the visit or the payment.
What good looks like
A single list applied to every new patient, checked before the visit rather than at the window, with the gaps surfaced early enough to fix.
Demographics and contact verified, not assumed
Coverage checked and copay known
Referral or PCP requirement resolved
Consents signed and filed
Pharmacy and referring provider captured
What to measure
Agree these before changing anything, so the effect is visible rather than argued about.
Share of new patients fully registered pre-visit
Check-in duration for new vs established
Denials on first claims for new patients
Where we stand: Available now
Captured on the call today; the document half is in development.
Rollout checklist
Document how this is handled today, and by whom.
Put a number on the hours or dollars involved.
Decide which cases must always reach a person.
Agree the metrics you will judge success on.
Frequently asked questions
Do you solve this today?
Captured on the call today; the document half is in development.
How do we know if this is our biggest gap?
The Front Desk Opportunity Scan ranks this against every other area using your own volumes.
Keep going on MedReception.ai
MedFrontDesk.ai is the playbook library. MedReception.ai is the platform that runs it.