Utilisation

Finding and Filling Schedule Gaps

The empty twenty minutes at 2:40pm that nobody notices until the day is over.

The empty twenty minutes at 2:40pm that nobody notices until the day is over.

Gaps appear from cancellations, mis-sized visit types and template drift. Individually each is trivial; across a month they are a meaningful share of capacity. Nobody owns finding them because the schedule looks full at a glance.

What goes wrong today

Gaps appear from cancellations, mis-sized visit types and template drift. Individually each is trivial; across a month they are a meaningful share of capacity. Nobody owns finding them because the schedule looks full at a glance.

What good looks like

Gaps surfaced while they can still be filled, matched against a waitlist that knows who wants an earlier slot.

  • Gap detection during the day, not in a monthly report
  • Waitlist matched by visit type and provider
  • Outreach that does not require staff to place calls
  • Template drift flagged when gaps repeat

What to measure

Agree these before changing anything, so the effect is visible rather than argued about.

  • Unfilled slot-minutes per provider per week
  • Share of gaps backfilled
  • Gaps traced to template rather than cancellation

Where we stand: In development

Waitlist backfill is live; systematic gap detection is on the roadmap.

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?

Waitlist backfill is live; systematic gap detection is on the roadmap.

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.

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