DENTAL REVENUE LEAKAGE

Not every lost dental patient is a marketing problem.

Most international dental revenue is lost inside the operation, after the inquiry has already been paid for.

PFIPFI for Dental

Marketing is measured obsessively; the operation that receives the result is often measured not at all. This page maps eight places where international dental patients stop moving, what usually causes each one, and which metric makes it visible. Causes are described as possibilities to investigate — not as diagnoses, and not as guaranteed financial outcomes.

Eight leakage points

Symptom · possible operational cause · metric to watch · how PFI adds visibility.

Inquiry Leakage

Symptom: inquiries answered late or never. Possible cause: no single queue across channels and shifts. Metric: first-response time and unanswered inquiry count. PFI: one intake queue with owner and response clock.

Information Leakage

Symptom: cases stuck without X-rays or photos. Possible cause: requests made once, in a chat thread, with no owner. Metric: case-information completion rate. PFI: per-case checklist with request state and waiting time.

Clinical Leakage

Symptom: complete cases waiting days for an opinion. Possible cause: review depends on one clinician's inbox. Metric: clinical-review completion time. PFI: routing, queue and turnaround visibility per reviewer.

Treatment Plan Leakage

Symptom: reviewed cases that never become a documented plan. Possible cause: no defined handover from clinical decision to patient proposal. Metric: treatment-plan generation rate. PFI: plan objects with state and owner.

Follow-up Leakage

Symptom: patients who simply stop replying and are never contacted again. Possible cause: follow-up depends on memory and workload. Metric: follow-up coverage. PFI: stage-aware follow-up queue and coverage reporting.

Booking Leakage

Symptom: agreed patients who never confirm dates or deposits. Possible cause: no explicit booking stage between yes and calendar. Metric: quote-to-booking rate and deposit rate. PFI: booking and deposit state per patient.

Arrival Leakage

Symptom: booked patients who do not arrive. Possible cause: no contact between deposit and travel date. Metric: arrival rate. PFI: pre-arrival checkpoints and travel-state visibility.

Completion Leakage

Symptom: multi-stage treatments that stop after the first visit. Possible cause: no recall owner once the patient flies home. Metric: treatment completion and second-visit rate. PFI: recall queues built from treatment history.

How PFI adds visibility

Visibility first. Operational change follows from what the clinic can finally see.

State instead of anecdote

Every open case sits in a defined stage with an owner and a next action date.

Value attached to stage

Open treatment value is visible per stage, so the largest silent loss is obvious.

Coverage, not activity

The question stops being “are we busy?” and becomes “what share of open cases were actually contacted?”.

Metrics that expose leakage

Unanswered inquiries
18 / mo

Inquiries with no meaningful reply.

Cases missing imaging
31

Qualified patients blocked before clinical review.

Plans with no response
41

Sent plans with no patient reply and no next contact.

Open treatment value
€326,000

Value represented by plans that have not converted.

Follow-up coverage
62%

Share of open cases contacted within their interval.

Arrival gap
12%

Bookings that did not arrive.

Sample Data

Frequently asked questions

Does PFI guarantee recovered revenue?

No. PFI makes operational loss visible and gives the team a structure to act on it. Financial outcomes depend on the clinic's clinical capacity, pricing and execution.

Are these leakage figures benchmarks?

No. Every number shown on this site is illustrative sample data. Your own figures come from your own operation.

Where should a clinic start?

Usually at the largest single drop-off. The simulator identifies it from your inputs so the first fix is the one with the most visible impact.

Is leakage always an operational problem?

No. Pricing, market fit and case mix all play a role. The point is to separate what the operation controls from what it does not.

Continue exploring

Find your largest drop-off.

Enter your own numbers and see which stage is costing the most visible treatment value.