Dental · Patient retention

Hygiene reappointment rate

The share of patients seen in hygiene who leave with their next hygiene visit already on the schedule. It is a simple, early signal of whether patients will keep coming back.

Plan your metrics

What it is

Hygiene reappointment rate is the share of patients seen in hygiene during a period who have a future hygiene appointment booked.

Practices define "booked" in different ways. The strictest rule counts only patients booked before they leave the office. A looser rule also counts patients booked within a few days by follow-up.

Why operators track it

  • Retention. A patient with a next visit booked is more likely to return than one told to call later.
  • Schedule planning. Reappointments fill the hygiene schedule months ahead.
  • Front office follow-up. The patients who were not booked make a clear call list.
  • Treatment. Hygiene visits are often where treatment needs are found, so missed visits can mean missed care. (This is a general observation, not a measured figure.)

How it is calculated

Hygiene reappointment rate = hygiene patients with a future hygiene appointment ÷ hygiene patients seen

  • Count unique patients, not visits.
  • Decide the rule for "booked": before leaving, or within a set number of days.
  • Count only future appointments of a hygiene type.

Worked example

In one example month, 400 patients were seen in hygiene. 352 left with their next hygiene visit booked. The front office booked 28 more within 7 days. 20 were not booked.

One example month: 400 hygiene patients seenBooked before leaving: 352Follow-up: 28Not booked: 20Rule A: booked before leaving88.0%352 ÷ 400Rule B: booked within 7 days95.0%(352 + 28) ÷ 400The 20 not bookedare the follow-up list for thefront office this week.
Example data Same month, two rules. Rule A is the one used on this page. State which rule a report uses.

How to read it

  • Look at the gap between the two rules. A big gap means booking is happening by follow-up rather than at checkout.
  • Look by hygienist and by day. Low rates on certain days can point to checkout workflow, not the clinician.
  • Patients who should not be counted. Patients moving away or transferring care lower the rate. Some practices exclude them. Say if you do.
  • We do not publish a benchmark. Rates depend on the patient base and the rule used.

Definitional choices and common pitfalls

  • When booking counts. Before leaving, same day, or within N days. Pick one and label it.
  • Patients or visits. Use unique patients so a patient seen twice is not counted twice.
  • Which visit types count as hygiene. Prophylaxis, periodontal maintenance, and others. Write down the list of procedure codes or appointment types.
  • Exclusions. Decide whether to exclude patients who are moving, deceased, or referred elsewhere.
  • Cancelled later. A booked appointment may be cancelled the next week. The rate measures booking at the time, not attendance.

How different roles use it

Role How they use it
Owner dentist Watches the trend as a sign of patient retention.
Office manager Reviews it weekly, works the unbooked list, and coaches checkout.
Hygienist Sees their own rate and asks patients to book before leaving.
DSO regional manager Compares locations using the same rule.

Questions it answers

  • What share of hygiene patients left with a next visit booked?
  • Which patients need a follow-up call this week?
  • Which days or providers have the lowest rate?
  • Is the rate improving after a checkout change?

How to present it in a report

  • A headline rate with the rule stated, such as "booked before leaving".
  • A monthly trend line.
  • A table by hygienist and by location.
  • A linked list of unbooked patients for the front office.

Data you need

Fields

Field What it means Example value
Patient A unique patient ID Patient 40112
Hygiene visit A completed visit of a hygiene type, with date and provider Oct 14, K. Lee, D1110
Future appointment Any later appointment, with its type and date Apr 15, recall
Appointment created at When the future appointment was booked Oct 14, 10:42
Checkout time When the patient left, if recorded Oct 14, 10:45
Patient status Active, inactive, moved, or deceased Active
Location The office Maple Grove

What the raw data looks like

Example data A few rows as they might come out of the source system.

Patient Hygiene visit Hygienist Next hygiene appt Booked at Status
40112 Oct 14 K. Lee Apr 15 Oct 14, 10:42 Active
40187 Oct 14 K. Lee Apr 22 Oct 17, 2:10 Active
40203 Oct 14 M. Ortiz none Active
40219 Oct 15 M. Ortiz none Moved

Where this data usually lives

  • Practice management system (PMS) holds the schedule, procedures, fees, adjustments, treatment plans, and payments. For example: Dentrix and Dentrix Ascend (Henry Schein One), Eaglesoft (Patterson Dental), Open Dental.
  • Insurance clearinghouse and eligibility tools hold claims, remittances, and payer details, which explain write-offs.
  • Imaging systems hold x-rays and clinical images. They are rarely needed for these metrics.
  • Payroll or HR may hold hours actually worked, if the schedule does not.
  • DSO data warehouses combine data from many locations, sometimes from more than one PMS.

Common data gaps and traps

  • Booked time not stored. Without the appointment created time, you cannot tell booked-before-leaving from booked later.
  • Recall vs appointment. A recall reminder is not a booked appointment. Make sure you count real appointments.
  • Appointment types not consistent. Hygiene may be booked under several types. List them.
  • Inactive patients not marked. Patients who left the practice stay in the denominator.

FAQ

Is this the same as recall rate?
Not always. Some practices use "recall" for reminders sent. Reappointment means an appointment is actually booked.
Should I count patients or visits?
Patients. A patient seen twice in a month should count once.
What window should I use for booked later?
Pick one, such as 7 days, and label it. Show the strict rule next to it if you can.
For your data teamFormula variants, tables, SQL sketch, and dashboard spec

Formula details

seen        = DISTINCT patients with a completed hygiene visit in period
booked      = seen patients with a future hygiene appointment
              where appointment.created_at <= checkout_time        -- rule A
              (or created_at <= visit_date + :days)                -- rule B
rate        = COUNT(booked) / COUNT(seen)

Worked example detail

Count
Hygiene patients seen 400
Booked before leaving 352
Booked within 7 days by follow-up 28
Not booked 20
Rule A rate 352 / 400 = 88.0%
Rule B rate 380 / 400 = 95.0%

Tables and fields

Table Fields Notes
appointments appt_id, patient_id, provider_id, appt_type, start_at, created_at, status
procedures patient_id, provider_id, cdt_code, status, completed_at To identify hygiene visits
patients patient_id, status, location_id Exclusions

SQL sketch

WITH seen AS (
  SELECT DISTINCT a.patient_id, a.location_id, a.provider_id, a.start_at::date AS visit_date,
         a.checkout_at
  FROM appointments a
  WHERE a.appt_type IN (:hygiene_types) AND a.status = 'completed'
    AND a.start_at >= :start AND a.start_at < :end
),
booked AS (
  SELECT DISTINCT s.patient_id
  FROM seen s JOIN appointments f
    ON f.patient_id = s.patient_id AND f.appt_type IN (:hygiene_types)
   AND f.start_at > s.visit_date
   AND f.created_at <= COALESCE(s.checkout_at, s.visit_date + INTERVAL '1 day')
)
SELECT COUNT(b.patient_id)::numeric / NULLIF(COUNT(DISTINCT s.patient_id), 0) AS reappointment_rate
FROM seen s LEFT JOIN booked b USING (patient_id);

As a dashboard card

  • Card type: KPI with the rule in the subtitle, a monthly trend, and a table of unbooked patients.
  • Measures: seen, booked, reappointment_rate.
  • Dimensions: hygienist, location, day of week, period.

Common mistakes

  • Counting recall reminders as appointments.
  • Counting visits instead of patients.
  • Not stating which booking rule is used.

Version 1.0 · Last reviewed 2026-10-20 · Machine-readable definition