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Overview of Patient Metrics

Namitha Elizabeth Smart
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Let's take a look at the Patient Metrics.

  • Active Patients: This metric represents the total number of patients who are marked as active in the practice management system. Only patients explicitly marked with the active flag are considered. It excludes all non-patient records and any entries flagged as duplicates, inactive, or merged.
    • Inclusions:
      • Patients marked with the active flag
      • Valid patient records only (i.e., excluding non-patients)
    • Exclusions:
      • Patients marked as inactive
      • Duplicate records
      • Merged records
      • Non-patient 
    • Use Case: This metric is used to monitor the current base of valid, active patients available for recall, scheduling, and clinical engagement.
    • This is an all time metric. When a date range is applied it is based on the active patients as of the end date of the selected period.
  • Patient Growth Rate: This metric measures the net change in the active patient population by evaluating additions and losses over a selected time range.
    • It is calculated using the following formula: Patient Growth Rate = (New Patients + Reactivated Patients − Inactive Patients) / Total Active Patients at End of Period × 100
    • Reactivated Patients: Refers to previously inactive patients who became active again by checking out during the selected period.
    • Inactive Patients: Patients who were marked as inactive during the selected time frame.
    • Total Active Patients: The count of patients with the active flag at the end of the selected period.
    • Use Case: This metric is used to monitor the overall health of patient acquisition and retention. A positive growth rate indicates successful outreach and retention strategies, while a negative or flat growth rate may signal issues in scheduling, engagement, or patient satisfaction.
  • Patient Attrition Rate: This metric measures the rate at which patients are lost or marked as inactive during a given time period. In most cases, inactivation is due to prolonged inactivity (e.g., no visits within a configured time frame - set within Practice Settings), though it may also result from manual updates. 
    • Formula: Patient Attrition Rate = (Number of Patients Marked Inactive During Period / Total Active Patients at Start of Period) × 100
    • Inclusions: All patients flagged as inactive within the selected date range
    • Exclusions:
      • Patients marked as inactive before the selected range
      • Duplicate or merged patient records
      • Non-patient profiles
    • Use Case: Helps practices monitor patient retention performance. A high attrition rate may signal the need for stronger recall workflows, improved communication, or satisfaction follow-up efforts.
  • Patient Reactivation Rate: This metric measures how effectively the practice re-engages lapsed patients. It calculates the percentage of patients who were previously marked as inactive but had their status changed back to active during the selected time period. It excludes new patients and considers only those whose last known status prior to the date range was inactive.
    • Formula: Patient Reactivation Rate = (Reactivated Patients / Total Active Patients at End of Selected Date Range) × 100
    • Inclusions:
      • Distinct patients reactivated (status changed from inactive to active) during the selected date range
      • Only patients who were previously inactive
    • Exclusions:
      • New patients
      • Patients whose status change did not involve reactivation
      • Duplicate, merged, or non-patient records
  • Patients Visit: This metric is based on configuration set in Insights > Settings > Metric Customization.
    • Patient Visit can be configured based on:
      • Treatment completed
      • Appointment checked out or
      • Either of the above
    • With the configuration, patient visit is counted when either treatment is completed / appt is checked out or any of the two is completed. The customization allows to exclude certain codes from counting towards patient visit as well.
    • This metric is based on DOS/Appt Date.

  • New Patient Visit: This metric counts the number of patients who completed their first visit within the selected date range.

    • A new patient visit is defined based on a back-end setup that identifies either the patient’s very first completed procedure code or completion of one or more specific procedure codes designated to mark new patient visits. Only patients who have reached the ‘completed’ status for these qualifying visits are included.
    • Setup can be based on: 
      1. Any code logic: The first code completed against the patient is considered as their first visit.
      2. Specific code logic: One of the specified codes have to be completed to consider as their first visit. Until one of these codes is completed, the patient is considered a new patient and is pending their first visit.
    • This metric helps dental practices accurately track new patient acquisition and monitor growth by measuring how many new patients completed their initial care appointment within the given timeframe.
       
  • New Patient Visit/Day: This metric calculates the daily average of new patients who had their first visit (based on configured criteria) during the specified period. A 'new patient' is determined using system-configured rules—either based on their first completed code or a defined set of codes (e.g., D0150).
    • Formula: New Patient Visit/Day = Total New Patients Visit / Number of Days in Date range where there is patient visit.
    • New Patient Visit: Number of patients who had their first visit in the selected date range.
    • Number of days: Number of days in the selected date range where there was a patient visit.
    • Patient Visit: Based on settings, a completed code or checked-out appointment or both can be considered for patient visit.
  • Walkout Retention: This KPI measures the effectiveness of the front desk and scheduling team in securing future appointments at the time patients complete their current visit (walkout). It tracks patients seen during the selected date range who have subsequently scheduled appointments that include a specified subset of procedure codes.
    • Users can configure two code filters:
      (A) Codes that patients must have completed within the selected date range (completed status, excluding deleted or migrated codes).
      (B) Codes to check for in patients’ future appointments.
    • The metric identifies patients who had specific codes (A) completed during the selected date range (based on DOS) and checks if these patients have future appointments containing codes (B). If the selected date range excludes the current day, patient is considered as they have future appointment if the patient has a code completed after the DOS of the code in (A). If no code filtering is applied, walkout retention calculates percentage of all patients who had an appointment in the selected date and has a future appointment.
    • This metric can also highlight appointments scheduled without procedure codes attached, which may indicate potential gaps in scheduling or coding workflows.
    • Use Cases:
      • Assessing front desk performance in scheduling recall/hygiene appointments at checkout
      • Monitoring patient engagement and adherence to recommended care schedules
      • Identifying scheduling or coding process inefficiencies
  • Hygiene Patient Visit: This metric is based on configuration set in Insights > Settings > Metric Customization.
    • Hygiene Patient Visit can be configured based on:
      • You can configure the set of codes that needs to be considered as a hygiene visit.
      • Any patient who has one of these codes completed will be considered as a hygiene patient.
      • Based on DOS.
  • Perio Visit %: The Perio Visit KPI evaluates how effectively the practice is identifying and treating periodontal conditions within the hygiene department.
    • Distinct patients who completed any of the perio codes (D4341, D4342, D4355, D4381, D4346, D4921, D4910) ÷ distinct patients who had a hygiene visit.
    • The KPI shows how frequently periodontal needs are being diagnosed and treated relative to the hygiene population.
    • A higher Perio Visit percentage may indicate strong periodontal assessment protocols, good case acceptance, and proper coding. A lower percentage may signal underdiagnosis, missed treatment opportunities, or gaps in hygiene-provider calibration.

Practices can use this simple guide to learn all about patient related metrics.

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