Research question and scope
Published September 4, 2026.
This study asks how often a reschedule confirmation matches the final authoritative booking and which mismatches are associated with repeat contact or missed service. It is a local quality design, not a universal estimate.
Define one journey from the first change request through the scheduled service and a follow-up window. Join request, original slot, temporary hold, cancellation, new booking, message delivery, provider change, customer contact, and attendance events. Normalize time zones while retaining the original local time.
Measures and quality controls
The primary measure is exact agreement on date, time zone, location or connection method, service, and guaranteed provider fields. Secondary measures include duplicate confirmations, obsolete reminders, repeat contact, and missed appointments. Publish field-level errors as well as complete-message accuracy.
Reconcile a sample against calendar audit logs and delivered messages. Annotate outages, daylight-saving changes, bulk schedule moves, and policy releases. The NIST Privacy Framework can guide data minimization for appointment records.
Analysis and limitations
Start with journey counts and missingness. Stratify by booking channel, service type, lead time, location, and whether the original slot was released before the replacement was secured. Review incorrect messages with a fixed taxonomy.
Availability, urgency, customer preference, provider absence, and external calendar synchronization may affect both rescheduling complexity and outcomes. A missed appointment does not by itself prove a confirmation defect. Some customers receive a correct message but do not open it. Observational analysis cannot establish causality.
Use results to test one confirmation or calendar control. Monitor exact agreement, repeat contact, missed service, accessibility, and additional manual work.