Preventing Endoscopy Clinic No-Shows: Prospective Validation of a Predictive Overbooking Model.

Abstract

Patient absenteeism for scheduled visits and procedures ("no-show") occurs frequently in healthcare systems worldwide, resulting in treatment delays and financial loss. To address this problem, we validated a predictive overbooking system that identifies patients at high risk for missing scheduled gastrointestinal endoscopy procedures ("no-shows" and cancellations), and offers their appointments to other patients on short notice. We prospectively tested a predictive overbooking system at a Veterans Administration outpatient endoscopy clinic over a 34-week period, alternating between traditional booking and predictive overbooking methods. For the latter, we assigned a no-show risk score to each scheduled patient, utilizing a previously developed logistic regression model built with electronic health record data. To compare booking methods, we measured service utilization-defined as the percentage of daily total clinic capacity occupied by patients-and length of clinic workday. Compared to typical booking, predictive overbooking resulted in nearly all appointment slots being filled-2.5 slots available during control weeks vs. 0.35 slots during intervention weeks, t(161)=4.10, P=0.0001. Service utilization increased from 86% during control weeks to 100% during intervention weeks, allowing 111 additional patients to undergo procedures. Physician and staff overages were more common during intervention weeks, but less than anticipated (workday length of 7.84 h (control) vs. 8.31 h (intervention), t(161)=2.28, P=0.02). Predictive overbooking may be used to maximize endoscopy scheduling. Future research should focus on adapting the model for use in primary care and specialty clinics.