Trial Information

Reducing VA No-Shows: Evaluation of Predictive Overbooking Applied to Colonoscopy

Patient "no-shows" are especially common in VA gastrointestinal (GI) endoscopy units, where
both open-access endoscopy scheduling and patient dislike of procedures contribute to high
absenteeism. In this proposal, investigators use endoscopy as a case example to evaluate a
predictive overbooking model derived using patient-level predictors of absenteeism. The
no-show overbooking intervention employs a logistic regression model that uses patient data
to predict the odds of no-showing with 80% accuracy. These projected no-show appointments
will be overbooked by clerks for patients who agree to join a "fast track" short-call line.
However, patients in the "fast track" assume a small risk of service denial on the day of
their overbooking in case of inaccurate predictions. If this occurs, the patient is
guaranteed service in the next available position and is assured of having a shorter wait
time. By rapidly processing upper endoscopy patients and moving them out of traditional
slots, investigators predict more scheduling slots would become available for patients
awaiting colonoscopy. Investigators propose to conduct a prospective, 24-month, interrupted
time series (ITS) trial in the WLAVA GI clinic endoscopy unit. During intervention periods,
investigators will activate the no-show predictive overbooking strategy described above.
Investigators will compare outcomes between scheduling strategies, including differences in
percent utilization of capacity (primary outcome), number of Veterans served, mean patient
lag time between scheduling and procedure, number of unexpected service denials ("bumps")
from no-show predictive overbooking, and direct costs of care. Investigators will analyze
differences using both traditional univariate and multivariate approaches, and using
autoregressive integrated moving average (ARIMA) analyses to adjust for auto-correlations in
ITS data.