We analyze a discrete multi-server model for scheduling customer arrivals under no-shows. The challenge is to assign customers to time slots so that the service system utilizes its resources efficiently and customers experience short waiting times. We provide theoretical and heuristic guidelines for an effective practice of appointment overbooking in order to offset no-shows. Recursive and expl...

The number of no-shows has a significant impact on the revenue, cost and resource utilization for almost all healthcare systems. In this study we develop a hybrid probabilistic model based on logistic regression and empirical Bayesian inference to predict the probability of no-shows in real time using both general patient social and demographic information and individual clinical appointments a...

We develop a sequential clinical scheduling method for patients with general service time distributions. Patients are scheduled during a call-in period that precedes the scheduled consultation session. The session is divided into a set of time intervals called “slots”. When a patient calls, the scheduler assigns the patient to a suitable slot if one exists. Each scheduled patient has a probabil...

the goal of this prospective study was to determine die prevalence of certain surgical findings in iranian patients with appendicitis in one of our surgical centers, including: position of the appendix, rate of true appendicitis, perforation, and peritonitis. duplication was observed in 4%, surface exudate in 52%, gangrenous necrosis in 27%, swelling in 79%, appendix in the left lower quadrant ...