An integrated analysis of capacity allocation and patient scheduling in presence of seasonal walk-ins

This study analyzes two decision levels in appointment system design in the context of clinics that face seasonal demand for scheduled and walk-in patients. The macro-level problem addresses access rules dealing with capacity allocation decisions in terms of how many slots to reserve for walk-ins and scheduled patients given fixed daily capacity for the clinic session. The micro-level problem addresses scheduling rules determining the specific time slots for scheduled arrivals. A fully-integrated simulation model is developed where daily demand actualized at the macro level becomes an input to the micro model that simulates the in-clinic dynamics, such as the arrivals of walk-ins and scheduled patients, as well as stochastic service times. The proposed integrated approach is shown to improve decision-making by considering patient lead times (i.e., indirect wait), direct wait times, and clinic overtime as relevant measures of performance. The traditional methods for evaluating appointment system performance are extended to incorporate multiple trade-offs. This allows combining both direct wait and indirect wait that are generally addressed separately due to time scale differences (minutes vs. days). The results confirm the benefits of addressing both decision levels in appointment system design simultaneously. We investigate how environmental factors affect the performance and the choice of appointment systems. The most critical environmental factors emerge as the demand load, seasonality level, and percentage of walk-ins, listed in the decreasing order of importance.