SYSTEMS AND METHODS FOR IMPROVING SCHEDULING INEFFICIENCIES USING PREDICTIVE MODELS

摘要

Systems and methods are presented for scheduling appointments efficiently by generating predictive models using historical appointment data and using these models to predict in advance whether an appointment will be a no-show or a cancellation. The predictive models may be based on logistic regression methods, support vector machines, or neural networks. If the model predicts that an appointment in a particular time-slot will probably be a no-show/cancellation, a scheduling system may decide to double-book that time-slot in order to reduce scheduling inefficiency.