Data-driven Appointment Scheduling in the Presence of No-shows

Presented by Michele Samorani -- Alberta School of Business and Linda LaGanga -- Mental Health Center of Denver

In this session, Samorani and LaGanga Grabau consider the problem of scheduling outpatient appointments in the presence of no-shows. Predictive analytics is used to forecast the show outcome of appointment requests, which are optimally scheduled given this prediction. Descriptive analytics is used to interpret the solutions of the scheduling problem in order to derive a heuristic policy, which, depending on the show rate and on the prediction quality, outperforms the reigning scheduling policy, open access. Prescriptive analytics is used to identify the conditions under which one should adopt overbooking or same-day scheduling.

2012 Annual Meeting Presentations -- Innovation in Analytics Award Semi-Finalists

To learn more, please visit