Industrial Engineering

Biography

Biography: Avigdor Gal

Abstract

Service systems play a central role in the health sector. The provisioning of services is realized by a service process that can be broadly captured by a set of activities that are executed by a service provider and designated to both attain a set of organizational goals and add value to customers. Service processes can be classified by the amount of interactions between service providers and customers and the level of demand predictability and capacity flexibility. A service can be multi-stage, in the sense that service provisioning involves a series of interactions of a customer with a provider or specific resources at a provider’s end. Further, a process can be scheduled, meaning that the number of customers to arrive is known in advance up to last moment cancellations and no-shows. Then, customers follow a predefined series of activities with every activity having a planned starting time for its execution, duration and a set of involved resources. Multi-stage scheduled processes are encountered for instance in outpatient clinics where various types of treatments are provided as a service to patients. Here, a schedule determines when a patient undergoes a specific examination or treatment. In this talk, we shall illustrate the impact big data has on the healthcare sector by analyzing RTLS-based data from a real-world use-case of scheduling in a large outpatient oncology clinic. We shall demonstrate the usefulness of the proposed methods in detecting operational bottlenecks in the schedule specifically longer-than-planned synchronization delays and diagnosing the root-cause to those problems.