A method for clustering surgical cases to allow master surgical scheduling

Master surgical scheduling can improve manageability and efficiency of operating room departments. This approach cyclically executes a master surgical schedule of surgery types. These surgery types need to be constructed with low variability to be efficient. Each surgery type is scheduled based upon its frequency per cycle. Surgery types that cannot be scheduled repetitively are put together in so-called dummy surgeries. Narrow defined surgery types, with low variability, lead to a large volume of such dummy surgeries that reduce the benefits of a master surgical scheduling approach. In this paper we propose a method, based on Ward's hierarchical cluster method, to obtain surgery types that minimizes the weighted sum of the dummy surgery volume and the variability in resource demand of surgery types. The resulting surgery types (clusters) are thus based on logical features and can be used in master surgical scheduling. The approach is successfully tested on a case study in a regional hospital.