A method for clustering surgical cases to allow master surgical scheduling

Master surgical scheduling can improve the manageability and efficiency of operating room departments. This approach cyclically executes a master surgical schedule of surgery types. 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. Narrowly defined surgery types, with low variability, lead to many of such dummy surgeries, which reduces 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 minimize 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.

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