Towards a systematic approach to resource optimization management in the healthcare domain

Abstract

Increasing patient demand, constrained physical resources, and a rising cost of operations are imperative concerns in healthcare management which require improvements to the way medical services are provided to the public. The urgency of the problem in Ontario, Canada has forced the Provincial Government to put a plan in place to increase access and reduce wait times for major health services including cancer surgery, cardiac procedures, cataract surgery, hip and knee replacements, general surgery, paediatric surgery, and MRI and CT exams (Ontario, 2008). The main directives of the plan include four goals: Operations of the Image Guided Therapy (IGT) Department of the Hospital for Sick Children ("SickKids"), Toronto, Canada have been taken as a sample object in the study. The IGT department provides valuable diagnostic and therapeutic data using procedures that involve different forms of anesthesia or sedation administered to the patients (Khaiter et al., 2015). The study demonstrated that none of the investigated optimization algorithms was able to minimize the IGT schedules with regard to all selected time-based performance criteria. Each algorithm generated schedules which are more efficient from the perspective of a single performance indicator, but not optimal for the others. It is reasonable to assume that specific features of the IGT department (i.e., multi-server environment and variable-length blocks) make the optimization of heir scheduling a complex non-trivial problem requiring a hybrid approach that combines several optimization techniques.