Dynamic resource allocation to improve emergency department efficiency in real time

• We develop a new dynamic scheduling model for the emergency department.
• The model proposes two layers of scheduling; patient-bed assignment and task-resource allocation.
• A dynamic algorithm is developed to generate fast solutions for the real-time environment.
• Novel extensions are made to disjunctive graph methods for flexible job shops.

A dynamic scheduling framework is proposed to provide real-time support for managing the scarce resources of the Emergency Department. The theory of parallel machine and flexible job shop environments are integrated to schedule patient-bed assignments and task-resource allocations. The solution method incorporates dispatch heuristics, disjunctive graph methods and meta-heuristic search in order to provide fast solutions that respond to unscheduled arrivals, competing priorities and heterogeneous patient care needs. The dynamic algorithm is compared against static solutions and is shown to achieve solutions within 5 percent of the best bound. The dynamic schedule updates are completed within 2 seconds of information updates. This level of decision support, when implemented within a patient management system, can reduce the clinicians’ workload by managing prioritized task lists such that the clinical staff is more free to focus on delivering clinical care.