A Distributed Optimized Patient Scheduling using Partial Information

Abstract

A software agent may be a member of a Multi-Agent System (MAS) which is collectively performing a range of complex and intelligent tasks. In the hospital, scheduling decisions are finding difficult to schedule because of the dynamic changes and distribution. In order to face this problem with dynamic changes in the hospital, a new method, Distributed Optimized Patient Scheduling with Grouping (DOPSG) has been proposed. The goal of this method is that there is no necessity for knowing patient agents information globally. With minimal information this method works effectively. Scheduling problem can be solved for multiple departments in the hospital. Patient agents have been scheduled to the resource agent based on the patient priority to reduce the waiting time of patient agent and to reduce idle time of resources.

The internal and external customer focused process improvement and the performance analysis studies in healthcare systems

“…However, although tail models and discrete event simulation are applied on more than one department, the interflow between the departments is ignored in these studies (Cohcran & Bharti, 2006;Kapamara et al, 2007;Mageshwari & Kanaga, 2012;Ceschia & Schaerf, 2011). Despite the oral explanations made on the importance of the appointment scheduling practice and necessity of a roadmap for the appointment management system in various activities, the biggest drawback of the literature is the presence of the studies conducting system simulation due to the complicatedness of the system structure.…”

“…For this reason, agent based systems have been generally preferred in recent years (Mageshwari & Kanaga, 2012). Due to the scarcity of the studies conducted in consideration of the interdependencies among the system flows of various departments, the present study attempted to solve the problems by integrating the dynamic systems to the simulation.…”