A Distributed Optimized Patient Scheduling using Partial Information

TL;DR

This paper introduces DOPSG, a distributed patient scheduling method that efficiently manages hospital resources and patient flow with minimal global information, adapting dynamically to hospital changes.

Contribution

The paper proposes a novel distributed scheduling approach that operates effectively with limited information, improving hospital resource utilization and patient wait times.

Findings

Reduces patient waiting time

Minimizes resource idle time

Operates effectively with minimal global data

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.