Projects
A Smart Planning and Optimisation Tool (SPOT) for Healthcare Facilities |
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Objectives:
• Offer an innovative smart simulation-based planning solution
• Optimise healthcare operations towards achieving excellence in service delivery
• Assess investment decisions on increasing capacity or capacity expansion
• Provide generic web-based intelligent agent for healthcare planners
• Optimise healthcare operations towards achieving excellence in service delivery
• Assess investment decisions on increasing capacity or capacity expansion
• Provide generic web-based intelligent agent for healthcare planners
Description:
The project begins with modelling a healthcare facility such as emergency department. Modelling and simulation will allow the identification of system constraints and potential bottlenecks in the existing healthcare facility. Integrating performance management tools with simulation models will help to communicate and gain more insights into strategic initiatives, key objectives, and actions. Modelling and simulation integrated with performance management tools will constitute the first prototype of the proposed tool. Such a prototype will help healthcare managers to run a number of what-if scenarios to examine the impact of various changes and proposed solutions on system performance before their actual implementation. The next phase is to integrate demand forecasting tools within the framework. This is of a great benefit for the management of healthcare facilities to plan the capacity of both elective and non-elective patients. Subsequently, optimisation methods are to be integrated in the framework. This will in return, minimise staff rescheduling disruption, capitalise on resources utilisation (yet to avoid burn-out for staff), reduce running and operating costs using efficient layout, and produce streamlined assignment of resources and staff scheduling. Uncertainties and subjective objectives (e.g. patient satisfaction and quality of services) are taken into consideration and hence artificial intelligence (AI) concepts and algorithms (e.g. fuzzy logic) are to be used. Finally, aligning global system objective with each sub-system objectives and with private utilities of agents (e.g. medical staff and patients) will be achieved by using collective intelligence (COIN) concepts and tools. Moreover, the integration of COIN and AI algorithms (e.g. Reinforcement learning) provide the agility needed by the healthcare system to adapt to changes and events in a real-time manner.
Design:
