We propose to build a Software as a Service application, which will coexist with the existing Hospital Management System and connected to it via APIs and focus on 4 specific areas of operations such as Operation Theatre scheduling, Staff scheduling, Inventory management and Hospital Managment. The application will apply state of the art machine learning and operations research algorithms to historical data generated in the healthcare system and derive insights from it. It will identify the variability and seasonality of demand in healthcare services and its magnitude. Once such patterns are identified, the algorithms can be tweaked to give weightage of such factors and generate optimum schedules for surgical procedures, staff scheduling and inventory management. 

Not only the system will give optimum solutions to the scheduling or inventory problems it has to be provided an easy to use interface, which is mobile friendly. The end users will be able to make adjustments to the set plan based on approval so that any last minute changes can also be accommodated.