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This paper aims to ascertain the optimal number of consultation rooms to operate so that patients with high severity medical conditions are attended to promptly, yet with capacity to spare for low severity patients but without fully providing for this latter group to be seen within a very short duration of time upon arrival. The research methodology is based on the concepts from simulation-based lean...
We propose to use a new approach to model the polio spread and prevention. The propose approach is inspired from P2P network. The approach is based on the graph transformations, which is a visual rule based formalism. The graph transformation has properties for stochastic modelling and simulation. In order to develop a stochastic model using graph transformation, we consider polio spread and prevention...
Hospitals are huge and complex systems. However, for many years, the management was commonly focused on improving the quality of the medical care, while less attention was usually devoted to operation management. In recent years, the need of containing the costs while increasing the competitiveness along with the new policies of National Health Service hospital financing forced hospitals to necessarily...
This paper describes an analytical framework for establishing requisite bed capacity when cohorting paediatric patients by defined characteristics. As guided by the analytical framework, a simulation-based lean six-sigma approach is applied to analyze the operational data and processes when cohorting patients, and opportunities are identified for process improvement. The analytical framework is illustrated...
The effective use of data within intensive care units (ICUs) has great potential to create new cloud-based health analytics solutions for disease prevention or earlier condition onset detection. The Artemis project aims to achieve the above goals in the area of neonatal ICUs (NICU). In this paper, we proposed an analytical model for the Artemis cloud project which will be deployed at McMaster Children’s...
High speed physiological data produced by medical devices at intensive care units (ICUs) has all the characteristics of Big Data. The proper use and management of such data can promote the health and reduces mortality and disability rates of critical condition patients. The effective use of Big Data within ICUs has great potential to create new cloud-based health analytics solutions for disease prevention...
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