The operational management of allocating beds to patients is a challenging task, and an important component of a hospital’s processes. Given the lean bed capacity that LCX hospital had experienced in the past few months, John Teo, the director of the Bed Management Unit (BMU), and Doe Claris, the second in lead, were tasked to set up a workgroup with relevant stakeholders to examine the current policies and strategies of BMU, and seek out new and innovative solutions to improve the process of bed allocation to in-patients. Teo and Claris hope to improve the bed management system using the predictive capabilities of data analytics and mathematical modelling tools.
Through this case, students are expected to derive a suitable model to determine a bed allocation policy. The case reinforces the students’ skills in data processing, mathematical modelling, and numerical computation. Concepts and techniques covered include spreadsheet modelling, Linear Programming (LP), Optimisation, and Post-optimality analysis (such as shadow prices, sensitivity report and resolving model).
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