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Data-Driven Patient Scheduling in Emergency Departments: A Hybrid Robust-Stochastic Approach

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Dr Zhang Meilin, lecturer of the Business Analytics programme at SUSS School of Business (SBIZ), together with her co-authors, have developed a data-driven research approach in healthcare analytics to address the issue of crowding in the Emergency Department (ED).

Titled “Data-Driven Patient Scheduling in Emergency Departments: A Hybrid Robust-Stochastic Approach”, the paper was accepted for publishing at the premier journal of Management Science. It is one of the two flagship journals of INFROMS, the largest society in the world for professionals in the field of operations research (OR), management science, and analytics.

ED crowding and its resulting delays are global issues that have received considerable attention from governments, the public, media, and academic communities. Additionally, ED crowding also compromises the quality of emergency care and puts patients at greater risk of treatment errors.

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