Thursday, 29 April, 17:00 CEST *Carri Chan,* Columbia University Prediction-Driven Surge Planning with Applications in the Emergency Department <http://mailsender.luiss.it/lists/lt.php?id=cRpQBwwLSAULAAdOVgFdBQs> Optimizing emergency department (ED) nurse staffing decisions to balance the quality of service and staffing cost can be extremely challenging, especially when there is a high level of uncertainty in patient-demand. Increasing data availability and continuing advancements in predictive analytics provide an opportunity to mitigate demand-rate uncertainty by utilizing demand forecasts. In this work, we study a two-stage prediction framework that is synchronized with the base (made months in advance) and surge (made nearly real-time) staffing decisions in the ED. We quantify the benefit of the more expensive surge staffing. We also propose a near-optimal two-stage staffing policy that is straightforward to interpret and implement. Lastly, we develop a unified framework that combines parameter estimation, real-time demand forecasts, and staffing in the ED. High fidelity ED simulation experiments demonstrate that the proposed framework can reduce staffing costs by 8% – 17% while guaranteeing timely access to care. Joint work with Jing Dong and Yue Hu. Discussants: Vahid Sarhangian and Julien Grand-Clément This is the link to the Virtual Room <http://mailsender.luiss.it/lists/lt.php?id=cRpQAAYBSAULAAdOVgFdBQs>. If you want to receive the password to access the virtual room, please fill out this form <https://docs.google.com/forms/d/e/1FAIpQLSeDxM-M5ogG43elgjC-lNCp0BDhISiZHG0HPlNffQl3h3J2Mg/viewform?usp=sf_link> (If you filled it out in the past, this is not necessary). The schedule of the upcoming seminars can be found here <https://economiaefinanza.luiss.it/en/seminars/2020-2021-seminars>. ******************************************************* Marco Scarsini Dipartimento di Economia e Finanza Luiss Viale Romania 32 00197 Roma, ITALY URL: http://docenti.luiss.it/scarsini/