\ Robust approaches in optimization methods for health care delivery

Robust approaches in optimization methods for health care delivery

Date & Time

1 December 2014 - 14:00



Abstract: Uncertainty is inherent in many health care optimization problems and cannot be neglected, as it may have a significant impact on the problem solution. For instance, uncertainty is associated to the availability of ambulances in locating emergency vehicles, and related to the duration of surgery in planning and scheduling operating room theaters.
Uncertainty also occurs in managing Home Care (HC) services: the most critical and frequent random event is a sudden variation in the amount of service required by HC patients, which is in general highly variable.
In this talk, I discuss how to manage uncertain demands while planning the activities of a HC provider, with particular reference to the nurse-to-patient assignment problem under continuity of care. I present three different optimization techniques that include demand uncertainty, i.e., a stochastic programming approach, a robust cardinality-constrained optimization model, and an analytical policy.
In addition, since all these approaches require an estimation of the future patients demands, I briefly discuss two possible stochastic models to predict a patient s care pathway and his/her demands for visits over time.
Finally, the application to a relevant real case is described, and the benefits deriving from implementing the proposed approaches are shown.

Biography: Ettore Lanzarone was born in Milan, Italy, in 1979. He obtained his Ph.D. in bioengineering in June 2008 at the Politecnico di Milano, his master degree in biomedical engineering cum laude in April 2004 at the Politecnico di Milano.
Since November 2011 he is a Permanent Researcher at the division of Milan of the Institute of Applied Mathematics and Information Technology (IMATI) of the National Research Council of Italy (CNR). He is part of the β-Lab (Laboratory of Biomechanics for Endovascular Treatments of the Aorta), joint laboratory among Università degli Studi di Pavia, CNR-IMATI and Policlinico San Donato.
His main research interests include:
Optimization of resource planning in heathcare facilities, with particular interest in including the robustness in the plans, to face the high uncertainty of patients’ demands.
Stochastic models for estimating the demand and planning the activities in healthcare structures.
Scheduling algorithms for the manufacturing industry.
Industrial bioengineering, with particular interest to the cardiovascular fluyd dynamics (modelling studies, in-vitro studies, clinical trials and design of bench prototypes for the cardiovascular system) and the application of innovative biomedical devices and methodologies in the processes of healthcare facilities.
Parameter estimation and stochastic evolution of complex dynamic systems described by ordinary differential equations and partial differential equations.
Ettore Lanzarone is Adjunct Professor and Lecturer of Mathematical Analysis (MAT/05) and Lecturer of Geometry (MAT/03) and Probability and Statistics (MAT/06) at the Politecnico di Milano.


Yeditepe University, Industrial & Systems Engineering Department
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