Author : Austin Bren
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)
Book Synopsis Data-driven Robust Optimization in Healthcare Applications by : Austin Bren
Download or read book Data-driven Robust Optimization in Healthcare Applications written by Austin Bren and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare operations have enjoyed reduced costs, improved patient safety, and innovation in healthcare policy over a huge variety of applications by tackling problems via the creation and optimization of descriptive mathematical models to guide decision-making. Despite these accomplishments, models are stylized representations of real-world applications, reliant on accurate estimations from historical data to justify their underlying assumptions. To protect against unreliable estimations which can adversely affect the decisions generated from applications dependent on fully-realized models, techniques that are robust against misspecications are utilized while still making use of incoming data for learning. Hence, new robust techniques are applied that (1) allow for the decision-maker to express a spectrum of pessimism against model uncertainties while (2) still utilizing incoming data for learning. Two main applications are investigated with respect to these goals, the first being a percentile optimization technique with respect to a multi-class queueing system for application in hospital Emergency Departments. The second studies the use of robust forecasting techniques in improving developing countries' vaccine supply chains via (1) an innovative outside of cold chain policy and (2) a district-managed approach to inventory control. Both of these research application areas utilize data-driven approaches that feature learning and pessimism-controlled robustness.