Optimal allocation of surgical services

Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.

Bibliographic Details
Main Author: Braun, Marcus (Marcus D.)
Other Authors: Vivek Farias and David Simchi-Levi.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2014
Subjects:
Online Access:http://hdl.handle.net/1721.1/90767
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author Braun, Marcus (Marcus D.)
author2 Vivek Farias and David Simchi-Levi.
author_facet Vivek Farias and David Simchi-Levi.
Braun, Marcus (Marcus D.)
author_sort Braun, Marcus (Marcus D.)
collection MIT
description Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.
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spelling mit-1721.1/907672022-01-27T21:07:21Z Optimal allocation of surgical services Braun, Marcus (Marcus D.) Vivek Farias and David Simchi-Levi. Leaders for Global Operations Program. Leaders for Global Operations Program at MIT Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Sloan School of Management Sloan School of Management. Electrical Engineering and Computer Science. Leaders for Global Operations Program. Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT. Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014. In conjunction with the Leaders for Global Operations Program at MIT. 25 Cataloged from PDF version of thesis. Includes bibliographical references (pages 61-64). Over the past several years Greater Boston has witnessed the consolidation of multiple community hospitals into larger care organizations and a renewed focus on the delivery of affordable care. In order for the Beth Israel Deaconess Medical Center (BIDMc) to respond and adapt to this changing landscape it will be critical to not only understand demand and capacity across the organization's entire network, but also to recognize how the deployment of limited resources can best be improved. From a BIDMc Department of Surgery Perspective, essential business questions include: 1 How to allocate limited existing resources efficiently? 2 Which future growth opportunities should be pursued now? 3 How should a multiple-hospital network be used to meet system demand? Existing approaches employed for solving these questions often involve heuristic rules-of-thumb that fail to treat sunk costs and opportunity costs appropriately. These approaches often lead to demonstrably sub-optimal operational decisions. We have developed a framework for answering these questions in a more quantitatively rigorous fashion using mathematical programming. Our model captures each surgical case's impact on hospital resources (e.g. OR time, surgeon time, etc.) from when a patient enters the preoperative holding area to when they are released from the post anesthesia care unit. Using knowledge of resource requirements for each procedure, we compute an optimal allocation of cases subject to capacity and demand constraints. We pilot our framework by studying three surgical service lines within BIDMC: General Surgery, Colorectal Surgery, and Surgical Oncology. We explore three different approaches to more effectively using resources and determine that the most practical approach yields a potential profit increase of more than 5% over 2012 levels. by Marcus Braun. M.B.A. S.M. 2014-10-08T15:27:52Z 2014-10-08T15:27:52Z 2014 2014 Thesis http://hdl.handle.net/1721.1/90767 891385457 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 74 pages application/pdf Massachusetts Institute of Technology
spellingShingle Sloan School of Management.
Electrical Engineering and Computer Science.
Leaders for Global Operations Program.
Braun, Marcus (Marcus D.)
Optimal allocation of surgical services
title Optimal allocation of surgical services
title_full Optimal allocation of surgical services
title_fullStr Optimal allocation of surgical services
title_full_unstemmed Optimal allocation of surgical services
title_short Optimal allocation of surgical services
title_sort optimal allocation of surgical services
topic Sloan School of Management.
Electrical Engineering and Computer Science.
Leaders for Global Operations Program.
url http://hdl.handle.net/1721.1/90767
work_keys_str_mv AT braunmarcusmarcusd optimalallocationofsurgicalservices