Optimal allocation of surgical services

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.

Department dc:contributor.department

Leaders for Global Operations Program at MIT

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2014

Author dc:creator

• Braun, Marcus (Marcus D.)

Advisor dc:contributor.advisor

• Vivek Farias and David Simchi-Levi.

• Sloan School of Management.
• Electrical Engineering and Computer Science.
• Leaders for Global Operations Program.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/90767

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/90767