Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2008. / Includes bibliographical references (p. 123-130). / Large population health insurance claims databases together with operations research and data mining methods have the potential of significantly impacting health care management. In this thesis we research how claims data can be utilized in three important areas of health care and medicine and apply our methods to a real claims database containing information of over two million health plan members. First, we develop forecasting models for health care costs that outperform previous results. Secondly, through examples we demonstrate how large-scale databases and advanced clustering algorithms can lead to discovery of medical knowledge. Lastly, we build a mathematical framework for a real-time drug surveillance system, and demonstrate with real data that side effects can be discovered faster than with the current post-marketing surveillance system. / by Margrét Vilborg Bjarnadóttir. / Ph.D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/45946 |
| Date | January 2008 |
| Creators | Bjarnadóttir, Margrét Vilborg |
| Contributors | Dimitris J. Bertsimas., Massachusetts Institute of Technology. Operations Research Center., Massachusetts Institute of Technology. Operations Research Center. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 130 p., application/pdf |
| 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., http://dspace.mit.edu/handle/1721.1/7582 |
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