2026-09-19T02:38:36Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/459462022-01-13T07:54:48Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
Dimitris J. Bertsimas.
Bjarnadóttir, Margrét Vilborg
Massachusetts Institute of Technology. Operations Research Center.
Massachusetts Institute of Technology. Operations Research Center
Sloan School of Management
2009-06-30T16:46:02Z
2009-06-30T16:46:02Z
2008
2008
http://hdl.handle.net/1721.1/45946
321051813
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.
130 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Operations Research Center.
Data-driven approach to health care : applications using claims data
Thesis
application/pdf
Publication
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