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NEW APPROACHES USING PROBABILISTIC GRAPHICAL MODELS IN HEALTH ECONOMICS AND OUTCOMES RESEARCH
by
Quang Anh Le
________________________________________________________________________
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PHARMACEUTICAL ECONOMICS AND POLICY)
December 2010
Copyright 2010 Quang Anh Le
Object Description
| Title | New approaches using probabilistic graphical models in health economics and outcomes research |
| Author | Le, Quang Anh |
| Author email | quangle@usc.edu; quangale@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Pharmaceutical Economics & Policy |
| School | School of Pharmacy |
| Date submitted | 2010 |
| Restricted until | Unrestricted |
| Date published | 2010-11-16 |
| Advisor (committee chair) | Doctor, Jason N. |
| Advisor (committee member) |
Hay, Joel W. Cousineau, Michael |
| Abstract | Probabilistic graphical models (PGMs) are those models that employ both probability theory and graph theory. The fundamental to the idea of a PGM is the notion of modularity, i.e. a complex system can be built by combining simpler parts. Health economics and outcomes research (HEOR) is a multidisciplinary approach to healthcare and research that incorporates number of areas of expertise including clinical research, epidemiology, health services research, economics, and psychometrics. The field has rapidly expanded in the last decade and played a crucial role in improvement the quality of healthcare. Drugs, healthcare programs, and medical devices are increasingly required to demonstrate not only their efficacy and safety characteristics, but also their superior performance in clinical effectiveness, health-related quality of life and economic outcomes. While probabilistic graphical models have become a popular tool for data analysis in health informatics, especially used to prescribe treatment or guide diagnostic decisions, their use and applications in HEOR have been limited. This three-paper dissertation introduces new approaches using probabilistic graphical models in health economics and outcomes research.; Paper 1 demonstrates a cost-effectiveness analysis model of an expensive and newly approved cancer drug, lapatinib, using a Markov model with Monte-Carlo simulation method. This modeling approach innovatively uses Microsoft® Excel spreadsheet with Visual Basic programming language and provides health economists the flexibility to customize, ease to calibrate, and graphical visualization for their cost-effectiveness models. Paper 2 presents an alternative method using a Bayesian network that can detect blood lab errors better than the existing automated models. Successful implementation of the Bayesian network model in clinical laboratory can help to reduce medical costs and improve patient safety. Paper 3 provides a new robust and natural approach using Bayesian networks to map health-profile or disease-specific measures onto preference-based measures. Applying the probabilistic mapping technique to obtain QALYs can be useful in health economic evaluations when health utilities are not directly available. |
| Keyword | EQ-5D; SF-12; pobabilistic mapping; Bayesian networks; Markov model; lapatinib; cost-effectivness; blood laboratory errors |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m3528 |
| Rights | Le, Quang Anh |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Le-4162 |
| Archival file | uscthesesreloadpub_Volume29/etd-Le-4162.pdf |
Description
| Title | Page 1 |
| Full text | NEW APPROACHES USING PROBABILISTIC GRAPHICAL MODELS IN HEALTH ECONOMICS AND OUTCOMES RESEARCH by Quang Anh Le ________________________________________________________________________ A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (PHARMACEUTICAL ECONOMICS AND POLICY) December 2010 Copyright 2010 Quang Anh Le |
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