Optimal information collection for dynamic health care policy

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Abstract/Contents

Abstract
Mathematical models of health systems and disease can provide important information to decision makers when direct experimentation is impossible, impractical, or unethical, and when there are many possible decision alternatives. When costs or benefits of a medical or health policy decision are in the distant future (perhaps decades away) or are borne by other members of society, mathematical models may be the only practical way to fully evaluate the costs and consequences of policy alternatives. Through modeling, the decision maker can develop a deeper understanding of which factors have the greatest impact on the outcome of interest and explicitly explore decision uncertainty. This dissertation applies and extends the use of mathematical models in the application area of health policy -- specifically to applications of human immunodeficiency virus (HIV) and hepatitis C virus (HCV) screening in injection drug users (IDUs) and the general population.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Publication date 2013
Issuance monographic
Language English

Creators/Contributors

Associated with Cipriano, Lauren Elizabeth
Associated with Stanford University, Department of Management Science and Engineering.
Primary advisor Brandeau, Margaret L
Primary advisor Weber, Thomas
Thesis advisor Brandeau, Margaret L
Thesis advisor Weber, Thomas
Thesis advisor Owens, Douglas K
Advisor Owens, Douglas K

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Lauren Elizabeth Cipriano.
Note Submitted to the Department of Management Science and Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2013.
Location electronic resource

Access conditions

Copyright
© 2013 by Lauren Elizabeth Cipriano
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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