A systems model of the cost impact of new HIV/AIDS therapies: Applications of a Markov process

Persistent Link:
http://hdl.handle.net/10150/282506
Title:
A systems model of the cost impact of new HIV/AIDS therapies: Applications of a Markov process
Author:
Bhattacharyya, Samir Kumar, 1966-
Issue Date:
1997
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
The primary objectives of this research were to (1) estimate survival functions and the natural history of patients infected with human immunodeficiency virus who are using antiretroviral medication with a protease inhibitor and those who are under treatment protocols without protease inhibitors, and (2) estimate average lifetime treatment costs of infected patients for both drug regimens. A secondary objective was to provide a step by step discussion of the applicability of a Markov process in modeling survival and cost profiles of acquired immunodeficiency syndrome, a complex set of diseases, to managed care organizations. Data used in this study were collected using two techniques: expert physician panel interviews and a literature search. The transition rates for patients moving from one disease state to another were obtained from both sources. Cost estimates were calculated predominantly from published literature. The fundamental matrix solution of a Markov chain model was used to estimate survival functions, natural history profiles, and lifetime costs of therapy for HIV-infected patients. The research was conducted from the perspective of a managed health care organization. Results indicated that protease inhibitors significantly improved overall survival of infected patients by deterring the progression of disease and onset of various opportunistic infections. Lifetime costs of treatment, however, were substantially higher for treatment protocols using protease inhibitors as one of the components of recommended combination retroviral therapy. Estimates obtained from this study also indicated that unless significant reductions in high resource intensive events such as hospitalization can be achieved, protease inhibitors might not be cost efficient in treating HIV-infected patients. Lastly, this research showed that Markov modeling techniques can offer valuable benchmarks for both clinical and economic decision making in planning disease intervention to improve health outcomes and evaluate costs.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Economics, General.; Health Sciences, Pharmacy.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Pharmacy Practice and Science
Degree Grantor:
University of Arizona
Advisor:
Langley, Paul C.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleA systems model of the cost impact of new HIV/AIDS therapies: Applications of a Markov processen_US
dc.creatorBhattacharyya, Samir Kumar, 1966-en_US
dc.contributor.authorBhattacharyya, Samir Kumar, 1966-en_US
dc.date.issued1997en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractThe primary objectives of this research were to (1) estimate survival functions and the natural history of patients infected with human immunodeficiency virus who are using antiretroviral medication with a protease inhibitor and those who are under treatment protocols without protease inhibitors, and (2) estimate average lifetime treatment costs of infected patients for both drug regimens. A secondary objective was to provide a step by step discussion of the applicability of a Markov process in modeling survival and cost profiles of acquired immunodeficiency syndrome, a complex set of diseases, to managed care organizations. Data used in this study were collected using two techniques: expert physician panel interviews and a literature search. The transition rates for patients moving from one disease state to another were obtained from both sources. Cost estimates were calculated predominantly from published literature. The fundamental matrix solution of a Markov chain model was used to estimate survival functions, natural history profiles, and lifetime costs of therapy for HIV-infected patients. The research was conducted from the perspective of a managed health care organization. Results indicated that protease inhibitors significantly improved overall survival of infected patients by deterring the progression of disease and onset of various opportunistic infections. Lifetime costs of treatment, however, were substantially higher for treatment protocols using protease inhibitors as one of the components of recommended combination retroviral therapy. Estimates obtained from this study also indicated that unless significant reductions in high resource intensive events such as hospitalization can be achieved, protease inhibitors might not be cost efficient in treating HIV-infected patients. Lastly, this research showed that Markov modeling techniques can offer valuable benchmarks for both clinical and economic decision making in planning disease intervention to improve health outcomes and evaluate costs.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectEconomics, General.en_US
dc.subjectHealth Sciences, Pharmacy.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplinePharmacy Practice and Scienceen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorLangley, Paul C.en_US
dc.identifier.proquest9814394en_US
dc.identifier.bibrecord.b37742206en_US
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