Kabiri, Mina
(2017)
Computer simulations in health policy: methodology and applications in the management of chronic diseases.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Among the main challenges of public-health policy makers is reducing gaps in the delivery of care, given limited human and monetary resources. In a public health setting, decision-analysis tools such as simulation models can be used to inform decision-makers in answering what-if policy questions in order to improve public health and clinical practice, optimize resource allocation, or guide funding and reimbursement decisions. Of the main public-health challenges in the United States is the burden of chronic infectious diseases. The prevalence and associated cost of chronic infectious diseases, such as hepatitis C virus (HCV) and sexually transmitted diseases (STDs) has increased in the United States due to rising life expectancy and social changes. Many of these diseases have effective therapies, but there are gaps in research on effective mitigation strategies. The public health significance of this dissertation was to apply rigorous decision-sciences methods using computer simulations in health services research and to expand the application of existing methods to answer real-world questions in health policy of chronic infectious diseases.
In the first section of this dissertation, I quantified the the effects of new HCV therapies and updated screening guidelines on the burden of HCV and associated disease outcomes in the United States using an individual-level state-transition microsimulation model. The second section of this dissertation, estimated the status of HCV disease burden and the potential budget impact of various treatment strategies in the Pennsylvania Medicaid population using the HCV microsimulation model that was calibrated to Pennsylvania Medicaid according to the claims data from 2007–2012. The last section of this dissertation, included the development and maintenance of sexual partnership networks using an agent-based simulation modeling approach, according to serial cross-sectional data obtained from the 2007–2014 National Health and Nutrition Examination Survey. This study provides a tool for understanding the dynamics of sexual partnership networks which is critical to improve the impacts of STD mitigation strategies that focus on the sexual behaviors of individuals. In conclusion, this dissertation provided the details of two computer-simulation applications in health-related multi-disciplinary policy research, and delivers insights on how to use computer simulation in medical decision-sciences and policy problems.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
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| Date: |
30 August 2017 |
| Date Type: |
Publication |
| Defense Date: |
7 June 2017 |
| Approval Date: |
30 August 2017 |
| Submission Date: |
4 June 2017 |
| Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
| Number of Pages: |
153 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Public Health > Health Policy & Management |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
health policy computer simulation microsimulation agent-based modeling chronic diseases social networks |
| Date Deposited: |
30 Aug 2017 21:44 |
| Last Modified: |
01 Jul 2019 05:15 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/32528 |
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