Modeling Hepatitis C treatment policy.

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Description

Chronic infection with Hepatitis C virus (HCV) results in cirrhosis, liver cancer and death. As the nation's largest provider of care for HCV, US Veterans Health Administration (VHA) invests extensive resources in the diagnosis and treatment of the disease. This report documents modeling and analysis of HCV treatment dynamics performed for the VHA aimed at improving service delivery efficiency. System dynamics modeling of disease treatment demonstrated the benefits of early detection and the role of comorbidities in disease progress and patient mortality. Preliminary modeling showed that adherence to rigorous treatment protocols is a primary determinant of treatment success. In depth ... continued below

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36 p.

Creation Information

Kuypers, Marshall A.; Lambert, Gregory Joseph; Moore, Thomas W.; Glass, Robert John,; Finley, Patrick D.; Ross, David et al. September 1, 2013.

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This report is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. More information about this report can be viewed below.

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Description

Chronic infection with Hepatitis C virus (HCV) results in cirrhosis, liver cancer and death. As the nation's largest provider of care for HCV, US Veterans Health Administration (VHA) invests extensive resources in the diagnosis and treatment of the disease. This report documents modeling and analysis of HCV treatment dynamics performed for the VHA aimed at improving service delivery efficiency. System dynamics modeling of disease treatment demonstrated the benefits of early detection and the role of comorbidities in disease progress and patient mortality. Preliminary modeling showed that adherence to rigorous treatment protocols is a primary determinant of treatment success. In depth meta-analysis revealed correlations of adherence and various psycho-social factors. This initial meta-analysis indicates areas where substantial improvement in patient outcomes can potentially result from VA programs which incorporate these factors into their design.

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36 p.

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  • Report No.: SAND2013-8134
  • Grant Number: AC04-94AL85000
  • Office of Scientific & Technical Information Report Number: 1096266
  • Archival Resource Key: ark:/67531/metadc827558

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  • September 1, 2013

Added to The UNT Digital Library

  • May 19, 2016, 9:45 a.m.

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  • June 17, 2016, 3:19 p.m.

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Kuypers, Marshall A.; Lambert, Gregory Joseph; Moore, Thomas W.; Glass, Robert John,; Finley, Patrick D.; Ross, David et al. Modeling Hepatitis C treatment policy., report, September 1, 2013; Washington D.C.. (digital.library.unt.edu/ark:/67531/metadc827558/: accessed September 22, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.