Literature DB >> 18664951

Assessing efficiency and costs of scaling up HIV treatment.

Susan M Cleary1, Di McIntyre, Andrew M Boulle.   

Abstract

INTRODUCTION: Whereas cost-effectiveness/utility analyses theoretically assess efficiency in HIV treatment, in practice they are of limited use to policy makers who are also concerned with the total costs of scaling up. This paper proposes an approach to simultaneously assessing both factors when setting priorities for HIV treatment.
METHODS: Three interventions were assessed: a no antiretroviral therapy (ART) status quo, ART including first-line only, and ART including first and second-line regimens. Data were from a cohort receiving healthcare in a poor South African setting. Markov modelling was used to calculate patient-level lifetime costs and quality-adjusted life-years (QALY) as well as population-level total costs and QALY in each intervention. Linear programming was used to assess efficiency at the population level.
RESULTS: First-line ART costs US$795 per QALY gained compared to no ART, while first and second-line costs US$1625 compared to first-line alone. The efficiency of either ART strategy depends on the HIV treatment budget. If this is less than US$10 billion during the planning period, first-line ART is most efficient. A combination of first-line with first and second-line treatment is most efficient if the budget is US$10-12 billion. Using both first and second-line treatment for everyone becomes efficient as the main strategy only at budgets greater than US$13 billion.
CONCLUSION: An approach has been developed to HIV treatment priority setting that simultaneously considers efficiency and the costs of scaling up. This can help to establish explicit and evidence-based priorities and budgets to meet scaling up challenges.

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Year:  2008        PMID: 18664951     DOI: 10.1097/01.aids.0000327621.24232.71

Source DB:  PubMed          Journal:  AIDS        ISSN: 0269-9370            Impact factor:   4.177


  15 in total

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4.  Decision making for HIV prevention and treatment scale up: bridging the gap between theory and practice.

Authors:  Sabina S Alistar; Margaret L Brandeau
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5.  Improving the evidence base of Markov models used to estimate the costs of scaling up antiretroviral programmes in resource-limited settings.

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6.  The determinants of HIV treatment costs in resource limited settings.

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8.  Mean Corpuscular Volume as a Marker for Adherence to Zidovudine-Containing Therapy in HIV-Infected Adults.

Authors:  Joseph O Mugisha; Katherine Donegan; Sarah Fidler; Gita Ramjee; Andrew Hodson; David T Dunn; Kholoud Porter; Pontiano Kaleebu
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9.  Key actors' perspectives on cost-effectiveness analysis in Uganda: a cross-sectional survey.

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10.  A novel Markov model projecting costs and outcomes of providing antiretroviral therapy to public patients in private practices versus public clinics in South Africa.

Authors:  Rory Leisegang; Gary Maartens; Michael Hislop; John Sargent; Ernest Darkoh; Susan Cleary
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

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