S4HARA: System for HIV/AIDS resource allocation
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BioMed Central
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S4HARA: System for HIV/AIDS resource allocation Arielle Lasry1, Michael W Carter1 and Gregory S Zaric*2 Address: 1Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, M5S 3G8, Canada and 2Ivey School of Business, University of Western Ontario, London, ON, N6A 3K7, Canada Email: Arielle Lasry - [email protected]; Michael W Carter - [email protected]; Gregory S Zaric* - [email protected] * Corresponding author
Published: 26 March 2008 Cost Effectiveness and Resource Allocation 2008, 6:7
doi:10.1186/1478-7547-6-7
Received: 27 June 2007 Accepted: 26 March 2008
This article is available from: http://www.resource-allocation.com/content/6/1/7 © 2008 Lasry et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract Background: HIV/AIDS resource allocation decisions are influenced by political, social, ethical and other factors that are difficult to quantify. Consequently, quantitative models of HIV/AIDS resource allocation have had limited impact on actual spending decisions. We propose a decision-support System for HIV/AIDS Resource Allocation (S4HARA) that takes into consideration both principles of efficient resource allocation and the role of non-quantifiable influences on the decision-making process for resource allocation. Methods: S4HARA is a four-step spreadsheet-based model. The first step serves to identify the factors currently influencing HIV/AIDS allocation decisions. The second step consists of prioritizing HIV/AIDS interventions. The third step involves allocating the budget to the HIV/AIDS interventions using a rational approach. Decision-makers can select from several rational models of resource allocation depending on availability of data and level of complexity. The last step combines the results of the first and third steps to highlight the influencing factors that act as barriers or facilitators to the results suggested by the rational resource allocation approach. Actionable recommendations are then made to improve the allocation. We illustrate S4HARA in the context of a primary healthcare clinic in South Africa. Results: The clinic offers six types of HIV/AIDS interventions and spends US$750,000 annually on these programs. Current allocation decisions are influenced by donors, NGOs and the government as well as by ethical and religious factors. Without additional funding, an optimal allocation of the total budget suggests that the portion allotted to condom distribution be increased from 1% to 15% and the portion allotted to prevention and treatment of opportunistic infections be increased from 43% to 71%, while allocation to other interventions should decrease. Conclusion: Condom uptake at the clinic should be increased by changing the condom distribution policy fr
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