Optimising the cost and delivery of HIV counselling and testing services in Kenya and Swaziland.


Obure, CD; Vassall, A; Michaels-Igbokwe, C; Terris-Prestholt, F; Mayhew, S; Stackpool-Moore, L; Warren, C; Integra research team, ; Watts, C; (2012) Optimising the cost and delivery of HIV counselling and testing services in Kenya and Swaziland. Sexually transmitted infections, 88 (7). pp. 498-503. ISSN 1368-4973 DOI: https://doi.org/10.1136/sextrans-2012-050544

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Abstract

BACKGROUND: Approaches to HIV counselling and testing (HCT) within low-resource high HIV prevalence settings have shifted over the years from primarily client-initiated approaches to provider initiated. As part of an ongoing programme science research agenda, we examine the relative costs of provider-initiated testing and counselling (PITC) services compared with voluntary counselling and testing (VCT) services in the same health facilities in two low-resource settings: Kenya and Swaziland.<br/> METHODS: Annual financial and economic costs and output measures were collected retrospectively from 28 health facilities. Total annual costs and average costs per client counselled and tested (C&T), and HIV-positive clients identified, were estimated.<br/> RESULTS: VCT remains the predominant mode of HCT service delivery across both countries. However, unit cost per client C&T and per person testing HIV positive is lower for PITC than VCT across all facility types in Kenya, but the picture is mixed in Swaziland. Average cost per client C&T ranged from US $4.81 to US $6.11 in Kenya, US $6.92 to US $13.51 in Swaziland for PITC, and from US $5.05 to US $16.05 and US $8.68 to US $19.32 for VCT in Kenya and Swaziland, respectively.<br/> CONCLUSIONS: In the context of significant policy interest in optimising scarce HIV resources, this study demonstrates that there may be potential for substantial gains in efficiency in the provision of HCT services in both Kenya and Swaziland. However, considerations of how to deliver services efficiently need to be informed by local contextual factors, such as prevalence, service demand and availability of human resources.<br/>

Item Type: Article
Faculty and Department: Faculty of Public Health and Policy > Dept of Global Health and Development
Research Centre: Social and Mathematical Epidemiology (SaME)
SaME Modelling & Economics
PubMed ID: 22859498
Web of Science ID: 311292100010
URI: http://researchonline.lshtm.ac.uk/id/eprint/126384

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