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Diagnosing Xpert MTB/RIF negative TB: Impact and cost of alternative algorithms for South Africa

K Schnippel, G Meyer-Rath, L Long, W S Stevens, I Sanne, S Rosen

Abstract


Background. Use of Xpert MTB/RIF is being scaled up throughout South Africa for improved diagnosis of tuberculosis (TB). A large proportion of HIV-infected patients with possible TB are Xpert-negative on their initial test, and the existing diagnostic algorithm calls for these patients to have sputum culture (Xpert followed by culture (X/C)). We modelled the costs and impact of an alternative diagnostic algorithm in which these cultures are replaced with a second Xpert test (Xpert followed by Xpert (X/X)).

Methods. An existing population-level decision model was used. Costs were estimated from Xpert implementation studies and public sector price and salary data. The number of patients requiring diagnosis was estimated from the literature, as were rates of TB treatment uptake and loss to follow-up. TB and HIV positivity rates were estimated from the national TB register and laboratory databases.

Results. At national programme scale in 2014, X/X (R969 million/year) is less expensive than X/C R1 095 million/year), potentially saving R126 million/year (US$17.4 million). However, because Xpert is less sensitive than culture, X/X diagnoses 2% fewer TB cases. This is partly offset by higher expected treatment uptake with X/X due to the faster availability of results, resulting in 1% more patients initiating treatment under X/X than X/C. The cost per TB patient initiated on treatment under X/X is R2 682, which is 12% less than under X/C (R3 046).

Conclusions. Modifying the diagnostic algorithm from X/C to X/X could provide rapid results, simplify diagnostic processes, improve HIV/TB treatment outcomes, and generate cost savings.

Authors' affiliations

K Schnippel, Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg

G Meyer-Rath, Center for Global Health and Development, Boston University, Boston, USA; and Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Joh

L Long, Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg

W S Stevens, Department of Molecular Medicine and Haematology, Faculty of Health Sciences, University of the Witwatersrand; and National Health Laboratory Service, Johannesburg

I Sanne, Center for Global Health and Development, Boston University, Boston, USA; and Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Joh

S Rosen, Center for Global Health and Development, Boston University, Boston, USA; and Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Joh

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Keywords

TB/HIV co-infection; economics; GeneXpert; molecular diagnostics; TB diagnosis

Cite this article

South African Medical Journal 2013;103(2):101-106. DOI:10.7196/SAMJ.6182

Article History

Date submitted: 2012-08-03
Date published: 2013-01-14

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