n South African Medical Journal - Diagnosing Xpert MTB/RIF-negative TB : impact and cost of alternative algorithms for South Africa : research
|Article Title||Diagnosing Xpert MTB/RIF-negative TB : impact and cost of alternative algorithms for South Africa : research|
|© Publisher:||Health and Medical Publishing Group (HMPG)|
|Journal||South African Medical Journal|
|Affiliations||1 University of the Witwatersrand, 2 University of the Witwatersrand, 3 University of the Witwatersrand, 4 University of the Witwatersrand, 5 University of the Witwatersrand, 6 University of the Witwatersrand, 7 Boston University, USA, 8 Boston University, USA, 9 Boston University, USA and 10 National Health Laboratory Service|
|Publication Date||Feb 2013|
|Pages||101 - 106|
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.
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