Cost-effectiveness of automated digital microscopy for diagnosis of active tuberculosis

Swati Jha, Nazir Ismail, David Clark, James J. Lewis, Shaheed Omar, Andries Dreyer, Violet Chihota, Gavin Churchyard, David Wesley Dowdy

Research output: Contribution to journalArticle

Abstract

Background: Automated digital microscopy has the potential to improve the diagnosis of tuberculosis (TB), particularly in settings where molecular testing is too expensive to perform routinely. The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain. Methods: Using data from a demonstration study of an automated digital microscopy system (TBDx, Applied Visual Systems, Inc.), we performed an economic evaluation of TB diagnosis in South Africa from the health system perspective. The primary outcome was the incremental cost per new TB diagnosis made. We considered costs and effectiveness of different algorithms for automated digital microscopy, including as a stand-alone test and with confirmation of positive results with Xpert MTB/RIF ('Xpert', Cepheid, Inc.). Results were compared against both manual microscopy and universal Xpert testing. Results: In settings willing to pay $2000 per incremental TB diagnosis, universal Xpert was the preferred strategy. However, where resources were not sufficient to support universal Xpert, and a testing volume of at least 30 specimens per day could be ensured, automated digital microscopy with Xpert confirmation of low-positive results could facilitate the diagnosis of 79-84% of all Xpert-positive TB cases, at 50-60% of the total cost. The cost-effectiveness of this strategy was $1280 per incremental TB diagnosis (95% uncertainty range, UR: $340-$3440) in the base case, but improved under conditions likely reflective of many settings in sub-Saharan Africa: $677 per diagnosis (95% UR: $450-$935) when sensitivity of manual smear microscopy was lowered to 0.5, and $956 per diagnosis (95% UR: $40-$2910) when the prevalence of multidrug-resistant TB was lowered to 1%. Conclusions: Although universal Xpert testing is the preferred algorithm for TB diagnosis when resources are sufficient, automated digital microscopy can identify the majority of cases and halve the cost of diagnosis and treatment when resources are more scarce and multidrug-resistant TB is not common.

Original languageEnglish (US)
Article numbere0157554
JournalPLoS One
Volume11
Issue number6
DOIs
StatePublished - Jun 1 2016

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cost effectiveness
Cost effectiveness
tuberculosis
Cost-Benefit Analysis
Microscopy
microscopy
Microscopic examination
Tuberculosis
Multidrug-Resistant Tuberculosis
Testing
testing
Costs
Costs and Cost Analysis
Africa South of the Sahara
Sub-Saharan Africa
South Africa
economic analysis
Health Care Costs
Uncertainty
Demonstrations

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Cost-effectiveness of automated digital microscopy for diagnosis of active tuberculosis. / Jha, Swati; Ismail, Nazir; Clark, David; Lewis, James J.; Omar, Shaheed; Dreyer, Andries; Chihota, Violet; Churchyard, Gavin; Dowdy, David Wesley.

In: PLoS One, Vol. 11, No. 6, e0157554, 01.06.2016.

Research output: Contribution to journalArticle

Jha, S, Ismail, N, Clark, D, Lewis, JJ, Omar, S, Dreyer, A, Chihota, V, Churchyard, G & Dowdy, DW 2016, 'Cost-effectiveness of automated digital microscopy for diagnosis of active tuberculosis', PLoS One, vol. 11, no. 6, e0157554. https://doi.org/10.1371/journal.pone.0157554
Jha, Swati ; Ismail, Nazir ; Clark, David ; Lewis, James J. ; Omar, Shaheed ; Dreyer, Andries ; Chihota, Violet ; Churchyard, Gavin ; Dowdy, David Wesley. / Cost-effectiveness of automated digital microscopy for diagnosis of active tuberculosis. In: PLoS One. 2016 ; Vol. 11, No. 6.
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abstract = "Background: Automated digital microscopy has the potential to improve the diagnosis of tuberculosis (TB), particularly in settings where molecular testing is too expensive to perform routinely. The cost-effectiveness of TB diagnostic algorithms using automated digital microscopy remains uncertain. Methods: Using data from a demonstration study of an automated digital microscopy system (TBDx, Applied Visual Systems, Inc.), we performed an economic evaluation of TB diagnosis in South Africa from the health system perspective. The primary outcome was the incremental cost per new TB diagnosis made. We considered costs and effectiveness of different algorithms for automated digital microscopy, including as a stand-alone test and with confirmation of positive results with Xpert MTB/RIF ('Xpert', Cepheid, Inc.). Results were compared against both manual microscopy and universal Xpert testing. Results: In settings willing to pay $2000 per incremental TB diagnosis, universal Xpert was the preferred strategy. However, where resources were not sufficient to support universal Xpert, and a testing volume of at least 30 specimens per day could be ensured, automated digital microscopy with Xpert confirmation of low-positive results could facilitate the diagnosis of 79-84{\%} of all Xpert-positive TB cases, at 50-60{\%} of the total cost. The cost-effectiveness of this strategy was $1280 per incremental TB diagnosis (95{\%} uncertainty range, UR: $340-$3440) in the base case, but improved under conditions likely reflective of many settings in sub-Saharan Africa: $677 per diagnosis (95{\%} UR: $450-$935) when sensitivity of manual smear microscopy was lowered to 0.5, and $956 per diagnosis (95{\%} UR: $40-$2910) when the prevalence of multidrug-resistant TB was lowered to 1{\%}. Conclusions: Although universal Xpert testing is the preferred algorithm for TB diagnosis when resources are sufficient, automated digital microscopy can identify the majority of cases and halve the cost of diagnosis and treatment when resources are more scarce and multidrug-resistant TB is not common.",
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