Optimizing tuberculosis case detection through a novel diagnostic device placement model: The case of Uganda
By Mai Pho, Sarang Deo, Kara Palamountain, • Moses Joloba, Francis Bajunirwe, Achilles Katamba
PLoS One | April 2015
DOI
doi.org/10.1371/journal.pone.0122574
Citation
Pho, Mai., Deo, Sarang., Palamountain, Kara., Joloba, • Moses., Bajunirwe, Francis., Katamba, Achilles. Optimizing tuberculosis case detection through a novel diagnostic device placement model: The case of Uganda PLoS One doi.org/10.1371/journal.pone.0122574.
Copyright
PLoS One, 2015
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Abstract
Background
The Xpert MTB/RIF (Xpert) device is being widely adopted. Analysisis needed to guide the placement of devices within health systems to optimize tuberculosis (TB) detection.

Methods
We used epidemiologic and operational data from Uganda to perform a model-based comparison of different placement strategies for a limited number of Xpert devices, which included: 1) Health center level (sites ranked from highest to lowest level), 2) Smear volume (sites ranked from highest to lowest), 3) Antiretroviral therapy (ART) volume (sites ranked from greatest to least patients on ART), 4) External equality assessment (EQA) performance (sites ranked from worst to best smear microscopy performance) and 5) TB prevalence (sites ranked from highest to lowest). Outcomes included CDR, detection of multi-drug resistant TB, and number of sites requiring device placement.

Results
139 sites serving 87,600 TB suspects were modeled. Placement strategies that prioritized sites with higher TB prevalence and worse EQA performance led to a greater CDR compared to other strategies. They resulted in an incremental CDR of 4.9-12.3% compared to status quo (microscopy alone).  Diagnosis of MDR-TB was greatest in the TB Prevalence strategy, with a 2.6-3.4% higher rate compared to the next best strategy. The number of Xpert devices required for the TB Prevalence, EQA Performance, and ART volume strategies was greater than the other strategies for the same level of coverage. Results remained robust over variation in clinical algorithm, EQA accuracy, and return for test results.

Conclusion
In Uganda, placement of Xpert devices in sites with high TB prevalence and poor EQA performance yielded the highest TB case detection rate. These results represent a novel use of program level data to inform the optimal placement of new technology in resource-constrained settings.

Sarang Deo is a Professor of Operations Management at the Indian School of Business (ISB), where he also serves as the Deputy Dean for Faculty and Research and as the Executive Director of the Max Institute of Healthcare Management (MIHM).

His primary area of research is health care delivery systems. He is interested in investigating the impact of operations decisions on population-level health outcomes. Some of the healthcare contexts that he has studied include the influenza vaccine supply chain and the phenomenon of ambulance diversion in the US, HIV early infant diagnosis networks in sub-Saharan Africa, and formal and informal pathways for tuberculosis (TB) diagnosis in India. He regularly collaborates with international public health funding and implementation agencies such as Bill & Melinda Gates Foundation (BMGF), Clinton Health Access Initiative (CHAI), and PATH for his research. He currently serves as a member of the WHO Strategic and Technical Advisory Group on TB (STAG-TB).

Prior to joining ISB, Professor Deo was an Assistant Professor at the Kellogg School of Management. He holds a PhD from UCLA Anderson School of Management, an MBA from Indian Institute of Management (IIM) Ahmedabad, and a B Tech from the Indian Institute of Technology (IIT) Bombay. Before entering academia, he worked with Accenture as a management consultant.

Sarang Deo
Sarang Deo