PLoS One | April 2015
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). He also serves as the Executive Director of the ISB’s Max Institute of Healthcare Management, where he provides strategic leadership for ISB's healthcare initiatives through interdisciplinary research, education, and collaboration.
Professor Deo's research focuses on healthcare delivery systems, examining how operational decisions influence population-level health outcomes. His work spans a wide range of healthcare contexts, including influenza vaccine supply chains and ambulance diversion in the United States, HIV early infant diagnosis networks in sub-Saharan Africa, and formal and informal pathways for tuberculosis (TB) diagnosis and treatment in India. His recent research has focused on designing and evaluating healthcare delivery models, with a particular emphasis on digital health and the integration of artificial intelligence into healthcare systems.
He regularly collaborates with leading global health organisations, including the Gates Foundation, the Clinton Health Access Initiative (CHAI), and PATH. He currently serves on the World Health Organization's Strategic and Technical Advisory Group for Tuberculosis (STAG-TB) and the Working Group for Non-Technical Evaluation under the WHO Global Initiative on AI for Health (GI-AI4H).
Prior to joining ISB, Professor Deo was an Assistant Professor at the Kellogg School of Management. He holds a PhD from the UCLA Anderson School of Management, an MBA from the Indian Institute of Management Ahmedabad, and a BTech from the Indian Institute of Technology Bombay. Before entering academia, he worked as a management consultant with Accenture.
