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Differentiated HIV Viral Load Monitoring in Resource Limited Settings: An Economic Analysis

Tuesday, October 25, 2016 - 1:25pm - 2:25pm
Lind 305
Diana Negoescu (University of Minnesota, Twin Cities)
Viral load (VL) monitoring for patients receiving antiretroviral therapy (ART) is recommended worldwide. However, the costs of frequent monitoring are a barrier to implementation in resource-limited settings. The extent to which personalized monitoring frequencies may be cost-effective is unknown. We created a simulation model parameterized using person-level longitudinal data to assess the benefits of flexible monitoring frequencies. Our data-driven model tracked HIV+ individuals for 10 years following ART initiation. We then optimized the interval between viral load tests as a function of patients’ age, gender, education, duration since ART initiation, adherence behavior, and the willingness-to-pay threshold. We compared the cost-effectiveness of the personalized monitoring strategies to fixed monitoring intervals every 1, 3, 6, 12 and 24 months. We find that focusing on patients most at risk of virological failure improves the efficiency of VL monitoring. In low- and middle-income countries, adaptive policies achieve similar outcomes to fixed interval at lower costs, while in high-income countries adaptive policies can outperform fixed policies both in terms on health benefits and costs.

Diana Negoescu is an Assistant Professor in the Industrial and Systems Engineering Department at the University of Minnesota. Her broad research interest lie in the application of operations research and management science to medical and health policy decision-making problems. In particular, her research focuses on personalized medical decision-making and healthcare models for problems where patient characteristics are partially unknown or evolving over time, and where decision makers are risk-averse, or face constraints on the resources they can use or the actions they can take.