Optimal Decentralization of Early Infant Diagnosis of HIV in Resource-Limited Settings
Optimal Decentralization of Early Infant Diagnosis of HIV in Resource-Limited Settings
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DOI：
10.1287/msom.2014.0512
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发表时间：
2015-03-01
影响因子：
6.3
通讯作者：
Sohoni, Milind
中科院分区：
文献类型：
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作者：
Deo, Sarang;Sohoni, Milind
在许多资源有限的环境中，早期婴儿诊断（EID）项目旨在诊断感染艾滋病毒的母亲所生的婴儿。由于诊断技术的复杂性，EID项目通常高度集中，很少有实验室检测来自大型卫生设施网络的血液样本。这导致长时间的诊断延误和随之而来的患者未能及时收集结果。正在开发几种在卫生设施内提供快速诊断的医疗点（POC）设备，以减轻集中EID网络的这些缺点。我们以莫桑比克的EID项目为例，研究了哪些设施应该接收POC设备（安置计划）的决定。我们认为，在预算紧张的情况下，选择适当的计划对于最大限度地发挥POC设备对公共卫生的影响至关重要。为了形式化这一论点，我们开发了一个详细的模拟模型来评估安置计划的影响。它包括两个部分：一个是量化POC安置计划对诊断延迟影响的操作模型，另一个是量化诊断延迟对婴儿照顾者收集结果可能性的影响的行为部分。我们还开发了这些操作和患者行为动态的近似版本，并将它们嵌入到优化模型中，以生成候选POC放置计划。我们发现，与具有实际吸引力的经验法则相比，基于优化的计划可以导致多达30%的患者收集结果。最后，我们表明，POC设备的有效性远远高于EID网络的其他操作改进，例如增加实验室容量，减少运输延迟和更规范的运输。
Early infant diagnosis (EID) programs in many resource-limited settings are aimed at diagnosing infants born to HIV-infected mothers. Because of the complexity of the diagnostic technology, EID programs are often highly centralized with few laboratories testing blood samples from a large network of health facilities. This leads to long diagnostic delays and consequent failure of patients to collect results in a timely manner. Several point-of-care (POC) devices that provide rapid diagnosis within the health facilities are being developed to mitigate these drawbacks of centralized EID networks. We study the decision of which facilities should receive the POC device (the placement plan) using the EID program in Mozambique as a case study. We argue that the choice of an appropriate plan is critical to maximizing the public health impact of POC devices in the presence of tight budget constraints. To formalize this argument, we develop a detailed simulation model to evaluate the impact of a placement plan. It comprises two parts: an operational model that quantifies the impact of a POC placement plan on the diagnostic delay and a behavioral part that quantifies the impact of diagnostic delay on the likelihood of result collection by infants' caregivers. We also develop an approximate version of these operational and patient behavior dynamics and embed them in an optimization model to generate candidate POC placement plans. We find that the optimization-based plan can result in up to 30% more patients collecting their results compared to rules of thumb that have practical appeal. Finally, we show that the effectiveness of POC devices is much higher than other operational improvements to the EID network such as increased laboratory capacity, reduced transportation delay, and more regularized transport.