Using systems science to optimize the impact of point-of-care viral load testing for pediatric HIV management

利用系统科学优化床旁病毒载量检测对儿科艾滋病毒管理的影响

基本信息

批准号：
10263333
负责人：
Rena Chiman Patel
金额：
$ 19.11万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-15 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10263333
关键词：
Address Adherence Administrator Adolescent Adoption Adult Africa South of the Sahara Aftercare Anti-Retroviral Agents Budgets Caring Child Childhood Chronic Care Clinical Management Clinical effectiveness Complement Data Decision Making Diagnosis Dose Effectiveness Engineering Engineering Psychology Equilibrium Future Guidelines HIV HIV diagnosis Health Health Services Health system Healthcare Human immunodeficiency virus test Industrialization Infant Interview Investments Kenya Laboratories Lead Learning Methods Modeling Modification Monitor Morbidity - disease rate Mother-to-child HIV transmission Outcome Parents Point of Care Technology Policy Maker Population Prevention Process Psychology Public Health Recommendation Recovery Regimen Research Resistance Resource Allocation Resources Sampling Science Sexually Transmitted Diseases Site Software Engineering Speed System Technology Test Result Testing Time Treatment Failure Treatment outcome Tuberculosis Viral Viral Load result Wait Time World Health Organization antiretroviral therapy base budget impact clinical care clinical decision-making effectiveness clinical trial evidence base experience frontier implementation evaluation improved improved outcome innovation mortality novel pediatric human immunodeficiency virus point of care point-of-care diagnostics public health priorities randomized trial satisfaction scale up sharing platform software development standard of care tool usability user-friendly virology

项目摘要

ABSTRACT HIV-infected children have poorer viral load (VL) suppression than adults and experience high morbidity and mortality. Regular pediatric VL monitoring is critical to direct pediatric treatment and clinical care. VL testing is generally recommended every 6 months for the first year after treatment initiation and annually thereafter, but turnaround time of standard of care (SOC) VL systems is slow (median 21 days). Point of care (POC) technology has revolutionized HIV diagnosis and treatment initiation, and POC VL testing is the next frontier for HIV treatment monitoring. Clinical effectiveness of POC VL testing for children is currently being assessed in an ongoing randomized trial in Kenya (R34 PIs: Patel, Abuogi); however, large gaps exist between clinical effectiveness and real-world use for POC technology. Optimizing POC VL testing using a systems engineering approach will help realize the full impact of investments in POC VL monitoring. In the current proposal, we take a systems engineering approach and borrow methods from diverse fields, such as manufacturing, psychology, and software development to achieve the following aims: Aim 1: To determine the optimal placement of limited POC VL machines within a hub-and-spoke vs. platform sharing models, to balance budget impact and minimize turnaround time. We will create a queuing model – used in industrial engineering to model waiting times – to identify optimal placement of POC machines in Kenya. We will model the reduction in turnaround time and waiting time associated with placement of POC machines in select “hub” facilities (sites with a POC machine) and “spoke” (sites that send samples to a hub) facilities vs. platform sharing amongst sets of facilities. At different budget levels, we will identify the optimal number and placement of POC machines. Aim 2: To determine policymakers’ opinions about usability of the model tool from Aim 1. We will convert the model from Aim 1 into a user-friendly, Excel-based model for policymakers to use for decision-making. We will conduct usability interviews (covering learnability, efficiency, memorability, error recovery, and satisfaction) with approximately 20 health administrators and policymakers about the tool. This novel application of diverse methods borrowed from industrial engineering, software engineering, psychology, and quality improvement presents an innovative approach to increase scalability of POC VL testing for children.

抽象的 HIV 感染儿童的病毒载量 (VL) 抑制能力比成人差，发病率高，且感染率高。定期儿科 VL 监测对于直接儿科治疗和临床护理至关重要。通常建议在治疗开始后的第一年及随后每 6 个月进行一次，但是标准护理 (SOC) VL 系统的周转时间较慢（中位护理点 (POC) 技术为 21 天）。彻底改变了 HIV 诊断和治疗的开始，POC VL 检测是 HIV 的下一个前沿目前正在评估儿童 POC VL 测试的临床效果。肯尼亚正在进行的随机试验（R34 PI：Patel、Abuogi）；然而，临床之间存在很大差距使用系统工程优化 POC VL 测试的有效性和实际应用。方法将有助于实现 POC VL 监控投资的全面影响。在当前的提案中，我们采用了这种方法。系统工程方法并借鉴不同领域的方法，例如制造、心理学、和软件开发以实现以下目标：目标 1：确定有限的最佳布局中心辐射型与平台共享模型中的 POC VL 机器，以平衡预算影响并最大限度地减少我们将创建一个排队模型 - 用于工业工程中的等待时间建模 - 以确定 POC 机器在肯尼亚的最佳布局我们将模拟周转时间的缩短和与在选定的“中心”设施（设有 POC 机器的站点）放置 POC 机器相关的等待时间和“辐射”（将样本发送到中心的站点）设施与不同设施之间的平台共享。预算水平下，我们将确定 POC 机器的最佳数量和放置位置。目标 2：确定。政策制定者对目标 1 模型工具可用性的看法。我们将把目标 1 的模型转换为用户友好的、基于 Excel 的模型，供政策制定者用于决策。我们将进行可用性。与约 20 名受访者进行访谈（涵盖易学性、效率、记忆性、错误恢复和满意度）卫生管理者和决策者了解该工具的多种方法的新颖应用。工业工程、软件工程、心理学和质量改进提出了创新提高儿童 POC VL 测试可扩展性的方法。