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Network among HTA ecosystem

机译:HTA生态系统中的网络

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摘要

This study intends to examine the main drivers of network relations among health technology assessment (HTA) organizations. Social network analysis was performed to determine the relations among HTA organizations and to visualize the main drivers of such collaboration. The members in HTA organizations such as International Society for Pharmacoeconomics and Outcomes Research, Health Technology Assessment international, International Network of Agencies for Health Technology Assessment, EuroScan, European Network for Health Technology Assessment, HTAsiaLink, and Health Technology Assessment Network for the Americas are said to create networks. Ten different HTA organizations were considered in the analysis, including the Ministry of Health (MoH) organizations, universities, for-profit organizations, and hospitals. The Fruchterman-Reingold algorithm was used to perform networking, and the average clustering coefficient and average path length were examined to measure collaborative performance. The network graph of the HTA ecosystem shows the highest collaborative frequency among HTA organizations, which are the members of MoH organizations, government agencies, universities, and nonprofit organizations. The average path length was 2.21, and the average clustering coefficient was 36.57, indicating an obvious clustering effect. The study results highlight that networking within the HTA ecosystem is driven by government organizations. Boosting the integration of the private sector into the system and creating data-sharing strategies are essential to foster HTA collaboration. Because HTA is shaped by local dynamics and no gold standard exists for HTA implementation, encouraging collaborative efforts is the only way to avoid redundant efforts and make health technologies available for everyone.
机译:本研究打算审查健康技术评估(HTA)组织之间网络关系的主要驱动因素。进行社交网络分析以确定HTA组织之间的关系,并可视化此类合作的主要驱动因素。国际药物经济学和结果研究,卫生技术评估国际社会,欧洲健康技术评估,欧洲卫生技术评估,HTASialink和健康技术评估网络的国际机构国际社会,卫生技术评估国际社会,如国际电联的组织,欧洲卫生技术评估创建网络。在分析中考虑了十种不同的HTA组织,包括卫生部(MOH)组织,大学,营利组织和医院。 Fruchterman-Reingold算法用于执行网络,检查平均聚类系数和平均路径长度以测量协作性能。 HTA生态系统的网络图显示了HTA组织中的最高协作频率,这些协作频率是MOH组织,政府机构,大学和非营利组织的成员。平均路径长度为2.21,平均聚类系数为36.57,表明聚类效果明显。该研究结果强调了HTA生态系统内的网络由政府组织驱动。促进私营部门的集成到系统中并创建数据共享策略对于培养HTA协作至关重要。由于HTA由本地动态而塑造,并且没有用于HTA实施的黄金标准,令人鼓舞的合作努力是避免冗余努力和为每个人提供健康技术的唯一途径。

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