Cai Yong, Abouzahra Mohamed
IQVIA, 1 IMS Dr, Plymouth Meeting, PA, 19426, USA.
California State University at Monterey Bay, Marina, USA.
Int J Health Econ Manag. 2023 Mar;23(1):133-147. doi: 10.1007/s10754-022-09335-8. Epub 2022 Jul 24.
Physicians interact and exchange information through various social networks. Understanding peer effects through different networks can help accelerate new medical technology and innovative treatment adoption. In this research, we measure the influence of strong-tie and weak-tie connections on new drug adoption and study the overlap between advice-discussion and patient-sharing network. We construct two physician networks with strong and weak ties from peer nomination surveys and commercial medical claims data. We design a dynamic system to define peer adoption status and build patient-level hierarchical logistic models to measure the peer influence on new product adoption for treating new-to-therapy patients. Our results show that A strong-tie early adoption peer has six times more influence on new drug adoption than a weak-tie peer. Weak tie peers collectively exert as much or higher influence than strong-tie peers because of the larger network size. In the case of inaccessibility to strong-tie data, researchers can still reliably use the influence of the weak tie data only even though they will lose the effect of the omitted strong ties.
医生通过各种社交网络进行互动和信息交流。通过不同网络理解同伴效应有助于加速新医疗技术和创新治疗方法的采用。在本研究中，我们衡量强关系和弱关系连接对新药采用的影响，并研究建议讨论网络和患者分享网络之间的重叠情况。我们从同伴提名调查和商业医疗理赔数据构建了两个具有强关系和弱关系的医生网络。我们设计了一个动态系统来定义同伴采用状态，并建立患者层面的分层逻辑模型，以衡量同伴对治疗新疗法患者的新产品采用的影响。我们的结果表明，强关系早期采用同伴对新药采用的影响比弱关系同伴大六倍。由于网络规模较大，弱关系同伴集体发挥的影响与强关系同伴相当或更大。在无法获取强关系数据的情况下，研究人员即使会失去被省略的强关系的影响，仍然可以仅可靠地使用弱关系数据的影响。
