Identifying and Measuring Knowledge Spillovers of Health Service Delivery Interventions: A Network Analysis Approach

医疗保健政策可能会产生政策制定者最初打算之外的影响。这些意想不到的影响被称为溢出效应。例如，一项旨在降低美国联邦医疗保险中急性心肌梗死、心力衰竭和肺炎的再住院率的经济处罚政策，与政策未针对的情况的再住院率的降低有关。虽然这种溢出效应的存在越来越被认识到，但对这些溢出效应是如何发生的缺乏了解。在卫生保健领域，一个重要的机制是卫生保健专业人员之间的知识交流。卫生保健专业人员之间的溢出效应分析过去非常昂贵，因为它们需要详细的社会网络地图，而这只能通过基于定性采访和调查问卷的研究来产生。然而，最近发现，仅从行政数据来源就可以准确地推断社交网络。本研究的目的是利用这些新的方法1)构建卫生保健专业人员之间的社会网络，2)根据网络成员的密切程度和成员的特征来描述网络，3)在两个例子中测量溢出的大小，并确定网络的形状和大小以及成员之间的关系如何影响溢出效应。溢出效应的存在可能意味着卫生保健政策的效果被错误地衡量。该项目的最后部分将考虑如何利用卫生保健专业人员之间的网络信息来更准确地衡量新政策的效果。

Health care policies may have effects other than those originally intended by policy makers. These unintended effects are called spillovers. For example, a financial penalty policy intended to reduce readmission rates for acute myocardial infarction, heart failure, and pneumonia in the US Medicare was associated with reductions in readmission rates for conditions that were not targeted by the policy. Although the existence of such spillover effects is increasingly being recognised, there is a lack of understanding of how these spillover effects occur.In health care, an important mechanism is the exchange of knowledge between health care professionals. Analyses of spillovers between health care professionals used to be very costly because they required a detailed mapping of the social network that could only be generated by research based on qualitative interviews and questionnaires. However, it has recently been found that social networks can accurately inferred from administrative data sources alone. The aim of this research is to use these new methods to 1) construct social networks between health care professionals, 2) to describe the networks in terms of how closely related the network members are, and in terms of the characteristics of the members, 3) to measure the size of spillovers in two examples, and determine how the shape and size of the network and the relations between its members affect spillover effects. The existence of spillovers can mean that the effect of health care policies is measured incorrectly. The last part of the project will consider how information about networks between health care professionals can be used to measure the effect of new policies more accurately.