Paul Sudeshna, Keating Nancy L, Landon Bruce E, O'Malley A James
Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA 30322, USA.
Department of Health Care Policy, Harvard Medical School, Boston, MA 02115-5899, USA.
Soc Sci Med. 2015 Jan;125:51-9. doi: 10.1016/j.socscimed.2014.08.027. Epub 2014 Oct 7.
Professional physician networks can potentially influence clinical practices and quality of care. With the current focus on coordinated care, discerning influences of naturally occurring clusters and other forms of dependence among physicians' relationships based on their attributes and care patterns is an important area of research. In this paper, two directed physician networks: a physician influential conversation network (N = 33) and a physician network obtained from patient visit data (N = 135) are analyzed using a new model that accounts for effect modification of the within-dyad effect of reciprocity and inter-dyad effects involving three (or more) actors. The results from this model include more nuanced effects involving reciprocity and triadic dependence than under incumbent models and more flexible control for these effects in the extraction of other network phenomena, including the relationship between similarity of individuals' attributes (e.g., same-gender, same residency location) and tie-status. In both cases we find extensive evidence of clustering and triadic dependence that if not accounted for confounds the effect of reciprocity and attribute homophily. Findings from our analysis suggest alternative conclusions to those from incumbent models.
专业医生网络可能会影响临床实践和医疗质量。鉴于当前对协调医疗的关注，基于医生的属性和护理模式来识别自然形成的集群以及医生关系中其他形式的依赖性的影响，是一个重要的研究领域。在本文中，使用一种新模型对两个有向医生网络进行了分析：一个医生影响力对话网络（N = 33）和一个从患者就诊数据中获取的医生网络（N = 135），该模型考虑了互惠的二元组内效应和涉及三个（或更多）参与者的二元组间效应的效应修正。与现有模型相比，该模型的结果包括涉及互惠和三元依赖性的更细微差别效应，以及在提取其他网络现象（包括个体属性相似性（如同性、相同住院地点）与关系状态之间的关系）时对这些效应更灵活的控制。在这两种情况下，我们都发现了大量的集群和三元依赖性证据，如果不加以考虑，会混淆互惠和属性同质性的效应。我们的分析结果表明与现有模型的结论不同。
