Application of network analysis on healthcare

Fei Wang, Uma Srinivasan, M. S. Uddin, S. Chawla
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引用次数: 23

Abstract

The healthcare sector holds large amounts of semantically rich electronic data generated and used by different sections of the health care community. Data analytic techniques such as data mining and predictive modelling are being used to gain new insights into health care costs, performance and quality of care. In this context, social network analysis (SNA) has the unique ability to play a new role in exploring the context and situations that lead to efficient and effective healthcare. In this paper we describe a specific context of private healthcare in Australia and describe our SNA based approach (applied to health insurance claims) to understand the nature of collaboration among doctors treating hospital inpatients and explore the impact of collaboration on cost and quality of care. In particular, we use network analysis to (a) design collaboration models among surgeons, anaesthetists and assistants who work together while treating patients admitted for specific types of treatments (b) identify and extract specific types of network topologies that indicate the way doctors collaborate while treating patients and (c) analyse the impact of these topologies on cost and quality of care provided to those patients.
网络分析在医疗保健中的应用
医疗保健部门拥有大量语义丰富的电子数据,这些数据由医疗保健社区的不同部门生成和使用。数据挖掘和预测建模等数据分析技术正被用于获得有关医疗保健成本、绩效和质量的新见解。在这种情况下,社会网络分析(SNA)具有独特的能力,可以在探索导致高效和有效的医疗保健的背景和情况方面发挥新的作用。在本文中,我们描述了澳大利亚私人医疗保健的具体背景,并描述了我们基于SNA的方法(适用于健康保险索赔),以了解医生治疗医院住院患者之间合作的性质,并探讨合作对成本和护理质量的影响。特别是,我们使用网络分析来(a)设计外科医生、麻醉师和助手之间的协作模型,他们在治疗接受特定类型治疗的患者时一起工作;(b)识别和提取特定类型的网络拓扑,这些拓扑表明医生在治疗患者时合作的方式;(c)分析这些拓扑对提供给这些患者的护理成本和质量的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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