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Understanding Decision Making through Complexity in Professional Networks

机译:通过专业网络中的复杂性了解决策

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The attitudes of general practitioners (GP) play an influential role in their decision making about patient treatment and care. Considering the GP-patient encounter as a complex system, the interactions between the GP and their personal network of peers give rise to “aggregate complexity,” which in turn influences the GP’s decisions about patient treatment. This study models aggregate complexity and its influence in decision making in primary care through the use of social network metrics. Professional network and attitudinal data on decision making responsibility from 107 rural GPs were analysed. Social network measures of “density” and “inclusiveness” were used for computing the “interrelatedness” of components within such a “complex system.” The “number of components” and “degree of interrelatedness” were used to determine the complexity profiles, which was then used to associate with responsibility in decision making for each GP. GPs in simple profiles (i.e., with low components and interactions) in contrast to those in nonsimple profiles, indicate a higher responsibility for the decisions they make in medical care. This study suggests that social networks-based complexity profiles are useful for understanding decision making in primary care as it accounts for the role of influence through the professional networks of GPs.
机译:全科医生(GP)的态度在他们对患者治疗和护理的决策中起着重要的作用。考虑到GP与病人的相遇是一个复杂的系统,GP及其同伴的个人网络之间的相互作用会导致“总体复杂性”,进而影响GP对患者治疗的决定。本研究通过使用社交网络指标对总体复杂性及其在初级保健决策中的影响进行建模。分析了来自107个农村全科医生的决策责任的专业网络和态度数据。使用社交网络的“密度”和“包容性”度量来计算这种“复杂系统”中组件的“相互关联”。 “组件数”和“相互关联度”用于确定复杂性概况,然后将其与每个GP的决策责任相关联。与非简单配置文件中的GP相比,简单配置文件中的GP(即组件和交互作用少)表明他们对医疗决策的责任更高。这项研究表明,基于社交网络的复杂性概况有助于理解初级保健中的决策,因为它说明了通过全科医生的专业网络所产生的影响。

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