用里奇曲率来描述医生推网络的特征
Jeremy Wayland1,2, Russell J Funk3, Bastian Rieck1,2,4
1Technical University of Munich School of Computation, Information and Technology Arcisstraße 21 80333 Munich Germany.
本研究使用网络曲率来确定美国的医疗保健接入障碍和有效性指标. 新的方法揭示了护理提供和患者结果的区域差异.
科学领域:
- 网络科学 网络科学
- 医疗保健分析 医疗保健分析
- 计算拓学的计算拓学
背景情况:
- 识别美国获得优质医疗保健的系统性障碍是具有挑战性的.
- 医疗保健有效性的关键指标和医疗保健提供方面的区域差异需要进一步了解.
研究的目的:
- 为了在医生推网络中引入网络曲率的新应用.
- 确定医疗保健效率和区域差异的指标.
- 为分析医疗保健网络结构提供一个开源工具.
主要方法:
- 应用福尔曼-里奇和奥利维尔-里奇曲率测量到医生推网络.
- 利用网络拓来描述网络结构.
- 集成网络功能与当地人口普查数据和医疗保健有效性指标.
主要成果:
- 福曼 - 里奇和奥利维尔 - 里奇曲率测量结果显示,作为医疗保健有效性的指标,具有前景.
- 网络曲线捕捉了重要的区域人口特征和护理服务的差异.
- 该研究确定了网络结构,人口统计数据和患者结果之间的相关性.
结论:
- 网络曲率是分析医生推网络和了解医疗保健差异的宝贵工具.
- 开发的开源工具显然有助于检查医疗保健系统内的复杂关系.
- 通过识别区域差异,研究结果有助于改善医疗保健的获取和质量.
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