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Characterizing chronic disease and polymedication prescription patterns from electronic health records

机译：从电子健康记录中表征慢性疾病和多药处方模式

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Population aging in developed countries brings an increased prevalence of chronic disease and of polymedication-patients with several prescribed types of medication. Attention to chronic, polymedicated patients is a priority for its high cost and the associated risks, and tools for analyzing, understanding, and managing this reality are becoming necessary. We describe a prototype of a system for discovering, analyzing, and visualizing the co-occurrence of diagnostics, interventions, and medication prescriptions in a large patient database. The final tool is intended to be used both by health managers and planners and for primary care clinicians in direct contact with patients (for example for detecting unusual disease patterns and incorrect or missing medication). At the core of the analysis module there is a representation of diagnostics and medications as a hypergraph, and the most crucial functionalities rely on hypergraph transversal / variants of association rule discovery methods, with particular emphasis on discovering surprising or alarming combinations. The test database comes from the primary care system in the area of Barcelona for 2013, with over 1.6 million potential patients and almost 20 million diagnostics and prescriptions.
机译：发达国家的人口老龄化带来了慢性疾病和多种规定类型的药物治疗患者的患病率增加。注意慢性，聚体化患者是其高成本和相关的风险的优先事项，以及分析，理解和管理这一现实的工具正在成为必要。我们描述了一种用于发现，分析和可视化大型患者数据库中的诊断，干预和药物处方的共同发生的系统的原型。最终工具旨在由卫生经理和规划者和初级保健临床医生使用，直接接触患者（例如检测不寻常的疾病模式和不正确或缺失的药物）。在分析模块的核心，存在诊断和药物作为超图的表示，最重要的功能依赖于关联规则发现方法的超图横向/变体，特别强调发现令人惊讶或惊人的组合。测试数据库来自巴塞罗那面积的初级保健系统于2013年，潜在患者有超过160万次潜在患者和近2000万次诊断和处方。

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