Extraction of Health Condition Type from Personal Histories of Specific Medical Examination

Naoki Ikabata, Y. Seki, Junya Hujisaki, T. Sanada, Azusa Kamachi, Mika Tanigawa
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Abstract

: In Japan, Specific medical examination is conducted for national health insurance subscribers of 40 to 74 years old to prevent lifestyle-related diseases. However, problems remain in effective utilization of these examination results. In this research, we classify health condition types using SOM, one of clustering method, from the Specific health examination results of Izumi City, Osaka Prefecture. We also examined how these types change. As a result of SOM, health conditions were divided into 20 nodes, and it was found that these nodes are characterized by blood pressure, blood glucose level and so on respectively. We divide these nodes into three patterns: healthy, boundary and metabolic. The metabolic pattern was found to have higher medical expenses and medical treatment rates than healthy pattern. In addition, it was found that each pattern transits via the boundary pattern during the 6 years, i.e. data collection term. Furthermore, the medical cost has been on an upward trend at any node, however we can confirmed the node which has transition to a node with a low medical expenses, and in these node, increase in medical expenses are suppressed. Our future work is how to reduce medical expenses by human intervention such as health classroom.
从特定医学检查个人病史中提取健康状况类型
在日本,为预防与生活方式有关的疾病,对40至74岁的国民健康保险投保人进行了专门的体检。然而,如何有效利用这些检测结果还存在一些问题。在本研究中,我们从大阪府泉市的特定健康检查结果中,使用聚类方法中的SOM对健康状况类型进行分类。我们还研究了这些类型是如何变化的。SOM将健康状况分为20个节点,发现这些节点分别以血压、血糖水平等为特征。我们将这些节点分为三种类型:健康型、边界型和代谢型。代谢型患者的医疗费用和就医率均高于健康型患者。此外,在数据收集的6年时间里,发现每个模式都通过边界模式过境。此外,在任何节点上,医疗费用都呈上升趋势,但我们可以确定哪些节点已经过渡到医疗费用较低的节点,并且在这些节点上,医疗费用的增长受到抑制。我们未来的工作是如何通过健康课堂等人为干预来降低医疗费用。
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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