Estimation of temporal evolution of personal condition from medical service history and its application

• Project/Area Number: 15K00435
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Web informatics, Service informatics
• Research Institution: Gunma University
• Principal Investigator: Seki Yoichi 群馬大学, 大学院理工学府, 教授 (90196949)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Project Status: Completed (Fiscal Year 2017)
• Budget Amount: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000); Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000); Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000); Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
• Keywords: データマイニング / ビッグデータ解析 / 自己組織化マップ / 状態遷移 / 最尤法 / 医療保険サービス / 特定健康診査

Outline of Final Research Achievements

As an empirical analysis, we used the medical service history data (Recept Data of National Health Insurance and Specific Medical Examination Result) of Izumi City, Osaka Prefecture, from FY2011 to FY2016, and data of the exercise instruction program in the period. From the specific medical examination data, the health condition type was extracted by the self-organizing map, and the major disease name and medical cost for each type were obtained using the recept data, and the disease risk etc. of each type was clarified. In addition, as a result of considering the change in health condition type during the 6 years, it is suggested that medical expenses and rates of treatment accepter of the types corresponding to metabolic syndrome is larger than the other types, and that the exercise instruction program contribute to improving health condition. We also studied development of self-organizing map by maximum likelihood method.

Research Products

• [Presentation] Extraction of health condition type from personal histories of specific medical examination (2017)
  • Author(s): Naoki Ikabata, Yoichi Seki, Jyunya Hujisaki, Takashi Sanada, Azusa Kamachi, Mika Tanigawa,
  • Organizer: 15th ANQ Congress
  • Int'l Joint Research
• [Presentation] 自己組織化マップによる大規模データ中の多様性の把握法 (2016)
  • Author(s): 関 庸一, 川名純平, 諏訪竜也
  • Organizer: 日本経営工学会秋季大会
  • Place of Presentation: 日本教育会館
  • Year and Date: 2016-10-29
• [Presentation] 最尤自己組織化マップによる計数値ベクトルのセグメンテーション (2016)
  • Author(s): 茂木亮祐, 関 庸一
  • Organizer: 統計関連学会連合大会
  • Place of Presentation: 金沢大学
  • Year and Date: 2016-09-05
• [Presentation] 特定健康診査データからの健康状態類型の抽出 (2016)
  • Author(s): 五十畑直紀, 関 庸一, 藤崎 淳矢, 真田 崇, 蒲地 梓, 谷川 美香
  • Organizer: 日本品質管理学会第110回研究発表会
  • Place of Presentation: 日本科学技術連盟・東高円寺ビル(東京都・杉並区)
  • Year and Date: 2016-05-28