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山东大学学报(医学版) ›› 2017, Vol. 55 ›› Issue (6): 1-29.doi: 10.6040/j.issn.1671-7554.0.2017.430

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健康医疗大数据驱动的健康管理学理论方法体系

薛付忠1,2   

  1. 1.山东大学公共卫生学院生物统计学系, 山东 济南 250012;2.山东大学齐鲁生物医学大数据研究中心, 山东 济南250012
  • 收稿日期:2017-05-10 出版日期:2017-06-10 发布日期:2017-06-10
  • 通讯作者: 薛付忠. xuefzh@sdu.edu.cn E-mail:uefzh@sdu.edu.cn
  • 基金资助:
    国家国际科技合作专项项目(2014DFA32830);国家自然科学基金(81273177,81573259)

Healthcare big data-driven theory and methodology for health management

XUE Fuzhong1,2   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Cheeloo Research Center for Biomedical Big Data, Shandong University, Jinan 250012, Shandong, China
  • Received:2017-05-10 Online:2017-06-10 Published:2017-06-10

摘要: 当今互联网、云计算和物联网技术的成熟和发展,医疗/卫生信息化的广泛普及,使得医疗/卫生相关数据正在以惊人的速度增长;同时,组学技术(基因组、影像组等)的推广应用,以及可穿戴移动医疗与移动健康技术的迅猛发展,促使健康医疗领域快速进入“大数据”时代;“健康医疗大数据驱动的健康管理”的新时代已经来临,即大数据驱动的健康/疾病管理实践已经成为现实。基于此,创建了涵盖健康/疾病检测、风险评估与干预的“大数据驱动的健康/疾病管理学的理论方法体系”。该体系包括健康医疗大数据背景下生命历程流行病学与暴露组学理论指导的健康/疾病管理学理论框架与概念模型、健康/疾病检测指标筛选及证据获取的理论方法、健康/疾病风险评估的理论方法、制定健康/疾病干预策略的理论方法。该体系对于指导大数据驱动的健康/疾病管理的理论和实践、推进健康/疾病管理学转型升级和健康医疗大数据产业化发展具有理论和实际意义。

关键词: 健康医疗大数据, 健康/疾病管理学, 理论方法体系, 健康/疾病检测, 风险评估, 干预策略

Abstract: Todays Internet, cloud computing and networking technology is mature and developed, and the widespread adoption of medical/health information makes medical/health-related data grow at a staggering rate. At the same time, 山 东 大 学 学 报 (医 学 版)55卷6期 -薛付忠.健康医疗大数据驱动的健康管理学理论方法体系 \=-the popularization and application of omics technology(genome, radiomics, etc.)and the rapid development of wearable mobile medical care and mobile health technologies have promoted health care filed quickly into the “big data” era; This suggests that a new era for “health care big data-driven health/disease management” has come, that is, big data-driven health/disease management practices have become a reality. Based on this, we have developed a “health care big data-driven theory and methodology of health/disease management” that covers health/disease detection, risk assessment and intervention. The system includes the health/disease management theoretical framework and conceptual model by the guidance of life course epidemiology and exposome theory under the background of healthcare big data, health/disease detection index screening and evidence acquisition methods, health/disease risk assessment methods and the development of a theoretical approach to health/disease intervention strategies. It is of great theoretical and practical significance to guide the theory and practice development of big data-driven health/disease management, promote the transformation and upgrading of health/disease management and the industrialization of healthcare big data.

Key words: health/disease management, intervention strategy, theory and methodology, health/disease detection, healthcare big data, risk assessment

中图分类号: 

  • R1
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