摘要
基于近几年医疗与健康决策支持的相关研究观点,提出行为级、逻辑级和基于数据分析三个视角。从行为级的流程改善、人的可靠性、医疗风险三个角度归纳医疗管理的品质与效率;逻辑级从系统鲁棒性优化和鲁棒性推理角度,归纳医疗决策系统鲁棒性研究。基于异构实体数据融合、多模态数据管理、数据分治问题,对医疗大数据带来的精准医疗决策相关研究成果进行归纳。提出了数据驱动的医疗决策将成为提高医疗品质与效率的主要手段,特别是互联网环境下智能医疗,将对医疗与健康决策产生颠覆性的影响,成为重要研究方向。
Behavioral level, logic level and data-center perspectives are proposed on the basis of the review on healthcare decision-making support. On behavioral level, from the perspectives of business reengineering, human reliability and medical risk, the research findings on medical quality and efficiency are summarized. On logic level, from the perspective of system robustness optimization and robustness reasoning, the research findings on medical decision-making system are induced. Based on heterogeneous data fusion, multi-modal data management and data partition,the related researches on precision medical decision making are introduced. Data-driven healthcare Decision-making plays the key role in improving medical quality and efficiency, especially in the environments of internet. Intelligent medical system is bringing disruptive imt）acts,which will become animportant research domain in the future.
出处
《工业工程与管理》
CSSCI
北大核心
2017年第1期1-13,共13页
Industrial Engineering and Management
基金
国家自然科学基金资助项目(71571105
71601026)
重庆市教委科学技术研究项目(KJ1600401)
关键词
医疗健康
决策支持
大数据
综述
health care
decision-making support
big data
review
