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综合医院大数据应用需求调查与分析
引用本文:黄小龙,罗旭,汪鹏等.综合医院大数据应用需求调查与分析[J].西北植物学报,2018,38(1):69-71.
作者姓名:黄小龙  罗旭  汪鹏等
摘    要: 目的 分析综合医院对于大数据应用的内在需求,为医院的大数据研发与应用提供导向和依据。方法 采用德尔菲法自制医院大数据应用需求调查问卷,随机抽取中国研究型医院学会医疗分会64家会员单位进行调查,获得有效问卷104份,有效回收率为94.55%。结果 精准医疗(4.31±0.42)分,精益管理(4.23±0.56)分,科学研究(4.19±0.52)分,健康管理(4.16±0.52)分,数字医疗(4.06±0.60)分,教育培训(3.69±0.69)分。不同性别、年龄、职称、岗位组间的需求差异有统计学意义(P<0.05)。多元线性回归分析结果显示,医学人工智能(b=0.324,P=0.000)和互联网+医疗(b=0.161,P=0.047)的需求程度会对医院大数据应用前景态度产生显著的正向影响关系。结论 综合性医院对大数据具有较强的、多样化的应用需求,应以实际需求为导向,重点推进精准医疗、医学人工智能和互联网+医疗等相关应用的研发。

关 键 词:综合性医院  大数据  应用需求

Investigation and Analysis of the Application Demand for Big Data in Comprehensive Hospitals
Abstract: Objective To deeply analyze the comprehensive hospitals of inner need for big data of application and provide the guidance and evidence for development and application of big data in comprehensive hospitals. Method Self-designed questionnaire for application need of big data in comprehensive hospitals was achieved scientifically on the basis of Delphi method, which was given to 64 comprehensive hospitals randomly selected from medical branch of Chinese Research Hospital Association. 104 effective questionnaires were reclaimed and effective rate of return was 94.55%. Result Precision medicine is (4.31±0.42), lean management is (4.23±0.56), scientific research is (4.19±0.52), health management is (4.16±0.52), digital medicine is (4.06±0.60), and education training is (3.69±0.69). There is statistical significance among different groups of gender, age, professional title and post groups (P< 0.05). The results from multiple linear regression analysis manifest that medical artificial intelligence (b=0.324, P=0.000) and internet plus medicine (b=0.161, P=0.047) have a positive influence on application prospect of big data in comprehensive hospitals. Conclusion Obviously, comprehensive hospitals have an urge for application of big data. Therefore, propelling the development and application of big data in comprehensive hospitals should be guided by actual needs and supported by information technologies, focusing on precision medicine as the breakthrough.
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