王丹丹,徐雪静

Research on the influencing factors of health care big data reuse for scientific researchersBased on the theoretical perspective of SOR model

摘要:

揭示科研人员健康医疗大数据重用影响因素及其作用机理,以期为健康医疗大数据平台服务水平的提高和相关政策措施的制定提供参考和借鉴。文章基于SOR理论模型,以平台性能、服务功能、数据质量、数据访问许可的可获取性和组织支持作为刺激因素,将感知努力、感知价值和感知信任作为反应机体,构建健康医疗大数据重用意愿的影响因素模型,采用问卷调查和结构方程分析进行实证检验。研究发现,感知信任、感知价值和感知努力是影响重用意愿的直接因素,其中感知信任在反应机体因素中影响最大,然后依次是感知价值和感知努力；平台性能、服务功能、数据质量、数据访问许可的可获取性和组织支持通过个体感知对重用意愿有间接影响；平台服务功能对感知价值影响不显著。最后提出从数据安全访问环境、可信与场景牵引平台服务、统一数据质量标准和验证技术、聚焦研究氛围与激励措施四方面,提供科研人员健康医疗大数据重用意愿的相关建议和策略。

关键词:科研人员;健康医疗;大数据;数据重用;SOR理论;

Abstract:

This paper reveals the influencing factors and mechanism of health care big data reuse by researchers, in order to provide reference for the improvement of the service level of health care big data platform and the formulation of relevant policies and measures. Based on the SOR theoretical model, this paper takes platform performance, service function, data quality, availability of data access permission, and organizational support as stimuli as stimuli and perceived effort, perceived value and perceived trust as the response organism, constructs a model of the influencing factors of health care big data reuse intention, and uses questionnaire survey and structural equation analysis to conduct empirical tests. The results show that perceived trust, perceived value and perceived effort are the direct factors influencing the willingness to reuse, among which perceived trust has the greatest impact on the body"s factors, followed by perceived value and perceived effort. Platform performance, service functionality, data quality, availability of data access permissions, and organizational support have an indirect impact on reuse willingness through individual perception; The platform service function has no significant impact on the perceived value. Finally, this paper proposes to provide relevant suggestions and strategies for researchers" willingness to reuse big data in health care from four aspects: data security access environment, trusted and scenario-driven platform services, unified data quality standards and verification technologies, and focus on research atmosphere and incentive measures.

Key words:scientific researchers; health care; big data; data reuse; SOR theory;