Gu Dongxiao, Li Jingjing, Li Xingguo, Liang Changyong
School of Management, Hefei University of Technology, 193 Tunxi Road, Hefei, Anhui 230009, China.
School of Management, Hefei University of Technology, 193 Tunxi Road, Hefei, Anhui 230009, China; National Joint Engineering Research Center for Intelligent Decision and Information Systems, 193 Tunxi Road, Hefei, Anhui 230009, China.
Int J Med Inform. 2017 Feb;98:22-32. doi: 10.1016/j.ijmedinf.2016.11.006. Epub 2016 Nov 23.
In recent years, the literature associated with healthcare big data has grown rapidly, but few studies have used bibliometrics and a visualization approach to conduct deep mining and reveal a panorama of the healthcare big data field.
To explore the foundational knowledge and research hotspots of big data research in the field of healthcare informatics, this study conducted a series of bibliometric analyses on the related literature, including papers' production trends in the field and the trend of each paper's co-author number, the distribution of core institutions and countries, the core literature distribution, the related information of prolific authors and innovation paths in the field, a keyword co-occurrence analysis, and research hotspots and trends for the future.
By conducting a literature content analysis and structure analysis, we found the following: (a) In the early stage, researchers from the United States, the People's Republic of China, the United Kingdom, and Germany made the most contributions to the literature associated with healthcare big data research and the innovation path in this field. (b) The innovation path in healthcare big data consists of three stages: the disease early detection, diagnosis, treatment, and prognosis phase, the life and health promotion phase, and the nursing phase. (c) Research hotspots are mainly concentrated in three dimensions: the disease dimension (e.g., epidemiology, breast cancer, obesity, and diabetes), the technical dimension (e.g., data mining and machine learning), and the health service dimension (e.g., customized service and elderly nursing).
This study will provide scholars in the healthcare informatics community with panoramic knowledge of healthcare big data research, as well as research hotspots and future research directions.
近年来，与医疗大数据相关的文献迅速增长，但很少有研究使用文献计量学和可视化方法进行深度挖掘并揭示医疗大数据领域的全景。
为了探索医疗信息学领域大数据研究的基础知识和研究热点，本研究对相关文献进行了一系列文献计量分析，包括该领域论文的产出趋势以及每篇论文合著者数量的趋势、核心机构和国家的分布、核心文献分布、多产作者的相关信息以及该领域的创新路径、关键词共现分析以及未来的研究热点和趋势。
通过进行文献内容分析和结构分析，我们发现以下几点：(a) 在早期阶段，来自美国、中华人民共和国、英国和德国的研究人员对与医疗大数据研究及该领域创新路径相关的文献贡献最大。(b) 医疗大数据的创新路径包括三个阶段：疾病早期检测、诊断、治疗和预后阶段、生命与健康促进阶段以及护理阶段。(c) 研究热点主要集中在三个维度：疾病维度（如流行病学、乳腺癌、肥胖症和糖尿病）、技术维度（如数据挖掘和机器学习）以及卫生服务维度（如定制服务和老年护理）。
本研究将为医疗信息学领域的学者提供医疗大数据研究的全景知识以及研究热点和未来研究方向。
