Big Data in the Population and Reproductive Health Science Data Sharing Platform:Accelerating Value and Innovation of Healthcare Research
Healthcare stakeholders now have access to promising new threads of knowledge.This information is a form of big data, so called not only for its sheer volume but for its complexity, diversity, and timellness.1 Pharmaceutical-industry experts, payors, and providers are now beginning to analyze big data to obtain insights.Although these efforts are still in their early stages, they could collectively help the industry address problems related to variability in healthcare quality and escalating healthcare spend.For instance, researchers can mine the data to see what treatments are most effective for particular conditions, identify patterns related to drug side effects or hospital readmissions, and gain other important information that can help patients and reduce costs.Fortunately, recent technologic advances in the industry have improved their ability to work with such data, even though the files are enormous and often have ditferent database structures and technical characteristics.Based on experience with senior leaders in other industries, we have compiled a short list of guiding principles that are universally applicable in advancing the big-data agenda for the development of Population and Reproductive Health Science Data Sharing Platform.
health informatics cloud computing big data workflow user interface data integration analysis security
Jing Dong Jadad Alex Huilong Duan Lianglin Hu
WHO Collaborating Center for Research in Human Reproduction; National Research Institute for Family Department of Telehealth Engineering, University of Toronto Toronto, Canada College of Biomedical Engineering & Instrument Science of Zhejiang University, Hangzhou, China Computer Network Information Centre Chinese Academy of Sciences Beijing, China
国际会议
武汉
英文
187-193
2013-10-25（万方平台首次上网日期，不代表论文的发表时间）