Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon.
Peiyao LiChen XieTom J PollardAlistair Edward William JohnsonDesen CaoHong-Jun KangHong LiangYuezhou ZhangXiaoli LiuYong FanYuan ZhangWanguo XueLixin XieLeo Anthony CeliZhengbo ZhangPublished in: JMIR medical informatics (2017)
Electronic health records (EHRs) have been widely adopted among modern hospitals to collect and track clinical data. Secondary analysis of EHRs could complement the traditional randomized control trial (RCT) research model. However, most researchers in China lack either the technical expertise or the resources needed to utilize EHRs as a resource. In addition, a climate of cross-disciplinary collaboration to gain insights from EHRs, a crucial component of a learning healthcare system, is not prevalent. To address these issues, members from the Massachusetts Institute of Technology (MIT) and the People's Liberation Army General Hospital (PLAGH) organized the first clinical data conference and health datathon in China, which provided a platform for clinicians, statisticians, and data scientists to team up and address information gaps in the intensive care unit (ICU).
Keyphrases
- electronic health record
- healthcare
- big data
- adverse drug
- public health
- health information
- palliative care
- intensive care unit
- double blind
- machine learning
- data analysis
- mechanical ventilation
- artificial intelligence
- placebo controlled
- extracorporeal membrane oxygenation
- human health
- phase iii
- acute respiratory distress syndrome