临床数据向通用数据模型转换研究及应用实践

Research and Application of Conversion from Clinical Data to OMOP Common Data Model

目的:通过参与OHDSI(ObservationalHealthDataSciencesandInformatics)研究,挖掘临床大数据的价值,评估OHDSI研究在国内的可行性,并探讨OHDSI研究的有效方法。方法:建立标准化的OMOP通用数据模型(CDM),并成功导入临床数据,在此基础上建设了临床医疗大数据科研分析平台,选择高血压、2型糖尿病、抑郁症三个慢病进行分析研究。结果:分析了高血压、2型糖尿病、抑郁症的治疗路径(用药品种与顺序),并进行了数据可视化,生成图形与图表。结论:通用数据模型的使用,既可实现全院级的科研数据的整合,也在充分保护患者隐私的前提下,为跨医院、跨区域的科研数据共享提供了一个良好的基础,可借助大数据技术开展大规模的合作式科研。

Objective： By participating m OHDSI （Observational Health Data Sciences and Informatics） research, we mined the value of clinical big data to assess the feasibility of OHDSI research in the country, and to explore effective methods of OHDSI research. Methods： We established the standardized OMOP common data model （CDM）, and successfuUy loaded the climcal data in it. On this basis, a platfrom for researching and analyzing clinical big data has been established. We selected three chronic diseases of hypertension, type 2 diabetes and depression to analysis. R.esults： The treatment pathways of hypertension, type 2 diabetes and depression （variety and sequence of medication） were analyzed. Data was visualized to generate graphs and charts. Conclusion： The use of a common data model not only achieves the integration of hospital-wide scientific research data but also provides a good foundation fi）r cross-hospital and inter-regional sharing of scientific data while fully protecting of patient privacy. With the help of big data technology we could carry out large-scale cooperative research.