■患者监控软件会生成大量数据,这些数据可以重新用于临床审核和科学研究。观察性健康数据科学与信息学(OHDSI)联盟开发了观察性医学成果伙伴关系(OMOP)通用数据模型(CDM),以标准化电子健康记录数据并促进大规模观察和纵向研究。
■本研究旨在将初级保健数据转换为OMOPCDM格式。
■我们从沃特雷洛斯多学科健康中心的电子健康记录中提取初级保健数据,法国。我们在本地初级保健数据库的设计与OMOPCDM表和字段之间进行了结构映射。当地法语词汇概念被映射到OHDSI标准词汇。为了验证将初级保健数据实施为OMOPCDM格式,我们应用了一组查询。通过仪表板的开发实现了实际应用。
■将18,395名患者的数据纳入OMOPCDM,相当于20年的592,226次磋商。总共执行了18个OMOP清洁发展机制表。共有17个地方词汇被确定为与初级保健相关,并与患者特征(性别,location,出生年份,和种族),计量单位,生物识别措施,实验室测试结果,病史,和药物处方。在语义映射期间,10,221个初级保健概念被映射到标准的OHDSI概念。通过将完成转换后获得的结果与在源软件中获得的结果进行比较,使用五个查询来验证OMOPCDM。最后,开发了一个原型仪表板来可视化健康中心的活动,实验室测试结果,和药物处方数据。
■来自法国医疗机构的初级保健数据已实施为OMOPCDM格式。有关人口统计的数据,units,测量,OHDSI词汇中已经提供了初级保健咨询步骤。将实验室测试结果和药物处方数据映射到可用的词汇表,并在最终模型中进行结构化。仪表板应用程序为医疗保健专业人员提供了有关其实践的反馈。
UNASSIGNED: Patient-monitoring software generates a large amount of data that can be reused for clinical audits and scientific research. The Observational Health Data Sciences and Informatics (OHDSI) consortium developed the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to standardize electronic health record data and promote large-scale observational and longitudinal research.
UNASSIGNED: This
study aimed to transform primary care data into the OMOP CDM format.
UNASSIGNED: We extracted primary care data from electronic health records at a multidisciplinary health center in Wattrelos, France. We performed structural mapping between the design of our local primary care database and the OMOP CDM tables and fields. Local French vocabularies concepts were mapped to OHDSI standard vocabularies. To validate the implementation of primary care data into the OMOP CDM format, we applied a set of queries. A practical application was achieved through the development of a dashboard.
UNASSIGNED: Data from 18,395 patients were implemented into the OMOP CDM, corresponding to 592,226 consultations over a period of 20 years. A total of 18 OMOP CDM tables were implemented. A total of 17 local vocabularies were identified as being related to primary care and corresponded to patient characteristics (sex, location, year of birth, and race), units of measurement, biometric measures, laboratory test results, medical histories, and drug prescriptions. During semantic mapping, 10,221 primary care concepts were mapped to standard OHDSI concepts. Five queries were used to validate the OMOP CDM by comparing the results obtained after the completion of the transformations with the results obtained in the source software. Lastly, a prototype dashboard was developed to visualize the activity of the health center, the laboratory test results, and the drug prescription data.
UNASSIGNED: Primary care data from a French health care facility have been implemented into the OMOP CDM format. Data concerning demographics, units, measurements, and primary care consultation steps were already available in OHDSI vocabularies. Laboratory test results and drug prescription data were mapped to available vocabularies and structured in the final model. A dashboard application provided health care professionals with feedback on their practice.