无访问EMR数据:综合治理,数字健康和OMOP-CDM
Christine Mary Hallinan1, Roger Ward2, Graeme K Hart3
1Health and Biomedical Informatics Centre, Research Information Technology Unit (HaBIC R2), Department of General Practice and Primary Care, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia hallinan@unimelb.edu.au dboyle@unimelb.edu.au.
观察医疗结果伙伴关系共同数据模型 (OMOP-CDM) 标准化电子病历 (EMR) 数据,以实现安全,高效的研究. 这种方法提高了数据的互操作性,并使跨机构分析能够在没有直接数据共享的情况下进行.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 流行病学 流行病学
背景情况:
- 电子病历 (EMR) 数据是复杂而异质的.
- 现有的数据存储库已经建立了治理流程.
- 为研究提供安全和有效的数据访问是一个重大挑战.
研究的目的:
- 描述观察医学结果伙伴关系共同数据模型 (OMOP-CDM).
- 概述EMR数据库的治理流程.
- 展示OMOP-CDM如何为医疗提供者和研究人员提供高效和安全的EMR数据访问.
主要方法:
- 使用假名化和共同的数据质量评估.
- 将复杂的EMR数据转换为标准化的OMOP-CDM格式.
- 开发共享的端到端分析包,用于非识别,聚合数据.
主要成果:
- OMOP-CDM为数据标准化和分析提供了一个强大的框架.
- 通过非识别数据共享和本地防火墙,增强数据安全性和隐私.
- 支持各种研究项目和医疗服务运营报告.
结论:
- 通过标准化EMR数据,OMOP-CDM的采用改变了健康数据分析.
- 简化治理,并促进快速,可重复的跨机构分析.
- 能够在不同的医疗保健环境中分析EMR数据的共同平台.
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