无缝的 EMR 数据访问:综合治理、数字医疗和 OMOP-CDM

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES BMJ Health & Care Informatics Pub Date : 2024-02-01 DOI:10.1136/bmjhci-2023-100953
Christine Mary Hallinan, Roger Ward, Graeme K Hart, Clair Sullivan, Nicole Pratt, Ashley P Ng, Daniel Capurro, Anton Van Der Vegt, Siaw-Teng Liaw, Oliver Daly, Blanca Gallego Luxan, David Bunker, Douglas Boyle
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引用次数: 0

摘要

目的 在本综述中,我们将介绍观察性医疗结果合作组织通用数据模型(OMOP-CDM)、EMR 数据存储库所采用的既定管理流程,并展示 OMOP 转换后的数据如何为医疗服务提供者和研究人员更高效、更安全地访问电子病历(EMR)数据提供杠杆作用。方法 通过化名和通用数据质量评估,OMOP-CDM 为将复杂的 EMR 数据转换为标准化格式提供了一个强大的框架。这样就可以创建共享的端到端分析包,而无需直接交换数据,从而提高了数据的安全性和隐私性。通过安全共享去标识化和汇总数据,并在多个 OMOP 转换数据库中进行分析,患者级数据在各自的本地站点内被安全防火墙隔离。结果 通过简化数据管理流程和治理,并通过促进互操作性,OMOP-CDM 支持了广泛的临床、流行病学和转化研究项目,以及医疗服务运营报告。讨论 在国际和本地采用 OMOP-CDM 能够将大量复杂、异构的 EMR 数据转换为标准化的结构化数据模型,简化管理流程,并通过共享端到端分析包,在不共享数据的情况下,促进快速、可重复的跨机构分析。结论 采用 OMOP-CDM 有可能改变健康数据分析,为分析不同医疗机构的 EMR 数据提供一个通用平台。由于未生成数据集,数据共享不适用。
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Seamless EMR data access: Integrated governance, digital health and the OMOP-CDM
Objectives In this overview, we describe theObservational Medical Outcomes Partnership Common Data Model (OMOP-CDM), the established governance processes employed in EMR data repositories, and demonstrate how OMOP transformed data provides a lever for more efficient and secure access to electronic medical record (EMR) data by health service providers and researchers. Methods Through pseudonymisation and common data quality assessments, the OMOP-CDM provides a robust framework for converting complex EMR data into a standardised format. This allows for the creation of shared end-to-end analysis packages without the need for direct data exchange, thereby enhancing data security and privacy. By securely sharing de-identified and aggregated data and conducting analyses across multiple OMOP-converted databases, patient-level data is securely firewalled within its respective local site. Results By simplifying data management processes and governance, and through the promotion of interoperability, the OMOP-CDM supports a wide range of clinical, epidemiological, and translational research projects, as well as health service operational reporting. Discussion Adoption of the OMOP-CDM internationally and locally enables conversion of vast amounts of complex, and heterogeneous EMR data into a standardised structured data model, simplifies governance processes, and facilitates rapid repeatable cross-institution analysis through shared end-to-end analysis packages, without the sharing of data. Conclusion The adoption of the OMOP-CDM has the potential to transform health data analytics by providing a common platform for analysing EMR data across diverse healthcare settings. Data sharing not applicable as no datasets generated.
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来源期刊
CiteScore
6.10
自引率
4.90%
发文量
40
审稿时长
18 weeks
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