Seamless EMR data access: Integrated governance, digital health and the OMOP-CDM

Hallinan, CM; Ward, R; Hart, GK; Sullivan, C; Pratt, N; Ng, AP; Capurro, D; Van Der Vegt, A; Liaw, ST; Daly, O; Luxan, BG; Bunker, D; Boyle, D

Author(s): Hallinan, CM; Ward, R; Hart, GK; Sullivan, C; Pratt, N; Ng, AP; Capurro, D; Van Der Vegt, A; Liaw, ST; Daly, O; Luxan, BG; Bunker, D; Boyle, D;
Details: Publication Year 2024-02-21,Volume 31,Issue #1,Page e100953
Journal Title: BMJ Health & Care Informatics
Publication Type: Review
Abstract: 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.
Publisher: BMJ
Keywords: Humans; *Digital Health; *Electronic Health Records; Delivery of Health Care; Databases, Factual; Data Management; Clinical Governance; Electronic Data Processing; Electronic Health Records; Information Systems; Medical Informatics
Department(s): Clinical Haematology
Publisher's Version: https://doi.org/10.1136/bmjhci-2023-100953
Open Access at Publisher's Site: https://doi.org/10.1136/bmjhci-2023-100953
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2024-04-02 04:06:00

Last Modified: 2024-04-02 04:14:45