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

BMJ Health Care Inform

Health 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

Published: February 2024

AI Article Synopsis

  • The Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) standardizes electronic medical record (EMR) data, making it easier for health service providers and researchers to access and analyze the data securely.
  • It uses techniques like pseudonymisation and common data quality assessments to protect patient privacy while allowing for the efficient sharing of de-identified, aggregated data for research.
  • By simplifying governance and promoting interoperability, the OMOP-CDM supports various clinical and epidemiological research initiatives, enabling faster and more accurate analysis across different healthcare systems without direct data exchange.

Article Abstract

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. 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. 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. 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. 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10882353PMC
http://dx.doi.org/10.1136/bmjhci-2023-100953DOI Listing

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