The article discusses the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) and its role in enabling secure and efficient access to electronic medical record (EMR) data. The OMOP-CDM provides a standardized framework for converting complex EMR data into a common format, allowing for shared end-to-end analysis packages without direct data exchange. This approach enhances data security and privacy by keeping patient-level data securely firewalled within local sites. The OMOP-CDM supports a wide range of clinical, epidemiological, and translational research projects, as well as health service operational reporting. The OMOP-CDM is part of the Observational Health Data Sciences and Informatics (OHDSI) consortium, which addresses challenges in EMR data integration by transforming each EMR database into the open-source OMOP-CDM. This process involves translating EMR data elements into standardized terminologies such as SNOMED-CT, LOINC, and RxNORM. The OMOP-CDM is open-source, allowing for collaboration and community-driven development, promoting transparency, innovation, and widespread accessibility. The adoption of the OMOP-CDM has been increasing globally, with over 12% of EMRs converted by 2022, encompassing data from 453 databases across 41 countries. In Australia, the OMOP-CDM has been adopted by various healthcare institutions, including tertiary hospitals, specialized hospitals, joint replacement registries, and the Australian Electronic Practice-Based Research Network (AU-ePBRN). However, there are limitations, such as the lack of seamless linkage between hospital and primary care data sources. The OMOP-CDM aligns with the principles of FAIR (Findable, Accessible, Interoperable, Reusable), CARE (Collective benefit, Authority, Researcher, Ethics), and the Five Safes, ensuring ethical data use, data quality, and security. It supports secure and firewalled environments for advanced analytics and prediction techniques, ensuring data is available for a wide range of research applications. The OMOP-CDM also adheres to the CARE principles for Indigenous data governance, ensuring data is used in a way that respects Indigenous Peoples' rights and interests. The OMOP-CDM facilitates data governance, ethical review, and consent processes, ensuring that data is used ethically and transparently. It allows for the secure sharing of de-identified and aggregated data, enabling collaborative research without the need for direct data sharing. The OMOP-CDM also supports risk mitigation strategies, such as the use of pseudonymisation, secure data management, and access control policies to protect patient privacy. Despite its benefits, the OMOP-CDM faces challenges, including the need for comprehensive funding to map data from local EMRs to the common format. However, the global community's commitment to the OMOP-CDM highlights its potential to transform healthcare researchThe article discusses the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) and its role in enabling secure and efficient access to electronic medical record (EMR) data. The OMOP-CDM provides a standardized framework for converting complex EMR data into a common format, allowing for shared end-to-end analysis packages without direct data exchange. This approach enhances data security and privacy by keeping patient-level data securely firewalled within local sites. The OMOP-CDM supports a wide range of clinical, epidemiological, and translational research projects, as well as health service operational reporting. The OMOP-CDM is part of the Observational Health Data Sciences and Informatics (OHDSI) consortium, which addresses challenges in EMR data integration by transforming each EMR database into the open-source OMOP-CDM. This process involves translating EMR data elements into standardized terminologies such as SNOMED-CT, LOINC, and RxNORM. The OMOP-CDM is open-source, allowing for collaboration and community-driven development, promoting transparency, innovation, and widespread accessibility. The adoption of the OMOP-CDM has been increasing globally, with over 12% of EMRs converted by 2022, encompassing data from 453 databases across 41 countries. In Australia, the OMOP-CDM has been adopted by various healthcare institutions, including tertiary hospitals, specialized hospitals, joint replacement registries, and the Australian Electronic Practice-Based Research Network (AU-ePBRN). However, there are limitations, such as the lack of seamless linkage between hospital and primary care data sources. The OMOP-CDM aligns with the principles of FAIR (Findable, Accessible, Interoperable, Reusable), CARE (Collective benefit, Authority, Researcher, Ethics), and the Five Safes, ensuring ethical data use, data quality, and security. It supports secure and firewalled environments for advanced analytics and prediction techniques, ensuring data is available for a wide range of research applications. The OMOP-CDM also adheres to the CARE principles for Indigenous data governance, ensuring data is used in a way that respects Indigenous Peoples' rights and interests. The OMOP-CDM facilitates data governance, ethical review, and consent processes, ensuring that data is used ethically and transparently. It allows for the secure sharing of de-identified and aggregated data, enabling collaborative research without the need for direct data sharing. The OMOP-CDM also supports risk mitigation strategies, such as the use of pseudonymisation, secure data management, and access control policies to protect patient privacy. Despite its benefits, the OMOP-CDM faces challenges, including the need for comprehensive funding to map data from local EMRs to the common format. However, the global community's commitment to the OMOP-CDM highlights its potential to transform healthcare research