OpenEMR and Practice Management on Azure

Deploy a production-ready OpenEMR system on Microsoft Azure in minutes, providing electronic health records (EHR), appointment scheduling, medical billing and a patient portal in one assembled and hardened platform. Built for medical practices, clinics and the IT providers who support them, this image eliminates days of LAMP stack installation and security hardening by delivering the latest stable OpenEMR release on a CIS-aligned Linux operating system.

Why OpenEMR, and Why This Image

OpenEMR is one of the world's most widely deployed open-source electronic health record and practice management platforms, with more than two decades of development behind its clinical records, scheduling, billing workflows, X12 claim generation, electronic prescribing, patient portal and FHIR R4 API. It enables healthcare organisations to own and control their clinical systems instead of relying on recurring per-provider subscription platforms.

The challenge is deploying it securely. This image provides a production-ready foundation with the operating system, web server, database stack and application configured and documented for healthcare environments, allowing organisations to focus on implementation rather than infrastructure.

What You Get Out of the Box

• Current stable release of OpenEMR deployed on a tuned production stack.
• FHIR API enabled and documented for integration with external healthcare applications and services.

Common Use Cases

• Private Practices and Clinics – Manage patient records, appointments, billing, claims and clinical workflows in one platform you control.
• Healthcare IT Providers and MSPs – Deliver repeatable, hardened OpenEMR deployments for healthcare customers.
• Billing Workflows – Support encounter coding, X12 837 claim generation and ERA posting for insurance billing.

Choosing Between OpenEMR and OpenMRS

Both OpenEMR and OpenMRS are mature open-source electronic medical record platforms, and CloudSOE provides hardened Azure images for both.

• OpenEMR is designed for medical practices and clinics requiring appointment scheduling, insurance billing, patient portals and comprehensive practice management.
• OpenMRS is intended for global health programmes, research organisations and NGOs that require a highly configurable clinical data platform across multiple sites.

Choose the CloudSOE OpenMRS image if your primary requirement is a flexible clinical data platform rather than a complete practice management solution.

Compliance: Read This Before Storing Patient Data

A virtual machine image alone cannot make a healthcare deployment compliant. Compliance depends on operational controls, organisational processes and the secure configuration of your environment. This image provides a hardened starting point, with documentation covering the remaining shared responsibilities.

• Use Azure managed disk encryption and encryption for backups.
• Deploy resources within private virtual networks wherever practical.
• Restrict access using Network Security Groups, Azure Firewall or VPN connectivity.
• Never expose database services directly to the public Internet.
• Limit administrative access to trusted practice networks or VPN connections.
• If enabling the patient portal, treat it as the only Internet-facing component and isolate it appropriately from backend services.

Sizing Guidance

Healthcare applications require adequate CPU, memory and storage for patient records, document management and concurrent clinical users.

• Evaluation and testing: Standard_D4s_v5 (4 vCPU, 16 GB RAM)
• Single-practice production deployment: Standard_D4s_v5 (4 vCPU, 16 GB RAM) with Premium SSD managed disks and encryption enabled.
• Multi-provider practices or document-intensive workloads: Standard_D8s_v5 (8 vCPU, 32 GB RAM) with Azure Database for MariaDB or MySQL where appropriate, as described in the deployment guide.

Trademark Notice

OpenEMR® is a registered trademark of its respective trademark holder, the OEMR organisation. This product is independently packaged and maintained and is not affiliated with or endorsed by OEMR or the OpenEMR project.