Open Client Registry (OpenCR)

Open Client Registry (OpenCR) links patient identities across information systems to support care coordination, continuity of care, and reporting. It suits health organizations and technical teams building their own patient registry integrations. Its open-source matching and FHIR exchange are useful, but production deployment requires Linux expertise and a database backend.

Overview

OpenCR is an identity registry, not a shared health record: it matches records across systems but does not hold clinical data. It can assign and look up unique identifiers and accept FHIR messages from point-of-service systems such as labs and EMRs. One important boundary is that those systems cannot retrieve patient demographic information from the registry through the documented implementation.

The project is open source and open standards-based, developed by IntraHealth International with USAID support through MEASURE Evaluation. It is described as a community project intended for others to adapt, rather than a turnkey managed service.

Key features

Configurable identity matching

OpenCR supports probabilistic and deterministic matching, with multiple algorithm variations and a hybrid approach. That flexibility suits deployments that need to tune how records are linked; the UI also lets users inspect records and break matches, giving staff a manual correction path when an automated link is wrong.

FHIR exchange and audit trail

OpenCR accepts FHIR messages from point-of-service systems and supports real-time API use as well as batch file import. Transactions, including queries, are stored as audit events in HAPI FHIR and can be viewed in the UI. This makes it a better fit for an integration workflow than for direct clinical record access.

Deployment components and security

The documented stack combines the OpenCR Service, HAPI FHIR Server, and OpenSearch or Elasticsearch; OpenHIM is optional. Security guidance calls for restricting access to the UI and services, using TLS, changing default passwords, and securing user and node access. JWT and other user authentication solutions are not included out of the box, so deployments needing them must add their own solution.

Pricing

OpenCR is free and open source, with no paid tier described. There is no per-seat or usage price to weigh, but organizations take on the work of deploying and securing the system themselves. The production installation guide expects Linux, command-line familiarity, and Linux administration expertise; HAPI FHIR also needs a database backend such as PostgreSQL or MySQL.

The local installation guide is intended for demonstrations or tests, not production, and lists a modern CPU with 8GB RAM among its prerequisites. For project inquiries, the About page directs users to [email protected] and invites them to join the OpenCR Slack channel.

Platforms

OpenCR is available for Linux, macOS, Windows, web, API, and self-hosted deployments. The production guide specifically expects Linux, so the broader platform list should not be read as a promise that every environment is equally suited to production operation.

Who it's for

OpenCR is strongest for health organizations with technical staff who need an adaptable patient identity layer across information systems and can manage a self-hosted stack. It is a poor fit for teams seeking a ready-made shared clinical record, demographic lookup by point-of-service systems, or built-in user authentication without further deployment work.

Pros and cons

Pros

• Flexible patient matching: probabilistic, deterministic, and hybrid approaches let a deployment adapt matching to its needs.
• FHIR-oriented exchange: real-time API use and batch import support connections to labs and EMRs.
• Manual correction and audit visibility: users can review and break matches, while transactions are retained as audit events viewable in the UI.
• Open-source, free deployment: there is no software plan price, and the project is intended for adaptation.

Cons

• Not a clinical record: it stores identity links rather than patient clinical data, and the documented implementation does not return demographic information to point-of-service systems.
• Production requires operational expertise: Linux administration, command-line familiarity, and a database backend are expected.
• Authentication needs deployment work: user authentication such as JWT is not provided out of the box.

Alternatives

For a different approach to identity resolution, browse Identity Resolution Software. Choose InterSystems IRIS if a paid platform with a free plan and free trial is preferable; its Community Edition is free, though AWS infrastructure costs may apply. Splink is another free open-source option, distributed as a Python package and available for Linux, macOS, Windows, and self-hosting.

Hightouch may suit teams wanting a web and API freemium service: its Free plan allows 2 active syncs per month, hourly syncs, and 100,000,000 operations per month. pyJedAI is a free open-source library with no paid plans or usage limits stated. Zingg offers a free open-source Community plan for batch probabilistic matching at millions of records, while its Enterprise plan adds batch and real-time use.

AWS Entity Resolution is a paid API and web service with no free plan; its Data service provider matching option is billed per 1,000 records processed and requires an additional provider license or subscription. Treasure AI Composable CDP is a paid option with custom pricing and warehouse credits for query execution. Precisely Data Matching and Entity Resolution is a paid Linux, self-hosted, web, and Windows option; pricing requires speaking with an expert.

Verdict

Choose OpenCR if your health organization needs a free, adaptable way to link patient identities and exchange FHIR messages, and has the technical capacity to operate it. Its strongest case is configurable matching with audit visibility; look elsewhere if you need a shared clinical record, demographic retrieval by source systems, or authentication built in.