Open Client Registry (OpenCR)
6.0#9 in identity resolution softwareWebAPILinuxmacOS
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| Fact | Open Client Registry (OpenCR) | Zingg |
|---|---|---|
| Integrations | The documentation describes FHIR R4, HAPI FHIR, OpenHIM, and OpenSearch or Elasticsearch as components or connections in an OpenCR deployment. | Documented connectors include Databricks, Snowflake, Cassandra, S3, Azure, Elastic, Exasol, relational databases and Spark-supported sources. |
| Intended users | The project describes itself as a community project intended for others to adapt to their use cases. | The maker describes Zingg as a tool for analytics engineers and data scientists to integrate data silos and build unified views at scale. |
| Matching | It supports probabilistic and deterministic matching, configurable decision rules, and 25 algorithm variations. | It combines machine learning matching with rule based deterministic matching, which can use identifiers such as email, SSN, and passport ID. |
| Purpose | OpenCR links patient identities across information systems to support clinical safety, continuity of care, and accurate reporting. | Zingg is open source, warehouse native master data management software for resolving entities and building unified views from siloed data. |
| Support | The About page directs users to contact [email protected] and join the OpenCR Slack community. | The comparison page lists open source support for Community and enterprise grade support for both Enterprise editions. |
No prices published.
OpenCR suits organizations that need to link patient identities across systems and support care coordination or reporting. Production deployment is aimed at teams with Linux administration and command-line expertise.
You want what its maker publishes above — check its page for the details.