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InterSystems IRIS for Health

FHIR-based Healthcare Application Development. Advanced Interoperability. Unprecedented Speed. Massive Scale.
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Create Information-Rich Healthcare Applications, Faster

InterSystems IRIS for Health™ is a comprehensive, cloud-first digital health development platform that provides all the building blocks needed to work with any healthcare data standard, including HL7® FHIR®. It gives you the fastest route to getting innovative healthcare apps up and running quickly and delivering sustainable value.

InterSystems IRIS for Health is used by leading independent software vendors and healthcare organizations, the largest clinical laboratories, and the largest regional health information networks. It is an extension of the InterSystems IRIS Data Platform used by Epic to support healthcare organizations whose systems count 2.5 million concurrent users, processing roughly 1.8 billion database accesses per second across all Epic customers.

Our History Helps You Chart the Future

From the earliest days of health IT, the industry has relied on and grown with InterSystems. Our healthcare interoperability and integration capabilities have been at or near the top of KLAS rankings for over a decade, and are used by companies like 3M, Optum, and Conifer Health to provide connectivity for their software solutions.

Data Services Built to Understand Healthcare and Clinical Research

Healthcare Interoperability and Data Standards

Deep support for FHIR, HL7 V2, IHE and other global healthcare information protocols and messaging formats enable the integration and interoperability of health applications.

Healthcare Data Management

An extensible FHIR repository and comprehensive REST APIs provide the foundation for modern healthcare application development and help you seamlessly handle multiple forms of data at high speed, with vertical and horizontal scalability.

Research Data Management

For clinical research, InterSystems IRIS for Health is a development platform that supports both i2b2 tools and the Observation Medical Outcomes Partnership (OMOP) Common Data Model (CDM), and is fully compatible with Observational Health Data Sciences and Informatics ( OHDSI) collaborative open-source tools. InterSystems OMOP Platform provides a scalable, managed solution for populating your OMOP repository with real-world EHR data using standard bulk FHIR downloads and data transformations.

Healthcare Analytics Framework

Include analytics and AI in your solutions using our open analytics platform, with your choice of embedded, standards-based, and best-of-breed analytics technologies for exploration, analysis, and prediction.

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Connectivity for Creativity

InterSystems IRIS for Health smart data services offer the capabilities you need to start developing in minutes:
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Spin up a FHIR server in the cloud with InterSystems IRIS FHIR Server
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Transform HL7 v2 messages to FHIR to populate a FHIR server using InterSystems FHIR Transformation Service
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Develop mobile, digital health applications to complement new device offerings using the full InterSystems IRIS for Health platform
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Establish an i2b2 clinical research repository – InterSystems IRIS for Health is a recognized platform
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Leverage out-of-the-box interoperability services to build connected health applications
If you can dream it, you can create and deliver it with InterSystems IRIS for Health. Try it yourself.

Try InterSystems IRIS for Health

Frequently Asked Questions

What development languages does InterSystems IRIS for Health support?
InterSystems IRIS for Health supports Python, Java, C# / .NET, Node.js, and ObjectScript.
What types of healthcare applications can I build--or connect--using InterSystems IRIS for Health?
Any app that needs to provide insights from diverse data.

  • Health information systems that deliver intelligent workflows with real-time analytics
  • Moving large, connected, healthcare data-intensive applications to the cloud
  • Building new connected health solutions that incorporate data from multiple sources using different standards
  • Clinical research applications examining large pools of data sources (e.g. clinical trials based on real-world evidence, population health initiatives)
  • Apps for the Internet of Healthy Things
  • Serving up massive quantities of clean data for machine learning or AI initiatives

Customer Success Stories

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