Fast Healthcare Interoperability Resources (FHIR, pronounced "fire") is a draft standard describing data formats and elements (known as "resources") and an Application Programming Interface (API) for exchanging Electronic health records. The standard was created by the Health Level Seven International (HL7) health-care standards organization.
Contents
FHIR builds on previous data format standards from HL7, like HL7 version 2.x and HL7 version 3.x. But it is easier to implement because it uses a modern web-based suite of API technology, including a HTTP-based RESTful protocol, HTML and Cascading Style Sheets for user interface integration, a choice of JSON or XML for data representation, and Atom for results. One of its goals is to facilitate interoperation between legacy health care systems, to make it easy to provide health care information to health care providers and individuals on a wide variety of devices from computers to tablets to cell phones, and to allow third-party application developers to provide medical applications which can be easily integrated into existing systems.
FHIR provides an alternative to document-centric approaches by directly exposing discrete data elements as services. For example, basic elements of healthcare like patients, admissions, diagnostic reports and medications can each be retrieved and manipulated via their own resource URLs. FHIR was supported at an American Medical Informatics Association meeting by companies like Cerner which value its open and extensible nature.
Standardization
In February 2014, Health Level Seven International published FHIR as a "Draft Standard for Trial Use" (DSTU), Release 1, version DSTU 1 (v0.0.82).
In December 2014, a broad cross-section of stakeholders committed to the Argonaut Project which will provide acceleration funding and political will to publish FHIR implementation guides and profiles for query/response interoperability and document retrieval by May 2015. It would then be possible for medical records systems to migrate from the current practice of exchanging complex Clinical Document Architecture (CDA) documents, and instead exchange sets of simpler, more modular and interoperable FHIR JSON objects. The initial goal, to be completed in time for the May 2015 HL7 FHIR Draft Standard for Trial Use revision 2 ballot, is to specify two FHIR profiles that are relevant to the Meaningful Use requirements, along with and an implementation guide for using OAuth 2.0 for authentication.
A DSTU version 2.1 ballot is anticipated in late 2015, and a full standard in 2017.
But even as FHIR standardization proceeds, the CEO of HL7 argued in August 2016 that it already provides valuable features, is ready to use, and is being adopted.
Implementations
A number of high-profile players in the health care informatics field are showing interest in and experimenting with FHIR, including CommonWell Health Alliance and SMArt (Substitutable Medical Applications, reusable technologies). In 2014, the U.S. Health IT Policy and the Health IT Standards committees endorsed recommendations for more public (open) APIs. The JASON task force report on "A Robust Health Data Infrastructure" says that FHIR is currently the best candidate API approach, and that such APIs should be part of stage 3 of the "meaningful use" criteria of the U.S. Health Information Technology for Economic and Clinical Health Act.
Open source implementations of FHIR data structures, servers, clients and tools include reference implementations from HL7 in a variety of languages, SMART on FHIR and HAPI-FHIR in Java.
In 2016, a variety of applications were demonstrated at the FHIR Applications Roundtable in July 2016. The Sync for Science (S4S) profile builds on FHIR to help medical research studies ask for (and if approved by the patient, receive) patient-level electronic health record data.
Implications for Healthcare Informatics
Because FHIR is implemented on top of HL7 and the HTTPS (HTTP Secure) protocol, messages can be parsed by wire data analytics platforms for real-time data gathering. In this concept, healthcare organizations would be able to gather real-time data from specified segments in FHIR messages as those messages pass over the network. That data can be streamed to a data store where it can be correlated with other informatics data. Potential use cases include epidemic tracking, prescription drug fraud, adverse drug interaction warnings, and emergency room wait times.