Globally, 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). Open source implementations of FHIR data structures, servers, clients and tools include reference implementations from HL7 in a variety of languages, SMART on FHIR, HAPI-FHIR in Java, and many others (see reference). 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. In January, 2018, Apple announced that its iPhone
Health App would allow viewing a user's FHIR-compliant medical records when providers choose to make them available. Johns Hopkins Medicine, Cedars-Sinai, Penn Medicine, NYU-Langone Medical Center, Dignity Health and other large hospital systems participated at launch.
United States In 2014, the U.S. Health IT Policy and the Health IT Standards committees endorsed recommendations for more public (open) APIs. The U.S.
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. In December 2014, a broad cross-section of US 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 was to specify two FHIR profiles that are relevant to the
Meaningful Use requirements, along with an implementation guide for using
OAuth 2.0 for authentication. A collaboration agreement with Healthcare Services Platform Consortium (now called Logica) was announced in 2017. Experiences with developing medical applications using FHIR to link to existing electronic health record systems clarified some of the benefits and challenges of the approach, and with getting clinicians to use them. In 2020, the U.S.
Centers for Medicare & Medicaid Services (CMS) issued their
Interoperability and Patient Access final rule, (CMS-9115-F), based on the
21st Century Cures Act. The rule requires the use of FHIR by a variety of CMS-regulated payers, including
Medicare Advantage organizations, state
Medicaid programs, and
qualified health plans in the
Federally Facilitated Marketplace by 2021. Specifically, the rule requires FHIR APIs for Patient Access, Provider Directory and Payer-to-Payer exchange. Proposed rules from CMS, such as the patient burden and
prior authorization proposed rule (CMS-9123-P), further specify FHIR adoption for payer-to-payer exchange. The CMS rules and Office of the National Coordinator for Health IT (ONC) Cures Act Final rule (HHS-ONC-0955-AA01) work in concert to drive FHIR adoption within their respective regulatory authorities. Further, other agencies are using existing rule-making authority, not derived from the Cures Act, to harmonize the regulatory landscape and ease FHIR adoption. For example, the
U.S. Department of Health and Human Services (HHS) Office of Civil Rights (OCR) has proposed to update the HIPAA privacy rule (HHS–OCR–0945–AA00) with an expanded right of access for personal health apps and disclosures between providers for care coordination. Unlike the CMS and ONC final rules, the OCR HIPAA privacy proposed rule is not specific to FHIR; however, OCR's emphasize on standards-based APIs clearly benefits FHIR adoption.
Brazil In 2020,
Brazil's
Ministry of Health, by the IT Department of the SUS, started one of the world's largest platforms for national health interoperability, called the National Health Data Network, which uses HL7 FHIR r4 as a standard in all its information exchanges.
Israel In 2020,
Israel's
Ministry of Health began working towards the goal of promoting accessibility of information to patients and caregivers through the adoption of the FHIR standard in health organizations in Israel. Its first act was to create the IL-CORE work team to adapt the necessary components for localization and regulation in the health system in Israel. The ministry, in cooperation with the
Nonprofit Organization 8400, created the FHIR IL community, whose purpose is to encourage the adoption of the standard in the Israeli healthcare system while cooperating with healthcare organizations and the industry. As part of a joint activity of the Ministry and 8400, a number of projects were launched for the implementation of FHIR in health management organizations (HMO) and hospitals, alongside other projects that are being independently promoted by healthcare organizations. In addition, the Ministry of Health allocated budgets to the HMOs and other organizations for the purpose of establishing organizational FHIR infrastructure. In the 2020 Eli Hurvitz Conference on Economy and Society, run by the
Israel Democracy Institute it was estimated that the cost of implementing central FHIR modules of in the Israeli healthcare system is estimated at about 400 million NIS over 5 years. In 2023, the Israeli government began a legislative process to promote the sharing of information between organizations in the Israeli health ecosystem for the benefit of the patient, with an emphasis on patient empowerment and reduced information blocking. The proposed legislation also refers to the need to standardize the data by adopting the FHIR standard and utilizing standard terminologies, such as
SNOMED-CT, both in source systems and in the data exchange process. The sharing of information will be with the patient's consent, and this consent will be given according to data buckets. ==References==