FHIR standards

As patient healthcare records become increasingly digitized, care providers need a simple way to discover, access and understand the records. They also need the data to be well structured and standardized to make it readable and actionable. FHIR Resources represent common healthcare-related concepts such as those used in electronic health records. FHIR Resources are categorized based on their purpose, such as Individuals, Diagnostics, and Billing. Ecosystem testing platforms address version heterogeneity through multi-version validation environments that eliminate the need for organizations to maintain separate testing infrastructure for each FHIR version. Your implementation is validated against partners operating on different versions simultaneously, producing empirical compatibility data rather than theoretical conformance assessments based on specification reading.

SQ6: What are the Challenges and Open Questions Related to FHIR?

FHIR standards

In this case, the QI-Core Observation profile is used, which in turn relies on the US Core Blood Pressure profile. That US Core profile requires fixed LOINC codes and specific component codes for systolic and http://www.medidfraud.org/membership/ diastolic values. These constraints ensure that dQMs represent blood pressure consistently.

FHIR standards

Driving Change in 2026: Use Case Progress and Preparing for HL7 FHIR Adoption

Forward compatibility means that content that is conformant in an old release will remain conformant with future versions. However, that doesn’t guarantee that all old systems will interoperate with future systems. Note that this same status will arise as a matter of process when new elements are introduced intonormative resources in future versions – they will undergo a period of trial use as appropriate. I hope that with these 5 key concepts—FHIR resources, data elements, profiles, exchange paradigms, and IGs—you are now armed with enough knowledge to confidently say you know what FHIR is and how it’s used. The FHIR IG Registry serves as a central repository for published Implementation Guides, making it easier for implementers to find relevant guides for their needs.

Interoperability

If we treat FHIR as a checkbox, we may miss the work required to make data usable. If we treat it as one layer in a broader data journey, we can design more realistic systems. We can ask what condition the data is in at the source, what transformation is required, what standard is expected, what validation is needed, and what job the data must perform in the receiving workflow. A clinician may need to see whether a patient’s results are trending in the wrong direction. An insurer may need to assess information as part of a claims or underwriting workflow. A remote monitoring platform may need to decide when a reading requires escalation.

  • In addition, FHIR is the latest standard, which is in an infancy stage of development.
  • When implemented correctly, CDS Hooks with FHIR enables scalable, interoperable, and workflow-integrated clinical decision support that enhances both efficiency and patient outcomes.
  • It is to understand real-world version heterogeneity scenarios, which informs which versions to support actively, how to handle mismatches, and where to invest compatibility effort.
  • Thus, we came up with eight categories based on how the applications make use of the FHIR standard (Table 9).
  • The JSON and XML formats are similar in terms of object members, objects and arrays, and properties.
  • We reviewed every section of the article from beginning to end and recorded details of the articles in these two forms whenever we found the answer to a corresponding research question.

FHIR standards

FHIR Resources represent defined healthcare information – clinical, administrative and operational workflows which are the foundation for the data model used in quality measurement. FHIR includes a set of modules that group related resources, including the Clinical Reasoning Module, which supports the representation, sharing, and evaluation of clinical knowledge artifacts. The Clinical Reasoning Module covers resources for decision support rules, quality measures, order sets, clinical protocols, evidence summaries, and other computable clinical logic. It enables both real-time clinical decision support during care delivery and retrospective quality measurement using the same underlying artifacts and data structures, reducing duplication and improving consistency compared to earlier standards. Interoperability, while not a medical term, is currently tightly intertwined with the healthcare industry.