Solving Common FHIR Implementation Challenges
The global digital health market is projected to grow from $332.53 billion in 2022 to over $900 billion in 2032, with FHIR implementation playing a crucial role in this expansion. As healthcare providers, we recognize that transitions from acute to post-acute or long-term care can be particularly vulnerable points in a patient’s journey. Without standardized data exchange, each care setting operates in isolation, creating significant barriers to continuity of care.
Though FHIR adoption has become a leading solution for facilitating healthcare interoperability in many countries, it comes with notable challenges. These include mapping legacy data structures, ensuring system compatibility, and maintaining data security. Additionally, when care teams lack interoperability, they often work without the full clinical picture, potentially compromising patient outcomes. In this article, we’ll explore common FHIR technology challenges and provide expert consulting tips to help you navigate these obstacles successfully.
Understanding the Core Challenges in FHIR Adoption
Despite growing interest in FHIR technology, healthcare organizations face significant implementation hurdles that slow adoption rates. Internal teams often struggle with FHIR’s resource-based model, which introduces complex webs of interdependencies requiring sophisticated management compared to simpler legacy standards.
Lack of standardized implementation across systems
Inconsistent FHIR implementation across healthcare systems presents a major challenge. While FHIR provides a framework for data exchange, it allows flexibility in how certain data elements are represented. Consequently, this leads to variations between organizations, creating compatibility issues that diminish interoperability benefits. Furthermore, different EHR vendors support FHIR resources inconsistently—some expose only subsets of resources or implement non-standard extensions.
This fragmentation extends beyond individual organizations. Even within the same country, contradictory responses about FHIR implementation suggest inconsistent communication between national bodies. Such disjointed version usage complicates interoperability not just across borders but even between institutions within the same country.
Complexity of mapping legacy data to FHIR resources
Healthcare organizations often operate multiple disconnected legacy systems that store data in non-standard formats, making FHIR resource mapping particularly challenging. Legacy data frequently contains inconsistencies, missing elements, and mixed terminologies that require comprehensive normalization before conversion.
The semantic interoperability challenge is especially notable. Different coding systems and clinical terminologies across healthcare providers mean that ensuring consistent meaning of data during transformation is difficult. These semantic inconsistencies can lead to errors in clinical decision support, reporting, and research. Moreover, maintaining data quality during transformation is critical—compromised data integrity can affect patient safety, clinical decisions, and regulatory compliance.
Security and compliance concerns during data exchange
FHIR’s openness and API-first architecture raise significant security concerns. Primary threats include unauthorized access to patient health records, data interception during transmission, and integrity issues during exchange processes.
According to HL7 FHIR itself, “FHIR is not a security protocol,” meaning data isn’t automatically secured when integrated into healthcare systems. Instead, organizations must implement separate security measures, including:
Healthcare providers must also navigate complex regulatory environments, ensuring FHIR implementations comply with regional requirements like HIPAA, GDPR, and the 21st Century Cures Act[11].
Profiling and Terminology Pitfalls in FHIR Projects
Profiling and terminology management represent key technical challenges in FHIR implementation projects. These areas often create significant obstacles even for experienced teams attempting to build interoperable healthcare systems.
StructureDefinition and the role of FHIR profiles
Profiling in FHIR allows organizations to customize standard resources for specific use cases through StructureDefinition resources. However, excessive profiling creates what experts call “profiliferation”—a major interoperability barrier. Research examining nearly 3,000 profiles from 125 implementation guides found that just two items—Extension and Observation—account for almost half (49%) of all profiles. This concentration suggests significant redundancy and missed opportunities for standardization.
The profiling process itself presents several challenges. Organizations struggle with complex XML editing requirements, determining appropriate constraints, and obtaining new terminology codes—a process that takes approximately 125 days for LOINC codes. Furthermore, only one-fifth of all extensions used in implementation guides leverage standard extensions, indicating potential duplication of effort across the FHIR community.
CodeSystem vs ValueSet: Misuse and misalignment
Many developers misunderstand the fundamental relationship between these two critical terminology resources:
A common misconception is that ValueSets contain actual codes, whereas they essentially store only references to codes in CodeSystems. This distinction becomes critical during ValueSet expansion operations when systems need to retrieve current codes. Additionally, hierarchical CodeSystems require special handling with “is-a” filters to properly include parent-child relationships.
Terminology inconsistencies affecting clinical decisions
Terminology challenges directly impact patient care. Inconsistent use of coding systems across healthcare providers makes it difficult to ensure consistent meaning during data transformation. The lack of shared governance between terminology standards—except for laboratory and vital sign observations—creates duplicate concepts across systems like LOINC and SNOMED CT.
FHIR implementation teams frequently encounter copyright restrictions on proprietary content, hampering their ability to create needed value sets. Additionally, terminology systems often evolve independently, complicating version management. Essentially, terminology inconsistencies can lead to significant errors in clinical decision support, reporting, and research activities unless properly managed with FHIR’s terminology services.
Search Parameters and Operations: Common Misconfigurations
Search capabilities form a critical component of any FHIR implementation, yet they often suffer from technical misconfigurations that compromise system performance. These issues typically remain undetected until they cause significant operational problems.
Incorrect use of _include and _revinclude in queries
The _include and _revinclude parameters enable clients to retrieve related resources in a single request, significantly reducing network overhead. Initially, _include fetches resources referenced by search results (following links forward), while _revinclude retrieves resources that reference the search results (following reverse links). Nonetheless, many developers misapply these parameters, creating performance bottlenecks.
One common mistake involves using _revinclude without adequate filters, which can generate unbounded result sets and higher latencies. Hence, several FHIR server providers limit the number of resources returned in response to _revinclude parameters. Additionally, complex searches using chained parameters alongside include directives further degrade query performance.
Overuse of custom operations instead of standard RESTful ones
Operations in FHIR provide RPC-like functionality beyond basic CRUD actions, typically identified with a “$” prefix. They should primarily be used when servers need to play an active role in formulating responses or when actions cause side effects across multiple resources.
Subsequently, many teams unnecessarily implement custom operations when standard RESTful approaches would suffice. This creates non-standard interfaces that reduce interoperability and complicate client development. Proper operations have clearly defined contexts (system, resource type, or resource instance), parameters with specific types, and documented functionality.
Search parameter definitions missing in IGs
Implementation Guides (IGs) often fail to include comprehensive search parameter definitions, creating inconsistencies across systems. Each search parameter requires specific elements including a unique URL, a code for API calls, base resource types, target types, data types, and expression logic.
Otherwise, when multiple search parameters share the same code, FHIR servers must resolve these conflicts independently, leading to unpredictable behavior. For instance, US Core defines search parameters that differ from standard FHIR parameters with the same names. Therefore, servers and clients must clearly document supported parameters in their capability statements to maintain interoperability.
Expert Consulting Tips for Successful FHIR Implementation
Successful FHIR implementation hinges on selecting appropriate tools and methodologies. Indeed, mastering these resources can significantly reduce development time and improve interoperability outcomes.
Using IG Publisher and Simplifier.net effectively
The FHIR Implementation Guide (IG) Publisher converts materials into XML, JSON, and TTL formats through a four-step process: installation, resource definition, structure development, and publishing. Specifically, Simplifier.net complements this workflow by enabling versioned publications with “Published guides” functionality, making ballotable and final publications available without extra effort. This platform primarily serves as a centralized repository where developers can create, upload, and find FHIR Implementation Guides.
Choosing the right profiling tools: Forge, Kodjin, Trifolia-on-FHIR
Selecting suitable profiling tools markedly improves development efficiency:
Validating FHIR conformance with test servers
Validation represents a critical quality assurance step. Currently, most tools incorporate either the HL7 Java validator or the Firely .NET validator. Simplifier.net and Touchstone offers multiple validation options, including copy-paste validation against core specifications or published packages.
Leveraging US Core and other national base IGs
Finally, the US Core Implementation Guide provides essential requirements for profile adoption, including conformance rules, mandatory elements, and terminology guidance. Its constraints on FHIR resources and RESTful interactions facilitate consistent implementation across healthcare systems nationwide.
Conclusion
FHIR implementation presents healthcare organizations with significant technical hurdles despite its growing adoption. Throughout this article, we explored several core challenges that commonly arise during implementation efforts. Standardization inconsistencies across systems create compatibility issues that diminish interoperability benefits. Additionally, the complexity of mapping legacy data to FHIR resources continues to pose substantial difficulties for many healthcare providers.
Security and compliance concerns remain paramount when exchanging sensitive patient data. Therefore, organizations must implement robust security measures beyond basic FHIR capabilities. Profiling and terminology management represent equally challenging technical areas, with issues like “profiliferation” and misalignment between CodeSystems and ValueSets creating potential roadblocks.
Search parameter configurations also demand careful attention. Many teams incorrectly use parameters like _include and _revinclude or unnecessarily implement custom operations instead of standard RESTful approaches. These misconfigurations often go undetected until they cause significant operational problems.
The expert consulting tips we provided offer practical solutions to these challenges. Effective use of tools like IG Publisher, Simplifier.net, and specialized profiling applications can significantly reduce development time. Validation through test servers ensures conformance with FHIR specifications. National base implementation guides such as US Core provide essential frameworks that facilitate consistent implementation across healthcare systems.
Healthcare organizations that address these implementation challenges stand to benefit from enhanced interoperability, streamlined data exchange, and ultimately improved patient care. FHIR technology, when properly implemented, serves as a cornerstone for healthcare’s digital transformation. The path may contain obstacles, yet with proper understanding and appropriate tools, we can successfully navigate FHIR implementation challenges while advancing healthcare interoperability for better patient outcomes.