Cora Drenkhahn

Background: To ensure interoperability, both structural and semantic standards must be followed. For exchanging medical data between information systems, the structural standard FHIR (Fast Healthcare Interoperability Resources) has recently gained popularity. Regarding semantic interoperability, the reference terminology SNOMED Clinical Terms (SNOMED CT), as a semantic standard, allows for postcoordination, offering advantages over many other vocabularies. These postcoordinated expressions (PCEs) make SNOMED CT an expressive and flexible interlingua, allowing for precise coding of medical facts. However, this comes at the cost of increased complexity, as well as challenges in storage and processing. Additionally, the boundary between semantic (terminology) and structural (information model) standards becomes blurred, leading to what is known as the TermInfo problem. Although often viewed critically, the TermInfo overlap can also be explored for its potential benefits, such as enabling flexible transformation of parts of PCEs. Objective: In this paper, an alternative solution for storing PCEs is presented, which involves combining them with the FHIR data model. Ultimately, all components of a PCE should be expressible solely through precoordinated concepts that are linked to the appropriate elements of the information model. Methods: The approach involves storing PCEs decomposed into their components in alignment with FHIR resources. By utilizing the Web Ontology Language (OWL) to generate an OWL ClassExpression, and combining it with an external reasoner and semantic similarity measures, a precoordinated SNOMED CT concept that most accurately describes the PCE is identified as a Superconcept. In addition, the nonmatching attribute relationships between the Superconcept and the PCE are identified as the “Delta.” Once SNOMED CT attributes are manually mapped to FHIR elements, FHIRPath expressions can be defined for both the Superconcept and the Delta, allowing the identified precoordinated codes to be stored within FHIR resources. Results: A web application called PCEtoFHIR was developed to implement this approach. In a validation process with 600 randomly selected precoordinated concepts, the formal correctness of the generated OWL ClassExpressions was verified. Additionally, 33 PCEs were used for two separate validation tests. Based on these validations, it was demonstrated that a previously proposed semantic similarity calculation is suitable for determining the Superconcept. Additionally, the 33 PCEs were used to confirm the correct functioning of the entire approach. Furthermore, the FHIR StructureMaps were reviewed and deemed meaningful by FHIR experts. Conclusions: PCEtoFHIR offers services to decompose PCEs for storage within FHIR resources. When creating structure mappings for specific subdomains of SNOMED CT concepts (eg, allergies) to desired FHIR profiles, the use of SNOMED CT Expression Templates has proven highly effective. Domain experts can create templates with appropriate mappings, which can then be easily reused in a constrained manner by end users.

BACKGROUND To guarantee interoperability, structural and semantic standards must be adhered to. For exchanging medical data between information systems, the structural standard FHIR (Fast Healthcare Interoperability Resource) is recently gaining traction. In terms of semantic interoperability, the reference terminology SNOMED CT as a semantic standard enables a post-coordination in comparison to many other vocabularies. These post-coordinated expressions (PCEs) result in SNOMED CT being an expressive and flexible interlingua, which enables precise coding of medical facts, but at the expense of increased complexity and challenges with storage and processing. In addition, the boundary between the scope of semantic (terminology) and structural (information model) standards blurs, the so-called TermInfo problem. OBJECTIVE Although often discussed critically, the TermInfo overlap can also be explored for its beneficial potential by enabling a flexible transformation of parts of the PCEs. In this paper, an alternative solution for the storage of PCEs is presented, i. e., in combination with the FHIR data model. In the end, all components of a PCE should be expressible exclusively by pre-coordinated concepts that are linked to suitable elements of the information model. METHODS The approach is based on storing PCEs and/or parts of them conforming to FHIR resources. Using the Web Ontology Language for generating an OWL ClassExpression in combination with an external reasoner and semantic similarity measures, a pre-coordinated SNOMED CT concept that describes the PCE most precisely is determined as a superconcept. In addition, the non-matching attribute relationships between the superconcept and the PCE are determined as the so-called delta. Once SNOMED CT attributes have been mapped to FHIR elements manually, FHIRPath expressions can be determined for the superconcept and the delta, which in turn enable the identified pre-coordinated codes to be stored in FHIR resources. RESULTS A web application called PCEtoFHIR was developed to implement this approach. In a validation with 600 randomly selected pre-coordinated concepts, the correctness of the generated OWL ClassExpression could be confirmed. Additionally, two different approaches for calculating semantic similarities were validated, with the approach by Sanches et al. demonstrably yielding more precise results. In a validation of the entire approach, considering 33 already existing PCEs, the correct functionality could also be demonstrated. CONCLUSIONS PCEtoFHIR provides services to decompose PCEs for storing them in FHIR resources. When creating structure mappings concerning certain subdomains of SNOMED CT concepts (e.g. allergies) to desired FHIR profiles, the use of SNOMED CT Expression Templates has proven to be very useful. Domain experts can prepare templates with suitable mappings that can be reused in a constrained way by end users more easily.

Interoperability in healthcare cannot be achieved without mapping local data to standardized terminology. In this paper, we investigate the performance of different approaches for implementing HL7 FHIR Terminology Module operations using a benchmarking methodology, to gather evidence on the benefits and pitfalls of these methods in terms of performance from the point-of-view of a terminology client. The approaches perform very differently, while having a local client-side cache for all operations is of supreme importance. The results of our investigation show that careful consideration of the integration environment, potential bottlenecks, and implementation strategies is required.

Expressive clinical terminologies are of utmost importance for achieving a semantically interoperable data exchange and reuse in healthcare. SNOMED CT, widely respected as the most comprehensive terminology in medicine, provides formal concept definitions based on description logic which not only allows for advanced querying of SNOMED-CT-coded data but also for flexibly augmenting its 350,000 concepts by allowing a controlled combination of these. This ability for postcoordination largely increases the expressivity of the terminology but correlates with an intrinsic complexity. Complicated by the current lack of tooling support, postcoordination is widely either ignored or applied in an error-prone way. To help facilitate the adoption of postcoordination, we implemented a web application that guides users through the creation of postcoordinated expressions (PCEs) while ensuring adherence to syntactic and semantic constraints. Our approach was largely facilitated by making use of the extensive SNOMED CT specifications as well as advanced HL7 FHIR Terminology Services. Qualitative evaluations confirmed the usability of the developed application and the correctness of the PCEs created with it.

Expressive clinical terminologies are of utmost importance for achieving an semantically interoperable data exchange and reuse in healthcare. SNOMED CT, widely respected as the most comprehensive terminology in medicine, provides formal concept definitions based on description logic which not only allows for advanced querying of SNOMED CT-coded data but also for flexibly augmenting its 350,000 concepts. This ability for postcoordination largely increases the expressivity of the terminology but correlates with an intrinsic complexity. Complicated by the current lack of tooling support, postcoordination is widely either ignored or applied in an error-prone way. To help facilitate the adoption of postcoordination, we implemented a web application that guides through the creation of Postcoordinated expressions (PCEs) while ensuring the adherence to syntactic and semantic constraints. Our approach was largely facilitated by making use of the extensive SNOMED CT specifications as well as advanced HL7 FHIR Terminology Services. Qualitative evaluations confirmed the usability of the developed application and the correctness of PCEs created with it.