Implementing SNOMED CT in Open Software Solutions to Enhance the Findability of COVID-19 Questionnaires.

SNOMED CT fosters interoperability in healthcare and research. This use case implemented SNOMED CT for browsing COVID-19 questionnaires in the open-software solutions OPAL/MICA. We implemented a test server requiring files in a given YAML format for implementation of taxonomies with only two levels of hierarchy. Within this format, neither the implementation of SNOMED CT hierarchies and post-coordination nor the use of release files were possible. To solve this, Python scripts were written to integrate the required SNOMED CT concepts (Fully Specified Name, FSN and SNOMED CT Identifier, SCTID) into the YAML format (YAML Mode). Mappings of SNOMED CT to data items of the questionnaires had to be provided as Excel files for implementation into Opal/MICA and further Python scripts were established within the Excel Mode. Finally, a total of eight questionnaires containing 1.178 data items were successfully mapped to SNOMED CT and implemented in OPAL/MICA. This use case showed that implementing SNOMED CT for browsing COVID-19 questionnaires is feasible despite software solutions not supporting SNOMED CT. However, limitations of not being able to implement SNOMED CT release files and its provided hierarchy and post-coordination still have to be overcome.

Fast Healthcare Interoperability Resources (FHIR) in a FAIR Metadata Registry for COVID-19 Research.

Adopting international standards within health research communities can elevate data FAIRness and widen analysis possibilities. The purpose of this study was to evaluate the mapping feasibility against HL7® Fast Healthcare Interoperability Resources® (FHIR)® of a generic metadata schema (MDS) created for a central search hub gathering COVID-19 health research (studies, questionnaires, documents = MDS resource types). Mapping results were rated by calculating the percentage of FHIR coverage. Among 86 items to map, total mapping coverage was 94%: 50 (58%) of the items were available as standard resources in FHIR and 31 (36%) could be mapped using extensions. Five items (6%) could not be mapped to FHIR. Analyzing each MDS resource type, there was a total mapping coverage of 93% for studies and 95% for questionnaires and documents, with 61% of the MDS items available as standard resources in FHIR for studies, 57% for questionnaires and 52% for documents. Extensions in studies, questionnaires and documents were used in 32%, 38% and 43% of items, respectively. This work shows that FHIR can be used as a standardized format in registries for clinical, epidemiological and public health research. However, further adjustments to the initial MDS are recommended - and two additional items even needed when implementing FHIR. Developing a MDS based on the FHIR standard could be a future approach to reduce data ambiguity and foster interoperability.

Evaluating Suitability of SNOMED CT in Structured Searches for COVID-19 Studies.

Studies investigating the suitability of SNOMED CT in COVID-19 datasets are still scarce. The purpose of this study was to evaluate the suitability of SNOMED CT for structured searches of COVID-19 studies, using the German Corona Consensus Dataset (GECCO) as example. Suitability of the international standard SNOMED CT was measured with the scoring system ISO/TS 21564, and intercoder reliability of two independent mapping specialists was evaluated. The resulting analysis showed that the majority of data items had either a complete or partial equivalent in SNOMED CT (complete equivalent: 141 items; partial equivalent: 63 items; no equivalent: 1 item). Intercoder reliability was moderate, possibly due to non-establishment of mapping rules and high percentage (74%) of different but similar concepts among the 86 non-equal chosen concepts. The study shows that SNOMED CT can be utilized for COVID-19 cohort browsing. However, further studies investigating mapping rules and further international terminologies are necessary.