Towards the Representation of Genomic Data in HL7 FHIR and OMOP CDM

Abstract

High throughput sequencing technologies have facilitated an outburst in biological knowledge over the past decades and thus enables improvements in personalized medicine. In order to support (international) medical research with the combination of genomic and clinical patient data, a standardization and harmonization of these data sources is highly desirable. To support this increasing importance of genomic data, we have created semantic mapping from raw genomic data to both FHIR (Fast Healthcare Interoperability Resources) and OMOP (Observational Medical Outcomes Partnership) CDM (Common Data Model) and analyzed the data coverage of both models. For this, we calculated the mapping score for different data categories and the relative data coverage in both FHIR and OMOP CDM. Our results show, that the patients genomic data can be mapped to OMOP CDM directly from VCF (Variant Call Format) file with a coverage of slightly over 50%. However, using FHIR as intermediate representation does not lead to further information loss as the already stored data in FHIR can be further transformed into OMOP CDM format with almost 100% success. Our findings are in favor of extending OMOP CDM with patient genomic data using ETL to enable the researchers to apply different analysis methods including machine learning algorithms on genomic data.

Fast Healthcare Interoperability Resources (FHIR) for Interoperability in Health Research: Systematic Review

“…Further medical specialties were environmental health (2%, 1/49) [ 64 ], genomic cancer medicine (2%, 1/49) [ 51 ], neuroimaging research (2%, 1/49) [ 12 ], and pulmonary hypertension (2%, 1/49) [ 35 ]. Despite studies implementing FHIR in specific use cases, 55% (12/22) of the studies [ 1 , 12 , 22 , 23 , 25 , 35 , 43 , 50 , 52 , 58 , 64 , 69 ] reported generic solutions conferrable to other use cases. Details on study objectives with regards to FHIR use can be found in Table 2 and Multimedia Appendix 3 .…”

“…Among the 49 studies, 37% (n=18) did not report on or use additional standards or terminologies [ 12 , 22 - 24 , 27 , 28 , 30 - 32 , 38 , 39 , 48 , 50 , 55 , 57 , 64 , 66 , 69 ]. SNOMED CT [ 1 , 25 , 26 , 35 , 37 , 43 , 45 - 47 , 51 , 55 , 56 , 65 , 70 ] and LOINC [ 25 , 26 , 35 , 37 , 42 - 45 , 47 , 49 , 51 , 55 , 56 , 58 , 61 , 65 , 68 , 70 ] were reported to be used by 29% (n=14) and 37% (n=18) of the studies, respectively; 18% (n=9) of the studies used International Classification of Diseases 10th Revision [ 25 , 26 , 35 , 37 , 49 , 51 , 58 , 65 , 68 ] and 12% (n=6) used OMOP CDM [ 26 , 29 , 35 , 47 , 52 , 60 ]; and 43% (n=21) of the studies used additional standards which were categorized under “Other” ( Table 1 ) [ 26 , 34 - …”

“…Of the 49 studies, the majority were conducted in Germany (47%, n=23) [12,26,[28][29][30][31]34,35,[40][41][42][45][46][47]52,53,[56][57][58]60,62,63,69], the United States (27%, n=13) [22,25,36,44,[48][49][50]61,[64][65][66]68,70], and Australia (6%, n=3) [1,43,67]. The remaining studies were performed in Austria (2%, n=1) [32], Canada (2%, n=1) [24], France (2%, n=1) [51], Greece (2%, n=1) [59], Japan (2%, n=1) [27], Pakistan (2%, n=1) [38], Spain (2%, n=1) [55], Switzerland (2%, n=1) [39], Taiwan (2%, n=1) [23], and the United Kingdom (2%, n=1)…”

“…In terms of medical specialty, most (55%, 27/49) of the studies [24,[27][28][29][30][31][32]34,[36][37][38][39][40][41][42]44,46,48,49,53,56,[60][61][62][63]67,70] were using a generic approach-implementable in any kind of specialty (Table 2). Of the remaining studies, 16% (8/49) use cases focused on infectious disease [1,22,23,26,45,47,50,59], whereas 12% (6/49) focused on oncology [25,55,57,58,65,66] and 8% (4/49) on genomics [43,52,68,69]. Further medical specialties were environmental health (2%, 1/49) [64], genomic cancer medicine (2%, 1/49) [51], neur...…”

“…Among the 49 studies, 37% (n=18) did not report on or use additional standards or terminologies [12,22-24,27,28,30-32, 38,39,48,50,55,57,64,66,69]. SNOMED CT [1,25,26,35,37,43,[45][46][47]51,55,56,65,70] and LOINC [25,26,35,37,42-45, 47,49,51,55,56,58,61,65,68,70] were reported to be used by 29% (n=14) and 37% (n=18) of the studies, respectively; 18% (n=9) of the studies used International Classification of Diseases 10th Revision [25,26,35,37,49,51,58,65,68] and 12% (n=6) used OMOP CDM [26,29,35,47,52,60]; and 43% (n=21) of the studies used additional standards which were categorized under "Other" (Table 1) [26,34-37,40,42,43,45-47,49,51,56,58-60, 62,63,67,70]. The implemented FHIR resources by each study are listed in Table 2; 5 (10%) studies did not precisely list their FHIR resources used [36,38,56,64,69].…”