Methods Inf Med 2019; 58(04/05): 151-159
DOI: 10.1055/s-0040-1702154
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Evaluating Manual Mappings of Russian Proprietary Formats and Terminologies to FHIR

Iuliia D. Lenivtceva
1   National Center for Cognitive Technologies, ITMO University, Saint Petersburg, Russia
,
Georgy Kopanitsa
1   National Center for Cognitive Technologies, ITMO University, Saint Petersburg, Russia
› Author Affiliations
Funding This work financially supported by the government of the Russian Federation through the ITMO fellowship and professorship program. This work was supported by a Russian Fund for Basic research 18-37-20002.
Further Information

Publication History

17 August 2019

18 December 2019

Publication Date:
13 March 2020 (online)

Abstract

Background Evaluating potential data losses from mapping proprietary medical data formats to standards is essential for decision making. The article implements a method to evaluate the preliminary content overlap of proprietary medical formats, including national terminologies and Fast Healthcare Interoperability Resources (FHIR)—international medical standard.

Methods Three types of mappings were evaluated in the article: proprietary format matched to FHIR, national terminologies matched to the FHIR mappings, and concepts from national terminologies matched to Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT). We matched attributes of the formats with FHIR definitions and calculated content overlap.

Results The article reports the results of a manual mapping between a proprietary medical format and the FHIR standard. The following results were obtained: 81% of content overlap for the proprietary format to FHIR mapping, 88% of content overlap for the national terminologies to FHIR mapping, and 98.6% of concepts matching can be reached from national terminologies to SNOMED CT mapping. Twenty tables from the proprietary format and 20 dictionaries were matched with FHIR resources; nine dictionaries were matched with SNOMED CT concepts.

Conclusion Mapping medical formats is a challenge. The obtained overlaps are promising in comparison with the investigated results. The study showed that standardization of data exchange between proprietary formats and FHIR is possible in Russia, and national terminologies can be used in FHIR-based information systems.

Supplementary Material

 
  • References

  • 1 Jardim SVB. The electronic health record and its contribution to healthcare information systems interoperability. Procedia Technol 2013; 9: 940-948
  • 2 Kreuzthaler M, Martínez-Costa C, Kaiser P, Schulz S. Semantic technologies for re-use of clinical routine data. In: Studies in Health Technology and Informatics. 2017. . IOS Press
  • 3 Clarke JM, Warren LR, Arora S, Barahona M, Darzi AW. Guiding interoperable electronic health records through patient-sharing networks. 2018 ;1:65. Available at: www.nature.com/npjdigitalmed . Accessed June 1, 2019
  • 4 Hosseini M, Dixon BE. Syntactic Interoperability and the Role of Standards. In: Health Information Exchange. Elsevier; 2016: 123-136 . Available at: https://linkinghub.elsevier.com/retrieve/pii/B9780128031353000086 . Accessed January 7, 2019
  • 5 Benson T. Why Interoperability is Hard. In: Principles of Health Interoperability HL7 and SNOMED. 2012: 21-32 . Available at: http://link.springer.com/10.1007/978-3-319-30370-3_2 . Accessed February 9, 2019
  • 6 Robkin M, Weininger S, Preciado B, Goldman J. Levels of conceptual interoperability model for healthcare framework for safe medical device interoperability. In: 2015 IEEE Symposium on Product Compliance Engineering (ISPCE). IEEE; 2015: 1-8 . Available at: http://ieeexplore.ieee.org/document/7138703/ . Accessed June 2, 2019
  • 7 Santos MR, Bax MP, Kalra D. Building a logical EHR architecture based on ISO 13606 standard and semantic web technologies. In: Studies in Health Technology and Informatics. Vol. 160 (Part 1). IOS Press; 2010: 161-165
  • 8 Kopanitsa G. Evaluation Study for an ISO 13606 Archetype Based Medical Data Visualization Method. J Med Syst 2015; 39 (08) 82
  • 9 Kashfi H. An openEHR-based clinical Decision Support System: a case study. In: Studies in Health Technology and Informatics. Vol. 150. IOS Press; 2009: 348
  • 10 Atalag K, Yang HY, Tempero E, Warren J. Model Driven Development of Clinical Information Systems using openEHR. In: Studies in Health Technology and Informatics. Vol. 169. IOS Press; 2011: 849-853
  • 11 Kuo JWY, Kuo AMH. Integration of health information systems using HL7: a case study. In: Studies in Health Technology and Informatics. Vol. 234. IOS Press; 2017: 188-194
  • 12 Rodrigues JJPC, Sendra Compte S, de la Torra Diez I, Rodrigues JJPC, Sendra Compte S, de la Torra Diez I. Electronic medical records and their standards. e-Health Syst 2016; 3-19 . Available at: https://www.sciencedirect.com/science/article/pii/B9781785480911500014 . Accessed February 9, 2019
  • 13 Ulrich H, Kock AK, Duhm-Harbeck P, Habermann JK, Ingenerf J. Metadata repository for improved data sharing and reuse based on HL7 FHIR. In: Studies in Health Technology and Informatics. Vol. 228. IOS Press; 2017: 162-166
  • 14 Mandel JC, Kreda DA, Mandl KD, Kohane IS, Ramoni RB. SMART on FHIR: a standards-based, interoperable apps platform for electronic health records. J Am Med Informat Assoc 2016; 23 (05) 899-908
  • 15 Kim H, El-Kareh R, Goel A, Vineet FNU, Chapman WW. An approach to improve LOINC mapping through augmentation of local test names. J Biomed Inform 2012; 45 (04) 651-657
  • 16 Lee D, Cornet R, Lau F, de Keizer N. A survey of SNOMED CT implementations. J Biomed Inform 2013; 46 (01) 87-96
  • 17 Queenan K, Mangesho P, Ole-Neselle M. , et al. Using local language syndromic terminology in participatory epidemiology: lessons for one health practitioners among the Maasai of Ngorongoro, Tanzania. Prev Vet Med 2017; 139: 42-49
  • 18 Goossen WTF, Goossen-Baremans A. Bridging the HL7 template - 13606 archetype gap with detailed clinical models. In: Studies in Health Technology and Informatics. Vol. 160 (Part I). IOS Press; 2010: 932-936
  • 19 Hammond WE, Jaffe C, Cimino JJ, Huff SM. Standards in biomedical informatics. In: Biomedical Informatics. London: Springer London; 2014: 211-253
  • 20 Ascoli GA, Maraver P, Nanda S, Polavaram S, Armañanzas R. Win–win data sharing in neuroscience. Nat Methods 2017; 14 (02) 112-116
  • 21 Spackman KA, Campbell KE, Côté RA. SNOMED RT: a reference terminology for health care. Proc AMIA Annu Fall Symp 1997; 640-644
  • 22 Park H-A, Kim H-Y, Min YH. Use of clinical terminology for semantic interoperability of electronic health records. J Korean Med Assoc 2012; 55 (08) 720
  • 23 Review: IT in HealthCare; 2017. Informatization complicates the work of clinicians - CNews [date unknown]. Available at: https://www.cnews.ru/reviews/it_v_zdravoohranenii_2017/articles/informatizatsiya_poka_uslozhnyaet_rabotu_vracha . Accessed November 12, 2019
  • 24 Andersen MV, Kristensen IH, Larsen MM, Pedersen CH, Gøeg KR, Pape-Haugaard LB. Feasibility of representing a Danish microbiology model using FHIR. Stud Health Technol Inform 2017; 235: 13-17
  • 25 Leroux H, Metke-Jimenez A, Lawley MJ. Towards achieving semantic interoperability of clinical study data with FHIR. J Biomed Semantics 2017; 8 (01) 41
  • 26 Doods J, Neuhaus P, Dugas M. Converting ODM metadata to FHIR questionnaire resources. In: Studies in Health Technology and Informatics. Vol. 228. IOS Press; 2017: 456-460
  • 27 Jiang G, Kiefer R, Prud'hommeaux E, Solbrig HR. Building interoperable FHIR-based vocabulary mapping services: a case study of OHDSI vocabularies and mappings. Stud Health Technol Inform 2017; 245: 1327
  • 28 Review: IT in Healthcare; 2017. Rates - CNews [date unknown]. Available at: http://www.cnews.ru/reviews/it_v_zdravoohranenii_2017/review_table/670336b6dff880184644199b18cac01ca570ef90 . Accessed May 25, 2019
  • 29 fhir.resources PyPI [date unknown]. Available at: https://pypi.org/project/fhir.resources/ . Accessed November 14, 2019
  • 30 Forge - FHIR. [date unknown]. Available at: https://fire.ly/products/forge/ . Accessed June 24, 2019
  • 31 Реестр справочников - НСИ - Министерство здравоохранения Российской Федерации [date unknown]. Available at: https://nsi.rosminzdrav.ru/#!/refbook . Accessed August 28, 2019
  • 32 Brown SH, Bauer BA, Wahner-Roedler DL, Elkin PL. Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT. AMIA Annu Symp Proc 2003; 2003: 115-119
  • 33 Rosenbloom ST, Miller RA, Johnson KB, Elkin PL, Brown SH. A model for evaluating interface terminologies. J Am Med Inform Assoc 2008; 15 (01) 65
  • 34 Hong N, Wen A, Mojarad MR, Sohn S, Liu H, Jiang G. Standardizing heterogeneous annotation corpora using HL7 FHIR for facilitating their reuse and integration in clinical NLP. AMIA Annu Symp Proc 2018; 2018: 574-583
  • 35 Kieft R, Vreeke E, de Groot E. , et al. Mapping the Dutch SNOMED CT subset to Omaha System, NANDA International and International Classification of Functioning, Disability and Health. International Journal of Medical Informatics 2018; 111: 77-82