Для обеспечения непрерывной и качественной медицинской помощи важно осуществлять обмен и интеграцию медицинских данных различных провайдеров. Оценка потенциальных потерь данных в результате миграции из одной медицинской базы в другую имеет важное значение в процессе принятия решений. В данной работе описан метод предварительной оценки перекрытия пользовательских форматов с международными стандартами, а также локальных терминологических справочников с международными терминологическими системами.
Литература
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4. Leroux H, Metke-Jimenez A, Lawley MJ. Towards achieving semantic interoperability of clinical study data with FHIR. J. Biomed. Semantics. 2017; 8(1): 41.
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6. Peng P, et al. Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation. J. Am. Med. Informatics Assoc. 2019; 26(1): 19–27.
7. Baumel T, et al. Multi-Label Classification of Patient Notes a Case Study on ICD Code Assignment. AAAI Conference on Artificial Intelligence. 2017: 409–416.
8. Andersen. V, et al. Feasibility of Representing a Danish Microbiology Model Using FHIR. Stud. Health Technol. Inform. 2017.
9. Doods J, Neuhaus P, Dugas M. Converting ODM metadata to FHIR questionnaire resources. Studies in Health Technology and Informatics. IOS Press. 2017; 228: 456–460.
10. Jiang G, Kiefer R, Prud’hommeaux E H.R.S. Building Interoperable FHIR-Based Vocabulary Mapping Services: A Case Study of OHDSI Vocabularies and Mappings. Stud. Health Technol. Inform. 2017; 245: 1327–1327.
11. Review: IT in HealthCare 2017, Informatization complicates the work of clinitians — CNews.
12. Benson T. Why Interoperability is Hard. Principles of Health Interoperability HL7 and SNOMED. Third Edit. 2012: 21–32.
13. Hong N, et al. Standardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP. AMIA. Annu. Symp. proceedings. AMIA Symp. NLM (Medline). 2018; 2018: 574–583.
14. Buck J, et al. Towards a comprehensive electronic patient record to support an innovative individual care concept for premature infants using the openEHR approach. Int. J. Med. Inform. Elsevier. 2009; 78(8): 521–531.
15. Brown S.H, et al. Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT. // AMIA. Annu. Symp. proceedings. AMIA Symp. American Medical Informatics Association. 2003; 2003: 115–119.
2. Kopanitsa G. Evaluation Study for an ISO 13606 Archetype Based Medical Data Visualization Method. J. Med. Syst. 2015; 39(8): 82.
3. Rodrigues J.J.P.C, et al. Electronic Medical Records and Their Standards. e-Health Syst. Elsevier. 2016: 3–19.
4. Leroux H, Metke-Jimenez A, Lawley MJ. Towards achieving semantic interoperability of clinical study data with FHIR. J. Biomed. Semantics. 2017; 8(1): 41.
5. Kieft R.A.M.M, et al. Mapping the Dutch SNOMED CT subset to Omaha System, NANDA International and International Classification of Functioning, Disability and Health. Int. J. Med. Inform. Elsevier Ireland Ltd. 2018; 111: 77–82.
6. Peng P, et al. Mapping of HIE CT terms to LOINC®: analysis of content-dependent coverage and coverage improvement through new term creation. J. Am. Med. Informatics Assoc. 2019; 26(1): 19–27.
7. Baumel T, et al. Multi-Label Classification of Patient Notes a Case Study on ICD Code Assignment. AAAI Conference on Artificial Intelligence. 2017: 409–416.
8. Andersen. V, et al. Feasibility of Representing a Danish Microbiology Model Using FHIR. Stud. Health Technol. Inform. 2017.
9. Doods J, Neuhaus P, Dugas M. Converting ODM metadata to FHIR questionnaire resources. Studies in Health Technology and Informatics. IOS Press. 2017; 228: 456–460.
10. Jiang G, Kiefer R, Prud’hommeaux E H.R.S. Building Interoperable FHIR-Based Vocabulary Mapping Services: A Case Study of OHDSI Vocabularies and Mappings. Stud. Health Technol. Inform. 2017; 245: 1327–1327.
11. Review: IT in HealthCare 2017, Informatization complicates the work of clinitians — CNews.
12. Benson T. Why Interoperability is Hard. Principles of Health Interoperability HL7 and SNOMED. Third Edit. 2012: 21–32.
13. Hong N, et al. Standardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP. AMIA. Annu. Symp. proceedings. AMIA Symp. NLM (Medline). 2018; 2018: 574–583.
14. Buck J, et al. Towards a comprehensive electronic patient record to support an innovative individual care concept for premature infants using the openEHR approach. Int. J. Med. Inform. Elsevier. 2009; 78(8): 521–531.
15. Brown S.H, et al. Coverage of oncology drug indication concepts and compositional semantics by SNOMED-CT. // AMIA. Annu. Symp. proceedings. AMIA Symp. American Medical Informatics Association. 2003; 2003: 115–119.
Для цитирования
Ленивцева Ю.Д., Копаница Г.Д. Метод сопоставления форматов обмена медицинскими данными и терминологий. Врач и информационные технологии. 2021; 1: 75–83. doi: 10.25881/ITP.2021.79.85.007.
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