Interoperability of population-based patient registries

R.E. Gliklich, N.A. Dreyer, M.B. Leavy, (Eds.), Registries for Evaluating Patient Outcomes: A User's Guide [Internet]. 3rd edition. Rockville (MD), Agency for Healthcare Research and Quality (US), Apr. 2014, Chapter 1: Patient Registries. Available from: https://www.ncbi.nlm.nih.gov/books/NBK208625/ (accessed 21 April 2020). Drolet, 2008, Categorizing the world of registries, J. Biomed. Inform., 41, 1009, 10.1016/j.jbi.2008.01.009 M. Zaletel, M. Kralj, Methodological guidelines and recommendations for efficient and rational governance of patient registries, PARENT joint action (cross-border Patient Registries iNiTiative), 2015. https://ec.europa.eu/health/sites/health/files/ehealth/docs/patient_registries_guidelines_en.pdf (accessed 21 April 2020). Olsen, 1999, What is a population-based registry?, Scand. J. Public Health, 27, 78, 10.1177/14034948990270010601 U.S. National Institutes of Health, National Cancer Institute, SEER Training Modules, Types of Registries. https://training.seer.cancer.gov/registration/ (accessed 21 April 2020). T. Albreht, M. McKee, D.M.Alexe, M. Coleman, J. Martin-Moreno, Making progress against cancer, in: M. Coleman, D.M. Alexe, T. Albreht, M. McKee (Eds.), Responding to the challenge of cancer in Europe. Institute of Public Health of the Republic of Slovenia, Ljubljana, 2008. Chapter 16, pp. 315–327. Available from: https://apps.who.int/iris/handle/10665/107879 (accessed 21 April 2020). Sørensen, 1996, A framework for evaluation of secondary data sources for epidemiological research, Int. J. Epidemiol., 25, 435, 10.1093/ije/25.2.435 Walters, 2013, Comparability of stage data in cancer registries in six countries: Lessons from the International Cancer Benchmarking Partnership, Int. J. Cancer, 132, 676, 10.1002/ijc.27651 Teppo, 1994, Data quality and quality control of a population-based cancer registry. Experience in Finland, Acta Oncol., 33, 365, 10.3109/02841869409098430 P. Aspden, J.M. Corrigan, J. Wolcott, et al. (Eds.), Ch.4 Health Care Data Standards, in Patient Safety: Achieving a New Standard for Care, National Academies Press (US), Washington (DC), 2004, pp. 127–168. Integrating the Healthcare Enterprise (IHE), IHE Profiles. https://www.ihe.net/resources/profiles/ (accessed 15 April 2020). HL7 International, C-CDA (HL7 CDA R2 Implementation Guide: Consolidated CDA Templates for Clinical Notes - US Realm). http://www.hl7.org/implement/standards/product_brief.cfm?product_id=492 (accessed 21 April 2020). Health Level Seven (HL7), The Relationship between FHIR and other HL7 Standards. https://www.hl7.org/fhir/comparison.html (accessed 21 April 2020). Health Level Seven (HL7), Introducing HL7 FHIR Release 4. https://www.hl7.org/fhir/summary.html (accessed 21 April 2020). Integrating the Healthcare Enterprise (IHE), IHE Cross-Enterprise Document Sharing. https://wiki.ihe.net/index.php/Cross-Enterprise_Document_Sharing (accessed 21 April 2020). World Health Organization (WHO), Classification of diseases ICD. https://www.who.int/classifications/icd/en/ (accessed 21 April 2020). Awaysheh, 2018, A review of medical terminology standards and structured reporting, J. Vet. Diagn. Invest., 30, 17, 10.1177/1040638717738276 National Institutes of Health (NIH), National Library of Medicine, Unified Medical Language System (UMLS). https://www.nlm.nih.gov/research/umls/index.html (accessed 21 April 2020). Observational Health Data Sciences and Informatics (OHDSI) forum, International Classification of Diseases for Oncology (ICD-O). https://forums.ohdsi.org/t/international-classification-of-diseases-for-oncology-icd-o/1851 (accessed 23 April 2020). Valentic, 2017, Addressing the data linking challenges: interviewing for best practices in patient registry interoperability, Methods Inf. Med., 56, 407, 10.3414/ME16-02-0029 European Cystic Fibrosis Society (ECFS), Common data elements metadata, cystic fibrosis. https://www.ecfs.eu/projects/ecfs-patient-registry/Variables-Definitions, 2019 (accessed 13 April 2020). European Cardiovascular Indicators Surveillance Set (EUROCISS), Common data elements metadata, cardiovascular. http://www.cuore.iss.it/eurociss/en/indicators-eu/indicators_europe.asp, 2019 (accessed 13 April 2020). European Commission, Common data elements metadata, congenital anomalies. https://eu-rd-platform.jrc.ec.europa.eu/sites/default/files/2.2.1b_28_Dec2018.pdf, 2019 (accessed 9 September 2019). European best information through regional outcomes in diabetes (EUROBIROD), BIRO data elements. http://www.eubirod.eu/eubirod_DataStandards.htm (accessed 21 April 2020). European Commission, Common data elements metadata, rare diseases. https://eu-rd-platform.jrc.ec.europa.eu/set-of-common-data-elements, 2019 (accessed 9 September 2019). C. Martos, E. Crocetti, O. Visser, B. Rous, F. Giusti, et al, A proposal on cancer data quality checks: one common procedure for European cancer registries (version 1.1), JRC Technical Report. Publications Office of the European Union, 2018. https://doi.org/10.2760/429053. Union for International Cancer Control's (UICC), TNM classification of malignant tumours. https://www.uicc.org/resources/tnm (accessed 21 April 2020). European Commission Consumers, Health, Agriculture, and Food Executive Agency (CHAFEA) Health Programmes Database, Cross-Border Patient Registries Initiative [PARENT] [20112302] - Joint Actions. Project Summary, https://webgate.ec.europa.eu/chafea_pdb/health/projects/20112302/summary/, 2015 (accessed 9 September 2019). Orphanet, Orphanet Report Series, Rare Disease Registries in Europe. http://www.orpha.net/orphacom/cahiers/docs/GB/Registries.pdf, 2019 (accessed 21 April 2020). Sinaci, 2013, A federated semantic meta- data registry framework for enabling interoperability across clinical research and care domains, J. Biomed. Inform., 46, 784, 10.1016/j.jbi.2013.05.009 ISO/IEC, 2019. ISO/IEC 11179: Information technology – Metadata Registries (MDR) Parts 1-7, ISO Standards. International Organization for Standardization. http://metadata-standards.org/11179/, 2015 (accessed 21 April 2020). Sinaci, 2015, Erturkmen, Gonul, et al, Postmarketing safety study tool: A web based, dynamic, and interoperable system for postmarketing drug surveillance studies, Biomed Res. Int., 10.1155/2015/976272 Integrating the Healthcare Enterprise (IHE), IHE Data Element Exchange (DEX) profile. https://wiki.ihe.net/index.php/Data_Element_Exchange (accessed 15 April 2020). Australian Institute of Health and Welfare, METeOR: Metadata online registry. http://meteor.aihw.gov.au/, 2019 (accessed 9 September 2019). World Health Organization, International statistical classification of diseases and related health problems – 10th revision (ICD-10 Version: 2016). https://icd.who.int/browse10/2016/en, 2016 (accessed 21 April 2010). A. Fritz, C. Percy, A. Jack, et al, International classification of diseases for oncology, 3rd ed. Technical Report, World Health Organization. https://apps.who.int/iris/handle/10665/42344, 2000 (accessed 9 September 2019). W3C Web Ontology Language (OWL). https://www.w3.org/TR/owl-features/, 2004 (accessed 9 September 2019). G. Klyne, J.J. Carroll, B. McBride, RDF 1.1 Concepts and Abstract Syntax, W3C Recommendation, World Wide Web Consortium. https://www.w3.org/TR/rdf11-concepts/, 2014 (accessed 9 September 2019). W3C, Web Services Architecture. https://www.w3.org/TR/ws-arch/ (accessed 24 April 2020). W3C SPARQL Working Group, 2013. SPARQL 1.1 Overview. W3C Recommendation. World Wide Web Consortium. https://www.w3.org/TR/2013/REC-sparql11-overview-20130321/, 2013 (accessed 21 April 2020). National Center for Biomedical Ontology, BioPortal. http://bioportal.bioontology.org (accessed 21 April 2010). Wilkinson, 2016, The FAIR guiding principles for scientific data management and stewardship, Sci. Data, 3, 10.1038/sdata.2016.18 European Commission, European cancer information system (ECIS). https://ecis.jrc.ec.europa.eu/, 2019 (accessed 9 September 2019). European Commission, List of cancer sites for estimates 2018 (ECIS). https://ecis.jrc.ec.europa.eu/pdf/Estimates_cancer_sites.pdf, 2018 (accessed 9 September 2019). E. Prud’hommeaux, G. Carothers, RDF 1.1 Turtle – Terse RDF Triple Language. W3C Recommendation. World Wide Web Consortium. http://www.w3.org/TR/2014/REC-turtle-20140225/, 2014 (accessed 21 April 2020). A. Perego, N. Nicholson, RDF representation of the ECIS data set, v1, OSF, 2020 https://osf.io/ya6bc/. SKOS Simple Knowledge Organization SystemReference, W3C Recommendation. https://www.w3.org/TR/2009/REC-skos-reference-20090818/, 2009 (accessed 21 April 2020). European Union, Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation) OJ L 119, 1–88. http://data.europa.eu/eli/reg/2016/679/oj, 2016 (accessed 21 April 2020). Blumenthal, 2017, Improving Interoperability between Registries and EHRs, AMIA Jt Summits Transl. Sci. Proc., 18, 20 European Union, Directive 2011/24/EU of the European Parliament and of the Council of 9 March 2011 on the application of patients’ rights in cross-border healthcare. OJ L 88, 45–65. http://data.europa.eu/eli/dir/2011/24/oj, 2011 (accessed 21 April 2020). V. Pajić, T. Čebular, M. Kostešić, Pilot Registry of Registries (RoR) Phase 1 Development Report. Technical Report. PARENT project. https://webgate.ec.europa.eu/chafea_pdb/assets/files/pdb/20112302/20112302_d06-00_en_ps__pilot_registry_of_registries_phase_1_development_report.pdf, 2103 (accessed 21 April 2020). BBMRI-ERIC, Biobanking and biomolecular resources European research infrastructure (BBMRI-ERIC). http://www.bbmri-eric.eu/, 2019 (accessed 9 September 2019). MIABIS Poject, Minimum information about biobank data sharing (MIABIS) standards. https://github.com/MIABIS/miabis/wiki, 2019 (accessed 9 September 2019). CORDIS, RD-CONNECT: An integrated platform connecting registries, biobanks and clinical bioinformatics for rare disease research. Project Fact Sheet. European Commission. https://cordis.europa.eu/project/id/305444, 2019 (accessed 9 September 2019). European Commission, European platform on rare disease registration (EU RD Platform). https://eu-rd-platform.jrc.ec.europa.eu/, 2019 (accessed 9 September 2019). EUBIROD Network, European best information through regional outcomes in diabetes (EUBIROD). http://www.eubirod.eu/, 2019 (accessed 21 April 2020). EUROCISS, European cardiovascular indicators surveillance set (EUROCISS). http://www.cuore.iss.it/eurociss/en/project/project.asp, 2019 (accessed 9 September 2019). CORDIS, EUROCOURSE – Europe against Cancer: Optimisation of the Use of Registries for Scientific Excellence in re- search. Project Fact Sheet, European Commission. https://cordis.europa.eu/project/id/219453, 2019 (accessed 9 September 2019). European Cystic Fibrosis Society (ECFS), European Cystic Fibrosis Society patient registry (ECFSPR). https://www.ecfs.eu/projects/ecfs-patient-registry/project, 2019 (accessed 9 September 2019). Lopes, 2012, COEUS: “semantic web in a box” for biomedical applications, J. Biomed. Semantics, 3, 10.1186/2041-1480-3-11 Sernadela, 2017, Linked registries: Connecting rare diseases patient registries through a semantic web layer, Biomed. Res. Int., 10.1155/2017/8327980