An application of an EHR based on conceptual modeling to integrate clinical and genomic data and guide therapeutic strategy
DOI:
https://doi.org/10.18004/anales/2020.053.01.17-030Keywords:
Conceptual modelling, Healthcare, Data management, EHR, ParaguayAbstract
Currently, data management in oncology department is complex and requires advanced Information Systems (ISs) to process data where “omic” information should be integrated together with patient’s clinical data to improve data analysis and decision-making process. This research paper reports a practical experience in this context. A Conceptual Model (CM) has been designed to develop an Information System (IS) in order to manage clinical, pathological, and molecular data in a holistic way at the oncology department of two main Hospitals in Paraguay. Additionally, model-based archetypes have been proposed to specify the selected user interaction strategy. The CM and its associated archetypes are the basis to develop a clinical IS in order to load -firstly- and manage -secondly- all the clinical data that the domain requires, showing how feasible the approach is in practice, and how much the corresponding clinical data management is improved. In this work, we want to reinforce with this real experience how using a CM along with archetypes correctly helps to design, develop and manage better information systems, emphasizing the relevance of the selected clinical domain.
References
1. World Health Organization (WHO) [Internet]. The problem; [cited 2019 Nov 11]. Available from: http://www.who.int/mediacentre/factsheets/fs297/en/
2. Electronic health record [Internet]. What is an electronic health record (EHR)? [cited 2019 Nov 11]. Available from: https://www.healthit.gov/faq/what-electronic-health-record-ehr
3. Multicenter Project of Multidisciplinary Training in Cancer and Application of Electronic Clinical History (ECH) [Internet]. Associative project within the Procience program of the National Council of Technology and Science (CONACYT-Paraguay); [cited 2019 Nov 11]. Available from: http://paraguay.pros.webs.upv.es/?page_id=1211&lang=en
4. International Organization for Standardization [Internet]. ISO 13606-1:2008 Health informatics – Electronic health record communication; [cited 2019 Nov 11]. Available from: https://www.iso.org/standard/40784.htm
5. Burriel V. Diseño y Desarrollo de un Sistema de Información para la Gestión de Información sobre Cáncer de Mama, PhD Thesis. Universitat Politècnica de València; [cited 2019 Nov 11]. Available from: https://riunet.upv.es/handle/10251/86158 doi:10.4995/Thesis/10251/86158.
6. Villanova P, et al. Orion Clinic. Un sistema de información orientado a transformar el uso de la información en la práctica clínica, administrativa y asistencial de los hospitales. IS Informática y Salud; 2011, vol. 85, pp. 18-26.
7. OpenEMR [Internrt]. Free open-source electronic medical record and practice management software; [cited 2019 Nov 11]. Available from: http://www.open-emr.org/
8. RITA [Internet]. Institutional Registry of Tumors of Argentina; [cited 2019 Nov 11]. Available from: http://www.msal.gov.ar/inc/epidemiologia-y-registros/rita/
9. Valencia Health Agency [Internet]. Generalitat Valenciana; [cited 2019 Nov 11]. Available from: http://www.san.gva.es/web_estatica/index_es.html
10. Hospital de clínicas [Internet]. Universidad Nacional de Asunción, Facultad de Ciencias Médicas; [cited 2019 Nov 11]. Available from: http://www.med.una.py/index.php/hospital-hc/directivos-del-hospital-de-clinicas
11. Instituto Nacional del Cáncer (INCAN) [Internet]. Asunción, Paraguay; [cited 2019 Nov 11]. Available from: https://www.mspbs.gov.py/incan
12. Multicenter Project of Multidisciplinary Training in Cancer and Application of Electronic Clinical History (ECH) [Internet]. Results of the project: [cited 2019 Nov 11]. Available from: http://paraguay.pros.webs.upv.es/?page_id=583&lang=es
13. Hamilton K, Miles R. Learning UML 2.0: A Pragmatic Introduction to UML. Published by O’Reilly; 2008. 288 p.
14. Burriel V, Pastor Ó. Conceptual Schema of Breast Cancer: The background to design an efficient information system to manage data from diagnosis and treatment of breast cancer patients, IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI); 2014. pp. 432-435.
15. Carboplatin AUC Dose Calculation [Internet]. Calvert Formula; [cited 2019 Nov 11]. Available from: https://reference.medscape.com/calculator/carboplatin-auc-dose-calvert
16. MASCC [Internet]. Multinational Association for Supportive Care in Cancer; [cited 2019 Nov 11]. Available from: http://www.mascc.org/mascc-fn-risk-index-score
17. CISNE [Internet]. Clinical Index of Stable Febrile Neutropenina; [cited 2019 Nov 11]. Available from: http://www.iricom.es/prognostictools/cisne/inicio.aspx
18. Purewal S. Learning Web App Development. Published by O’Reilly Media Inc; 2014.
19. Rudis B, Jacobs J. Data-Driven Security Analysis, Visualization and Dashboards. Published by John Wiley & Sons, Inc., Indianapolis, Indiana; 2014.
20. Distante D, Pedone P, Rossi G, and Canfora G. Model-Driven Development of Web Applications with UWA, MVC and JavaServer Faces, International Conference on Web Engineering. Published by Springer; 2007. pp 457-472.
21. The Gang of Four: Gamma E, Helm R, Johnson R, Vlissides J. Design Patterns: Elements of Reusable Object-Oriented Software; 1994.
22. Beydeda S, Book M, Gruhn V. Model-Driven Software Development. Published by Springer; 2005.
23. Hailpern B, Tarr P. Model-driven development: The good, the bad, and the ugly. IBM System Journal; 2006. Vol 45. No 3. p 451-461.
24. Bloch J. Effective Java, Best practices for Java Performance. Published by Pearson Education Inc; 2018.
25. Vohra D. Java EE Development with Eclipse. Published by Packt Publishing Ltd; 2012.
26. Grönroos M. Book of Vaadin: 4th Edition, 1st Revision Edition. Vaadin Ltd; 2012.
27. Williams H, Tahaghoghi S. Learning MySQL. Published by O’Reilly Media, Inc; 2009.
28. M2T transformation [Internet]. Eclipse IDE components for Model to Text transformation; [cited 2019 Nov 11]. Available from: https://www.eclipse.org/modeling/m2t/
29. Marcos M, Maldonado Segura JA, Martinez-Salvador B, Boscá Tomás D, Robles Viejo M. Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility. Journal of Biomedical Informatics; 2013. 46(4): p 676-689.
30. Maldonado JA, Moner D, Boscá D, Fernández-Beris J, Angulo C, Robles M. LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics, International Journal of Medical Informatics; 2009. Vol. 78. Issue 8. p 559-570.
