Metodologías para desarrollar arquetipos OpenEHR: una revisión narrativa de la literatura

Autores/as

  • Daiane Evangelista Ferreira Business Analyst, ProntLife, Rio de Janeiro (RJ) and Doctoral Student, Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro (PESC/COPPE/UFRJ), Rio de Janeiro (RJ), Brazil.
  • Jano Moreira de Souza PhD, Full Professor, Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro (PESC/COPPE/UFRJ), Rio de Janeiro (RJ), Brazil. https://orcid.org/0000-0001-5080-1955

DOI:

https://doi.org/10.59681/2175-4411.v15.i2.2023.970

Palabras clave:

Registros Electrónicos de Salud, semántica, metodologia

Resumen

Objetivo: Presentar una revisión narrativa de la literatura para identificar, analizar y caracterizar el estado del arte de las metodologías para el desarrollo de arquetipos openEHR. Método: Búsqueda exhaustiva en la literatura en el área de informática. Utilizamos las bases de datos IEEE Digital Library, ACM Digital Library, Science Direct, Scopus y Springer Link. El proceso de revisión implicó la aplicación de criterios de selección a los 361 textos encontrados, con el fin de seleccionar los artículos que se ajusten al alcance. Resultados: Los 9 artículos seleccionados se agruparon en cinco categorías, donde identificamos algunas conexiones y notamos que los vacíos de algunos artículos se complementaban con los vacíos de otros. Conclusión: La investigación contribuyó a la construcción de un marco teórico sobre metodologías para el desarrollo de arquetipos de openEHR, mostrando que es un tema de investigación en crecimiento y que algunos aspectos aún necesitan más estudios.

Citas

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OpenEHR Foundation. What is openEHR?. c2022. [Internet]; [cited 2020 Oct 29]. [Accessed 2022 Jun 13]. Available from: <https://www.openehr.org/>

Cruz-Correia R, Ferreira D, Bacelar G, Marques P, Maranhão P. Personalised medicine challenges: quality of data. International Journal of Data Science and Analytics 2018; 6:251-259. DOI: https://doi.org/10.1007/s41060-018-0127-9

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Eguzkiza, A., Trigo, J.D., Martínez-Espronceda, M., Serrano, L., Andonegui, J. Formalize clinical processes into electronic health information systems: Modelling a screening service for diabetic retinopathy. Journal of Biomedical Informatics 2015; 56: 112-126. Available from: <https://doi.org/10.1016/j.jbi.2015.05.017>. DOI: https://doi.org/10.1016/j.jbi.2015.05.017

Moner D, Maldonado JA, Robles M. Archetype modeling methodology. Journal of Biomedical Informatics 2018; 79:71-81. Available from: <https://doi.org/10.1016/j.jbi.2018.02.003>. DOI: https://doi.org/10.1016/j.jbi.2018.02.003

Maranhão PA, Bacelar-Silva GM, Gonçalves-Ferreira DN, Calhau C, Vieira-Marques P, Alvarenga M, et al. OpenEHR modeling applied to eating disorders in clinical practice. In: 2018 IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), 2018, 36-41. [Internet]; [cited 2020 Oct 29]. [Accessed 2022 Jun 13]. Available from: <https://ieeexplore.ieee.org/document/8417209>.

Maranhão PA, Bacelar-Silva GM, Gonçalves-Ferreira DN, Marques PV, Cruz-Correia RJ. Relevant lifelong nutrition information for the prevention and treatment of childhood obesity - Design and creation of new openEHR archetype set. In: 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), 2017, 236-241. [Internet]; [cited 2020 Oct 29]. [Accessed 2022 Jun 13]. Available from: <https://doi.org/10.1109/CBMS.2017.96>.

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Papež V, Mouček R. Applying an Archetype-Based Approach to Electroencephalography/Event-Related Potential Experiments in the EEGBase Resource. Front. Neuroinform. 2017; 11:24. Available from: <https://doi.org/10.3389/fninf.2017.00024>. DOI: https://doi.org/10.3389/fninf.2017.00024

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Publicado

2023-10-18

Cómo citar

Ferreira, D. E., & Souza, J. M. de. (2023). Metodologías para desarrollar arquetipos OpenEHR: una revisión narrativa de la literatura. Journal of Health Informatics, 15(2), 53–59. https://doi.org/10.59681/2175-4411.v15.i2.2023.970

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