Making EHRs Trustable: A Quality Analysis of EHR-Derived Datasets for COVID-19 Research

Miguel Pedrera-Jiménez, Noelia García-Barrio, Paula Rubio-Mayo, Guillermo Maestro, Antonio Lalueza, Ana Garcia-Reyne, María José Zamorro, Alejandra Pons, María Jesús Sanchez-Martin, Jaime Cruz-Rojo, Víctor Quiros, José María Aguado, Juan Luis Cruz-Bermúdez, José Luis Bernal, Laura Merson, Carlos Lumbreras, Pablo Serrano. Making EHRs Trustable: A Quality Analysis of EHR-Derived Datasets for COVID-19 Research. In Brigitte Séroussi, Patrick Weber, Ferdinand Dhombres, Cyril Grouin, Jan-David Liebe, Sylvia Pelayo, Andrea Pinna 0001, Bastien Rance, Lucia Sacchi, Adrien Ugon, Arriel Benis, Parisis Gallos, editors, Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022, Medical Informatics Europe, Nice, France, May 27-30, 2022. Volume 294 of Studies in Health Technology and Informatics, pages 164-168, IOS Press, 2022. [doi]

Abstract

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