As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Making EHRs Trustable: A Quality Analysis of EHR-Derived Datasets for COVID-19 Research
Miguel Pedrera-Jimenez, Noelia Garcia-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-Bermudez, José Luis Bernal, Laura Merson, Carlos Lumbreras, Pablo Serrano
One approach to verifying the quality of research data obtained from EHRs is auditing how complete and correct the data are in comparison with those collected by manual and controlled methods. This study analyzed data quality of an EHR-derived dataset for COVID-19 research, obtained during the pandemic at Hospital Universitario 12 de Octubre. Data were extracted from EHRs and a manually collected research database, and then transformed into the ISARIC-WHO COVID-19 CRF model. Subsequently, a data analysis was performed, comparing both sources through this convergence model. More concepts and records were obtained from EHRs, and PPV (95% CI) was above 85% in most sections. In future studies, a more detailed analysis of data quality will be carried out.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.