Methodological description of clinical research data collection through electronic medical records in a center participating in an international multicenter study

• Autor(a) principal: Queiroz,Veronica Neves Fialho
• Data de Publicação: 2019
• Outros Autores: Oliveira,Andrea da Costa Moreira de, Chaves,Renato Carneiro de Freitas, Moura,Lucas Araújo de Borges, César,Daniel Sousa, Takaoka,Flávio, Serpa Neto,Ary
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Einstein (São Paulo)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1679-45082019000400900
• topic: Electronic health records; Data accuracy; Data collection; Anesthesia; Critical care

ABSTRACT Data collection for clinical research can be difficult, and electronic health record systems can facilitate this process. The aim of this study was to describe and evaluate the secondary use of electronic health records in data collection for an observational clinical study. We used Cerner Millennium®, an electronic health record software, following these steps: (1) data crossing between the study’s case report forms and the electronic health record; (2) development of a manual collection method for data not recorded in Cerner Millennium®; (3) development of a study interface for automatic data collection in the electronic health records; (4) employee training; (5) data quality assessment; and (6) filling out the electronic case report form at the end of the study. Three case report forms were consolidated into the electronic case report form at the end of the study. Researchers performed daily qualitative and quantitative analyses of the data. Data were collected from 94 patients. In the first case report form, 76.5% of variables were obtained electronically, in the second, 95.5%, and in the third, 100%. The daily quality assessment of the whole process showed complete and correct data, widespread employee compliance and minimal interference in their practice. The secondary use of electronic health records is safe and effective, reduces manual labor, and provides data reliability. Anesthetic care and data collection may be done by the same professional.