How to set up a database?-a five-step process.

Fiche publication

Date publication

octobre 2018

Journal

Journal of thoracic disease

Auteurs

Membres identifiés du Cancéropôle Est :
Pr FALCOZ Pierre-Emmanuel , Pr MAUNY Frédéric

Tous les auteurs :
Brembilla A, Martin B, Parmentier AL, Desmarets M, Falcoz PE, Puyraveau M, Mauny F

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/30510791

Résumé

Database set-up directly impacts the quality and viability of research data, and therefore is a crucial part of the quality of clinical research. Setting up a quality database implies following a strict data-management process. Too much collected information threatens the quality of the information required to achieve the objectives of the study. Therefore, the data that will be collected and managed have to be cautiously discussed and selected. Case report forms (CRF) are the tools the most frequently used to collect the data specified by the protocol. An informative and well-structured document simplifies database design and data validation. Key elements are about choice of sequential or thematic structuring, information and type of information that should be entered and the importance of data standards and coding guide. Final database must be structured with unique ID patient, with one record per subject or per measure. Specific information must be provided for each variable according to the database specifications. The quality of the results is directly related to the quality of the collected data. The CRF should then be completed as fully and accurately as possible. Data validation relies on three key points: the CRF completion guidelines, the Edit Checks process and the Data clarification process. Various open source or business software applications provide all functionalities to set up a clinical data base and CRF. The General Data Protection Regulation (GDPR) standardizes and strengthens the protection of personal data across the EU and for other country's data being "processed" within the EU. The General principles include lawfulness, fairness and transparency, restricted use of data, data minimization, accuracy, limited storage, confidentiality and probity, and accountability.