Lesionia: a digital data management system for epidemiological and clinical data collected from patients suspected for cutaneous leishmaniasis

DOI: https://doi.org/10.21203/rs.2.22461/v1

Abstract

Background. Digital systems for data management (DSDM) are considered nowadays of high importance in the field of biomedical sciences. Such systems ensure that data meet the standards of FAIR (Findability, Accessibility, Interoperability and Reusability). Our group is interested in implementing a DSDM for data collected from patients suspected of having cutaneous leishmaniasis (CL) in the frame of diagnostics evaluation. The data is collected in multiple sites and countries by different partners in the frame of a project supported by the USAID-NAS PEER program. We capitalized on the thorough clinical and field expertise of some partners to assess needs. Then, we further refined these needs consortium-wide to define the data to be collected by the clinicians and biologists during the data life cycle. This led to the development of a questionnaire form for data collection and the implementation of a web-based application, called Lesionia.

Results. Based on the questionnaire, we developed Lesionia, a digital system for the management and the analysis of clinical and epidemiological data. It consists of a relational database and a web-based user interface (WUI). The database was conceived to be expandable to new collaborators and projects. It allows for data handling from the consented patient interview and sample collection to the samples storage and investigation. The WUI permits data entry, fetching, visualization and analysis. Rigorous controls on data entry were implemented to reduce discrepancies. It also offers a set of analysis tools that range from descriptive statistics to variable correlation analysis. Lesionia is accessible in a secure manner to all users of the consortium through a web browser connected to the Internet.

Conclusion. Lesionia is a valuable tool for clinical and epidemiological data management. It is an open source software that can broadly serve the scientific community interested in studying, controlling, reporting and diagnosing CL and similar cutaneous diseases.

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