Data management plan for a community-level study of the hidden burden of cutaneous leishmaniasis in Colombia

Abstract

Objectives Cutaneous leishmaniasis is a vector-borne parasitic disease whose lasting scars can cause stigmatization and depressive symptoms. It is endemic in remote rural areas and its incidence is under-reported, while the effectiveness, as opposed to efficacy, of its treatments is largely unknown. Here we present the data management plan (DMP) of a project which includes mHealth tools to address these knowledge gaps in Colombia. The objectives of the DMP are to specify the tools and procedures for data collection, data transfer, data entry, creation of analysis dataset, monitoring and archiving. Results The DMP includes data from two mobile apps: one implements a clinical prediction rule, and the other is for follow-up and treatment of confirmed cases. A desktop interface integrates these data and facilitates their linkage with other sources which include routine surveillance as well as paper and electronic case report forms. Multiple user and programming interfaces are used, as well as multiple relational and non-relational database engines. This DMP describes the successful integration of heterogeneous data sources and technologies. However the complexity of the project meant that the DMP took longer to develop than expected. We describe lessons learned which could be useful for future mHealth projects.

Sensitivity and Specificity of the Remote Evaluation of Therapeutic Response in Cutaneous Leishmaniasis Using Photographs from a Mobile Application

“…The web application allows access to the clinical photographs to be evaluated. 13 Access to both the mobile and the web-based apps was protected by password. The application ecosystem has an administrator role that allows registering new community leaders to access to the application and evaluate patients.…”