Data management plan for a community-level study of the hidden burden of cutaneous leishmaniasis in Colombia
| Autor: | Neal Alexander, Leonardo Vargas Bernal, Yenifer Orobio Lerma, Andres Navarro, Oscar Javier Oviedo Sarmiento, María del Mar Castro |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Science (General)
020205 medical informatics Interface (Java) Computer science QH301-705.5 Data management Leishmaniasis Cutaneous 02 engineering and technology Clinical prediction rule MHealth Colombia General Biochemistry Genetics and Molecular Biology 03 medical and health sciences Q1-390 0302 clinical medicine Under-reporting 0202 electrical engineering electronic engineering information engineering Humans 030212 general & internal medicine Biology (General) mHealth Data Management Data collection Cutaneous leishmaniasis business.industry Data management plan General Medicine Data science Mobile Applications Telemedicine Research Note Medicine Rural area business |
| Zdroj: | BMC Research Notes BMC Research Notes, Vol 14, Iss 1, Pp 1-6 (2021) |
| ISSN: | 1756-0500 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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