100
Participants
Start Date
July 31, 2015
Primary Completion Date
April 30, 2016
Study Completion Date
April 30, 2016
mHealth platform employing Fionet Deki Readers to ensure quality of community-based malaria diagnosis
The investigators propose to implement a new mobile interface that automatically reads and troubleshoots malaria rapid diagnostic test (RDT) cassettes. This device, called a Deki reader (DR), will allow the investigators to establish an extensive quality assurance program of malaria diagnosis performed by trained community health volunteers (CHVs). To ensure high-quality diagnosis by CHVs, the study team will deploy 10 Fionet DRs and rotate them amongst 200 CHVs who have been trained to do RDTs. In the first phase, each CHV will use the device for 10 successive clients presenting themselves for malaria diagnosis to the CHV, and then the device will be rotated to another CHV.
Duke University, Eldoret
Lead Sponsor
Duke University
OTHER