Novel mHealth Platform to Ensure Quality of Community-based Malaria Diagnosis

Duke University

Status: Completed

Conditions: Quality Assurance of Malaria Diagnosis

Treatments: Device: mHealth platform employing Fionet Deki Readers to ensure quality of community-based malaria diagnosis

Study type: Interventional

Funder types: Other

Identifiers

NCT02504593

Pro00063521

Details and patient eligibility

About

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). The study will lease 10 DRs and rotate them amongst 200 CHVs performing community-based malaria diagnosis through rapid diagnostic testing. The study setting is Bungoma East subcounty and Kiminini subcounty in Kenya. The overall goal is to measure and improve the quality of malaria diagnosis by CHVs using malaria RDTs. The investigators aim for every CHW to exceed 90% sensitivity and specificity and zero operator errors within six months. There are no appreciable risks to the CHV associated with evaluation by the DR device. The investigators' analysis will focus on descriptive statistics of RDT use and accuracy amongst all participating CHVs.

Enrollment: 100 patients

Sex: All

Ages: 18+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• All community health volunteers in 10 community units in Bungoma East and 6 community units in Kiminini that have been trained to provide community-based malaria diagnosis through rapid diagnostic testing are eligible.

Exclusion criteria

• Any person not meeting the inclusion criteria.

Trial design

100 participants in 1 patient group

Community health volunteers

Other group

Description:

The study subjects are all community health volunteers in community units in Kenya (10 community units in Bungoma East and 6 community units in Kiminini) that have been trained to provide community-based malaria diagnosis through rapid diagnostic testing.

Treatment:

Device: mHealth platform employing Fionet Deki Readers to ensure quality of community-based malaria diagnosis