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The Cooking and Pneumonia Study (CAPS) in Malawi: Implementation of Remote Source Data Verification
William Weston1, James Smedley1, Andrew Bennett1
1Liverpool School of Tropical Medicine (LSTM), Liverpool, Merseyside, United Kingdom.
Plos One
|June 30, 2016
Summary
Remote Source Data Verification (SDV) using mobile technology in rural Malawi proved feasible. Capturing digital images of records enabled efficient, secure remote SDV, reducing the need for on-site monitoring in clinical trials.
Area of Science:
- Clinical research methodology
- Public health surveillance
- Digital health interventions
Background:
- Traditional Source Data Verification (SDV) is resource-intensive, requiring multiple on-site visits.
- The Cooking And Pneumonia Study (CAPS) is a village-level trial in Malawi assessing cook-stove intervention effectiveness.
- CAPS utilized smartphones for electronic Case Report Forms (eCRFs) and digital record imaging.
Purpose of the Study:
- To evaluate the feasibility and efficiency of electronic data capture with remote SDV in a challenging rural research setting.
- To assess the use of mobile technology for data collection and verification in a public health trial.
- To report on the experience of remote SDV in the CAPS trial in Malawi.
Main Methods:
- Fieldworkers captured pneumonia data and digital images of original records onto eCRFs.
- Data and images were uploaded via a web-based application for remote SDV.
- Remote SDV compared eCRF data against digital images of original records for pneumonia occurrence, severity, and clinical indicators.
Main Results:
- After 6 months, 664 pneumonia episodes were recorded, with 92% confirmed by original records.
- All captured digital images of original records were clear and legible.
- Remote SDV was successfully conducted from the UK.
Conclusions:
- Electronic data capture with mobile technology is feasible in rural Malawi.
- Digital imaging facilitates efficient and secure remote SDV, eliminating the need for additional field visits.
- This approach is recommended for similar settings, particularly for studies with health endpoints.