title: The Cooking and Pneumonia Study (CAPS) in Malawi: Implementation of Remote Source Data Verification.
abstract: BACKGROUND
  Source data verification (SDV) is a data monitoring procedure which compares the original records with the Case Report Form (CRF). Traditionally, on-site SDV relies on monitors making multiples visits to study sites requiring extensive resources. The Cooking And Pneumonia Study (CAPS) is a 24- month village-level cluster randomized controlled trial assessing the effectiveness of an advanced cook-stove intervention in preventing pneumonia in children under five in rural Malawi (www.capstudy.org). CAPS used smartphones to capture digital images of the original records on an electronic CRF (eCRF). In the present study, descriptive statistics are used to report the experience of electronic data capture with remote SDV in a challenging research setting in rural Malawi.
  
  
  METHODS
  At three monthly intervals, fieldworkers, who were employed by CAPS, captured pneumonia data from the original records onto the eCRF. Fieldworkers also captured digital images of the original records. Once Internet connectivity was available, the data captured on the eCRF and the digital images of the original records were uploaded to a web-based SDV application. This enabled SDV to be conducted remotely from the UK. We conducted SDV of the pneumonia data (occurrence, severity, and clinical indicators) recorded in the eCRF with the data in the digital images of the original records.
  
  
  RESULTS
  664 episodes of pneumonia were recorded after 6 months of follow-up. Of these 664 episodes, 611 (92%) had a finding of pneumonia in the original records. All digital images of the original records were clear and legible.
  
  
  CONCLUSIONS
  Electronic data capture using eCRFs on mobile technology is feasible in rural Malawi. Capturing digital images of the original records in the field allows remote SDV to be conducted efficiently and securely without requiring additional field visits. We recommend these approaches in similar settings, especially those with health endpoints.
authors.affiliation: Liverpool School of Tropical Medicine (LSTM), Liverpool, Merseyside, United Kingdom.
authors.forename: William
authors.initials: W
authors.lastname: Weston
authors.affiliation: Liverpool School of Tropical Medicine (LSTM), Liverpool, Merseyside, United Kingdom.
authors.forename: James
authors.initials: J
authors.lastname: Smedley
authors.affiliation: Liverpool School of Tropical Medicine (LSTM), Liverpool, Merseyside, United Kingdom.
authors.forename: Andrew
authors.initials: A
authors.lastname: Bennett
authors.affiliation: Liverpool School of Tropical Medicine (LSTM), Liverpool, Merseyside, United Kingdom.
authors.forename: Kevin
authors.initials: K
authors.lastname: Mortimer
mesh_terms: D002675:Child, Preschool; D016000:Cluster Analysis; D016494:Computer Security; D003296:Cooking; D003625:Data Collection / Q000379:methods*; D016208:Databases, Factual; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D020407:Internet; D008295:Malawi; D008297:Male; D011014:Pneumonia / Q000453:epidemiology*; D012424:Rural Population; D000068997:Smartphone