King, C., Hall, J., Banda, M., Beard, J., Bird, J., Kazembe, P. & Fottrell, E. (2014). Electronic data capture in a rural African setting: evaluating experiences with different systems in Malawi. Global Health Action, 7(1), doi: 10.3402/gha.v7.25878
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As hardware for electronic data capture (EDC), such as smartphones or tablets, becomes cheaper and more widely available, the potential for using such hardware as data capture tools in routine healthcare and research is increasing.
We aim to highlight the advantages and disadvantages of four EDC systems being used simultaneously in rural Malawi: two for Android devices (CommCare and ODK Collect), one for PALM and Windows OS (Pendragon), and a custom-built application for Android (Mobile InterVA – MIVA).
We report on the personal field and development experience of fieldworkers, project managers, and EDC system developers.
Fieldworkers preferred using EDC to paper-based systems, although some struggled with the technology at first. Highlighted features include in-built skip patterns for all systems, and specifically the ‘case’ function that CommCare offers. MIVA as a standalone app required considerably more time and expertise than the other systems to create and could not be customised for our specific research needs; however, it facilitates standardised routine data collection. CommCare and ODK Collect both have user-friendly web-interfaces for form development and good technical support. CommCare requires Internet to build an application and download it to a device, whereas all steps can be done offline with ODK Collect, a desirable feature in low connectivity settings. Pendragon required more complex programming of logic, using a Microsoft Access application, and generally had less technical support. Start-up costs varied between systems, and all were considered more expensive than setting up a paper-based system; however running costs were generally low and therefore thought to be cost-effective over the course of our projects.
EDC offers many opportunities for efficient data collection, but brings some issues requiring consideration when designing a study; the decision of which hardware and software to use should be informed by the aim of data collection, budget, and local circumstances.
|Additional Information:||© 2014 Carina King et al. Published by Taylor & Francis in Global Health Action 2014, 7: 25878.|
|Uncontrolled Keywords:||Science & Technology; Life Sciences & Biomedicine; Public, Environmental & Occupational Health; mHealth; electronic data capture; Sub-Saharan Africa; MIVA; ODK Collect; CommCare; Pendragon; MOBILE PHONES|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||School of Informatics > Department of Computing|
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