Do surveys with paper and electronic devices differ in quality and cost? Experience from the Rufiji Health and demographic surveillance system in Tanzania

BACKGROUND: Data entry at the point of collection using mobile electronic devices may make data-handling processes more efficient and cost-effective, but there is little literature to document and quantify gains, especially for longitudinal surveillance systems. OBJECTIVE: To examine the potential of mobile electronic devices compared with paper-based tools in health data collection. METHODS: Using data from 961 households from the Rufiji Household and Demographic Survey in Tanzania, the quality and costs of data collected on paper forms and electronic devices were compared. We also documented, using qualitative approaches, field workers, whom we called 'enumerators', and households' members on the use of both methods. Existing administrative records were combined with logistics expenditure measured directly from comparison households to approximate annual costs per 1,000 households surveyed. RESULTS: Errors were detected in 17% (166) of households for the paper records and 2% (15) for the electronic records (p < 0.001). There were differences in the types of errors (p = 0.03). Of the errors occurring, a higher proportion were due to accuracy in paper surveys (79%, 95% CI: 72%, 86%) compared with electronic surveys (58%, 95% CI: 29%, 87%). Errors in electronic surveys were more likely to be related to completeness (32%, 95% CI 12%, 56%) than in paper surveys (11%, 95% CI: 7%, 17%).The median duration of the interviews ('enumeration'), per household was 9.4 minutes (90% central range 6.4, 12.2) for paper and 8.3 (6.1, 12.0) for electronic surveys (p = 0.001). Surveys using electronic tools, compared with paper-based tools, were less costly by 28% for recurrent and 19% for total costs. Although there were technical problems with electronic devices, there was good acceptance of both methods by enumerators and members of the community. CONCLUSIONS: Our findings support the use of mobile electronic devices for large-scale longitudinal surveys in resource-limited settings

Data science · Environmental health · Environmental planning · Geography · Tanzania · Computer Science · ICT in Developing Communities · Medicine · Mobile Health and mHealth Applications · Survey Methodology and Nonresponse

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