Abstract
OBJECTIVE: Ensuring good data quality within telemedicine and e-health systems in developing countries is resource intensive. We set out to evaluate an approach where in-built functionality within an electronic record system could identify data quality and integrity problems with little human input. MATERIALS AND METHODS: We developed a robust data integrity module to identify, enumerate, and facilitate correction of errors within an e-health system that is in wide use in sub-Saharan Africa. RESULTS: The data integrity module was successfully implemented within an electronic medical record system in Western Kenya. Queries were set to fail if one of more records did not meet defined criteria for data integrity. Only one of 14 data integrity checks implemented uncovered no errors. The other queries had errors or questionable results ranging from 51 records to 30,301 records. However, as a proportion of all patients and all observation, the identified records with likely data integrity problems only constituted a small percentage of all records (mean 0.96%, range 0-4.1%). Twelve of the 14 queries (86%) were executed in<15 s, with the longest query lasting 2 min and 18 s. CONCLUSION: A tool that allows for automatic data integrity and quality checks was successfully implemented within an e-health system in sub-Saharan Africa. The tool potentially reduces the burden of maintaining data quality by limiting the scale of manual reviews needed to identify electronic records with errors.