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 subSaharan 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.
