Lessons learned from over a decade of data audits in international observational HIV cohorts in Latin America and East Africa

Abstract

Introduction: Routine patient care data are increasingly used for biomedical research, but such "secondary use" data have known limitations, including their quality. When leveraging routine care data for observational research, developing audit protocols that can maximize informational return and minimize costs is paramount.

Methods: For more than a decade, the Latin America and East Africa regions of the International epidemiology Databases to Evaluate AIDS (IeDEA) consortium have been auditing the observational data drawn from participating human immunodeficiency virus clinics. Since our earliest audits, where external auditors used paper forms to record audit findings from paper medical records, we have streamlined our protocols to obtain more efficient and informative audits that keep up with advancing technology while reducing travel obligations and associated costs.

Results: We present five key lessons learned from conducting data audits of secondary-use data from resource-limited settings for more than 10 years and share eight recommendations for other consortia looking to implement data quality initiatives.

Conclusion: After completing multiple audit cycles in both the Latin America and East Africa regions of the IeDEA consortium, we have established a rich reference for data quality in our cohorts, as well as large, audited analytical datasets that can be used to answer important clinical questions with confidence. By sharing our audit processes and how they have been adapted over time, we hope that others can develop protocols informed by our lessons learned from more than a decade of experience in these large, diverse cohorts.

Keywords: Data audits; HIV; LMIC; data quality; international research; observational cohorts.

Figure 1.

Breakdown of overall data quality according to separate CCASAnet audit projects over time. (RDC or site in parentheses indicates that the audits were conducted by the regional data coordinating center at Vanderbilt University or site investigators, respectively).

Figure 2.

Breakdown of overall data quality according to separate EA-IeDEA audit projects over time. (RDC or site in parentheses indicates that the audits were conducted by the regional data coordinating center at Indiana University or site investigators, respectively).