Perceived Reasons for High and Low Quality Observational HIV Research Data.

Audits of data quality in a Latin America HIV research network revealed that study sites collected weight measurements, laboratory results, and medication data of inconsistent quality. We surveyed site personnel about perceived drivers of their high or low quality data. Most sites reported their research teams contained no data specialists and that missing data stemmed primarily from incomplete patient assessments at the point of care rather than inconsistent data recording. The root causes of data errors resulted from limited clinic resources (e.g., broken scales, limited record storage space), workflow complications, or the indifference of external participants towards research activities. Understanding these factors supports targeted quality improvement processes.