Background: Observational HIV clinic databases are now widely used to answer key questions related to HIV care and treatment, but there has been no systematic evaluation of their quality of data. Our objective was to evaluate the completeness and accuracy of recording of key data HIV items in a large routine observational HIV clinic database.
Methods: We looked at the number and rate of opportunistic infections (OIs) per 100 person years at risk in the 24 months following antiretroviral therapy (ART) initiation in 559 patients who initiated ART in 2004-2005 and enrolled into a research cohort. We compared this with data in a routine clinic database for the same 559 patients, and a further 1233 patients who initiated ART in the same period. The Research Cohort database was considered as the reference "gold standard" for the assessment of data accuracy. A crude percentage of underreporting of OIs in the clinic database was calculated based on the difference between the OI rates reported in both databases.We reviewed 100 clinic patient medical records to assess the accuracy of recording of key data items of OIs, ART toxicities and ART regimen changes.
Results: The overall incidence rate per 100 person years at risk for the initial OI in the 559 patients in the research cohort and clinic databases was 24.1 (95% CI: 20.5-28.2) and 13.2 (95% CI: 10.8-16.2) respectively, and 10.4 (95% CI: 9.1-11.9) for the 1233 clinic patients. This represents a 1.8- and 2.3-fold higher rate of events in the research cohort database compared with the same 599 patients and 1233 patients in the routine clinic database, or a 45.1% and 56.8% rate of underreporting, respectively. The combined error rate of missing and incorrect items from the medical records' review was 67% for OIs, 52% for ART-related toxicities, and 83% and 58% for ART discontinuation and modification, respectively.
Conclusions: There is a high rate of underreporting of OIs in a routine HIV clinic database. This has important implications for the use and interpretation of routine observational databases for research and audit, and highlights the need for regular data validation of these databases.