Quality of data collection in a large HIV observational clinic database in sub‐Saharan Africa: implications for clinical research and audit of care

Abstract

BackgroundObservational 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.MethodsWe 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.ResultsThe 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.ConclusionsThere 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.

Correlates of Use of Timed Unprotected Intercourse to Reduce Horizontal Transmission Among Ugandan HIV Clients with Fertility Intentions

“…Greatly improved access to ART [5], and knowledge of the efficacy of treatment to reduce transmission likely contributes to the high proportion (20–50%) of persons living with HIV (PLWHIV) who desire to have children in Uganda [6–8] and the larger region [9–12]. In fact, 20–40% of HIV-infected women become pregnant post-HIV diagnosis [13, 14], and nearly 100,000 HIV-infected women become pregnant annually in Uganda [15].…”

An algorithm to improve diagnostic accuracy in diabetes in computerised problem orientated medical records (POMR) compared with an established algorithm developed in episode orientated records (EOMR)

“…The data quality is poor in about 5% of records in health organisations 23–25. Many studies regularly report a range of deficiencies in the routinely collected electronic information for clinical6,26 or health promotion23 purposes in hospital27 and general practice28 settings.…”

A structured approach to recording AIDS-defining illnesses in Kenya: A SNOMED CT based solution

“…A majority of clinics providing HIV care and treatment in SSA use a fixed list of coarse-grained ADIs to perform clinical staging of HIV-infection as recommended by WHO [8]. Kiragga et al estimate that ADIs in clinical settings are under-reported by up to 67% in HIV clinics in Uganda [10]. Classification and terminology systems are increasingly used in developed countries for clinical documentation [12].…”

“…Classification and terminology systems are increasingly used in developed countries for clinical documentation [12]. Lack of a structured, uniquely coded and comprehensive set of ADIs based on a terminology standard, from which diagnoses can be documented to support clinical decisions such as eligibility for antiretroviral therapy can potentially compromise the quality of care [10,13]. Additionally, in busy clinics with over-worked health workers, ADIs are rarely recorded with a fine granularity including more specific disease sub-types.…”