ArticleBMC public health2019
The impact of data quality and source data verification on epidemiologic inference: a practical application using HIV observational data.
Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Data Quality of Longitudinally Collected Patient-Reported Outcomes After Thoracic Surgery: Comparison of Paper- and Web-Based Assessments.Journal of medical Internet research · 2021Trial
- Quality assessment of the forensic surveillance system: A data-quality monitoring system for substance-abuse detection in unnatural deaths in Thailand.Forensic science international. Synergy · 2026Article
- The Caribbean, Central and South America Network for HIV Epidemiology: 20 Years of HIV Research in the Region.Journal of the International AIDS Society · 2026Article
- Analysis approaches to combine error-prone data with a subset of validated data: an application to a multinational study of Kaposi sarcoma and HIV.American journal of epidemiology · 2026Article
- Data validation in multinational observational studies with error-prone data: applying an optimal validation sampling strategy in a study of Kaposi sarcoma and HIV.American journal of epidemiology · 2025Article
- Article
- Optimal multiwave validation of secondary use data with outcome and exposure misclassification.The Canadian journal of statistics = Revue canadienne de statistique · 2024Article
- Adopting Data to Care to Identify and Address Gaps in Services for Children and Adolescents Living With HIV in Mozambique.Global health, science and practice · 2024Article
- Source Data Verification (SDV) quality in clinical research: A scoping review.Journal of clinical and translational science · 2024Article
- Article
- Lessons learned from over a decade of data audits in international observational HIV cohorts in Latin America and East Africa.Journal of clinical and translational science · 2023Article
- Efficient odds ratio estimation under two-phase sampling using error-prone data from a multi-national HIV research cohort.Biometrics · 2022Article
- Improving data quality in observational research studies: Report of the Cure Glomerulonephropathy (CureGN) network.Contemporary clinical trials communications · 2021Article
- Looking beyond the numbers: quality assurance procedures in the Global Network for Women's and Children's Health Research Maternal Newborn Health Registry.Reproductive health · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundData audits are often evaluated soon after completion, even though the identification of systematic issues may lead to additional data quality improvements in the future. In this study, we assess the impact of the entire data audit process on subsequent statistical analyses.
methodsWe conducted on-site audits of datasets from nine international HIV care sites. Error rates were quantified for key demographic and clinical variables among a subset of records randomly selected for auditing. Based on audit results, some sites were tasked with targeted validation of high-error-rate variables resulting in a post-audit dataset. We estimated the times from antiretroviral therapy initiation until death and first AIDS-defining event using the pre-audit data, the audit data, and the post-audit data.
resultsThe overall discrepancy rate between pre-audit and audit data (n = 250) across all audited variables was 17.1%. The estimated probability of mortality and an AIDS-defining event over time was higher in the audited data relative to the pre-audit data. Among patients represented in both the post-audit and pre-audit cohorts (n = 18,999), AIDS and mortality estimates also were higher in the post-audit data.
conclusionThough some changes may have occurred independently, our findings suggest that improved data quality following the audit may impact epidemiological inferences.
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