Dataset Information

The impact of data quality and source data verification on epidemiologic inference: a practical application using HIV observational data.

ABSTRACT: BACKGROUND:Data 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. METHODS:We 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. RESULTS:The 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. CONCLUSION:Though some changes may have occurred independently, our findings suggest that improved data quality following the audit may impact epidemiological inferences.

SUBMITTER: Giganti MJ

PROVIDER: S-EPMC6937856 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The impact of data quality and source data verification on epidemiologic inference: a practical application using HIV observational data.

Giganti Mark J MJ Shepherd Bryan E BE Caro-Vega Yanink Y Luz Paula M PM Rebeiro Peter F PF Maia Marcelle M Julmiste Gaetane G Cortes Claudia C McGowan Catherine C CC Duda Stephany N SN

BMC public health 20191230 1

<h4>Background</h4>Data 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.<h4>Methods</h4>We 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 sele ...[more]

PMID: 31888571

Similar Datasets

Project description:Octavius® -4D is a very effective device in radiotherapy treatment quality assurance (QA), due to its simple set-up and analysis package. However, even if it is widely used, its main characteristics and criticalities were only partially investigated. Taking start from its commissioning, the aim of this work was to study the main dependencies of the device response. The outcome dependence was studied comparing results by different delivery techniques [Intensity Modulated Radiation Therapy, IMRT (n = 29) and RapidArc, RA (n = 15)], anatomical regions [15 head/neck, 19 pelvis and 10 pancreas] and linear accelerators [DHX (n = 14) and Trilogy (n = 30)]. Moreover, the agreement dependency on the section of the phantom was assessed. Plan evaluations obtained by 2D, 3D, and volumetric ?-index (both local and global) were also compared. Generally, high dose gradient resulted critically managed by the assembly, with a smoother effect in RA technique. Worse agreements emerged in the 2D ?-index vs those of 3D and volumetric (P < 0.001), that were instead statistically comparable in global metric (P > 0.300). Volumetric plan evaluation was coherent with the average of passing rates on the 3 phantom axes (r ? 0.9), but transversal section provided best agreements vs sagittal and coronal ones (P < 0.050). The three studied districts furnished comparable results (P > 0.050) while the two LINACs provided different agreements (P < 0.005). The study pointed out that the phantom transversal section better fits the planned dose distribution, so this should be accounted when a two-dimensional evaluation is needed. Moreover, the major reliability of the 3D metric with respect to the 2D one, as it better agrees with the dosimetric evaluation on the whole volume, suggests that it should be preferred in a two-dimensional evaluation. Better agreements, obtained with RA vs IMRT technique, confirm that Octavius® -4D is specifically conceived for rotational delivery. Lastly, the assembly resulted sensitive to different technology.

Project description:IntroductionCausal inference helps researchers and policy-makers to evaluate public health interventions. When comparing interventions or public health programs by leveraging observational sensitive individual-level data from populations crossing jurisdictional borders, a federated approach (as opposed to a pooling data approach) can be used. Approaching causal inference by re-using routinely collected observational data across different regions in a federated manner, is challenging and guidance is currently lacking. With the aim of filling this gap and allowing a rapid response in the case of a next pandemic, a methodological framework to develop studies attempting causal inference using federated cross-national sensitive observational data, is described and showcased within the European BeYond-COVID project.MethodsA framework for approaching federated causal inference by re-using routinely collected observational data across different regions, based on principles of legal, organizational, semantic and technical interoperability, is proposed. The framework includes step-by-step guidance, from defining a research question, to establishing a causal model, identifying and specifying data requirements in a common data model, generating synthetic data, and developing an interoperable and reproducible analytical pipeline for distributed deployment. The conceptual and instrumental phase of the framework was demonstrated and an analytical pipeline implementing federated causal inference was prototyped using open-source software in preparation for the assessment of real-world effectiveness of SARS-CoV-2 primary vaccination in preventing infection in populations spanning different countries, integrating a data quality assessment, imputation of missing values, matching of exposed to unexposed individuals based on confounders identified in the causal model and a survival analysis within the matched population.ResultsThe conceptual and instrumental phase of the proposed methodological framework was successfully demonstrated within the BY-COVID project. Different Findable, Accessible, Interoperable and Reusable (FAIR) research objects were produced, such as a study protocol, a data management plan, a common data model, a synthetic dataset and an interoperable analytical pipeline.ConclusionsThe framework provides a systematic approach to address federated cross-national policy-relevant causal research questions based on sensitive population, health and care data in a privacy-preserving and interoperable way. The methodology and derived research objects can be re-used and contribute to pandemic preparedness.

Dataset Information

The impact of data quality and source data verification on epidemiologic inference: a practical application using HIV observational data.

Publications

The impact of data quality and source data verification on epidemiologic inference: a practical application using HIV observational data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets