ArticleBiometrics2023
Multiwave validation sampling for error-prone electronic health records.
Article in Biometrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 16 citations in OpenAlex.
- 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
- Using large language models to enhance clinically-driven missing data recovery algorithms in electronic health records.JAMIA open · 2026Article
- Prevalence and Predictors of Guideline Concordant Pediatric Obesity Care: A Narrative Review.Current obesity reports · 2026Review
- Assessing Treatment Effects in Observational Data With Missing Confounders: A Comparative Study of Practical Doubly-Robust and Traditional Missing Data Methods.Statistics in medicine · 2026Article
- RELEAP: reinforcement-enhanced label-efficient active phenotyping for electronic health records.JAMIA open · 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
- Adaptive Multi-Wave Sampling for Efficient Chart Validation.Clinical epidemiology · 2026Article
- An Augmented Likelihood Approach Incorporating Error-Prone Auxiliary Data Into a Survival Analysis.Statistics in medicine · 2025Article
- 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
- Overcoming data challenges through enriched validation and targeted sampling to measure whole-person health in electronic health records.Journal of biomedical informatics · 2025Article
- Ascertainment Conditional Maximum Likelihood for Continuous Outcome Under Two-Phase Response-Selective Design.Statistics in medicine · 2025Article
- A future of data-rich pharmacoepidemiology studies: transitioning to large-scale linked electronic health record + claims data.American journal of epidemiology · 2025Article
- Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall.Journal of statistical software · 2025Article
- Optimal multiwave validation of secondary use data with outcome and exposure misclassification.The Canadian journal of statistics = Revue canadienne de statistique · 2024Article
- Associations Between Gestational Weight Gain, Gestational Diabetes, and Childhood Obesity Incidence.Maternal and child health journal · 2024Article
- Three-phase generalized raking and multiple imputation estimators to address error-prone data.Statistics in medicine · 2024Article
- Practical strategies for operationalizing optimal allocation in stratified cluster-based outcome-dependent sampling designs.Statistics in medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 2 countries.
Funding
Abstract
Electronic health record (EHR) data are increasingly used for biomedical research, but these data have recognized data quality challenges. Data validation is necessary to use EHR data with confidence, but limited resources typically make complete data validation impossible. Using EHR data, we illustrate prospective, multiwave, two-phase validation sampling to estimate the association between maternal weight gain during pregnancy and the risks of her child developing obesity or asthma. The optimal validation sampling design depends on the unknown efficient influence functions of regression coefficients of interest. In the first wave of our multiwave validation design, we estimate the influence function using the unvalidated (phase 1) data to determine our validation sample; then in subsequent waves, we re-estimate the influence function using validated (phase 2) data and update our sampling. For efficiency, estimation combines obesity and asthma sampling frames while calibrating sampling weights using generalized raking. We validated 996 of 10,335 mother-child EHR dyads in six sampling waves. Estimated associations between childhood obesity/asthma and maternal weight gain, as well as other covariates, are compared to naïve estimates that only use unvalidated data. In some cases, estimates markedly differ, underscoring the importance of efficient validation sampling to obtain accurate estimates incorporating validated data.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.