ArticleAnnals of epidemiology2022
An algorithm to predict data completeness in oncology electronic medical records for comparative effectiveness research.
Article in Annals of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
- Quantification of Information Gained by Linking Claims Data to an Electronic Health Record Cohort of Patients With Metastatic Breast Cancer.Pharmacoepidemiology and drug safety · 2025Article
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Authors and funding
5 authors.
Funding
Abstract
introductionElectronic health record (EHR) discontinuity (missing out-of-network encounters) can lead to information bias. We sought to construct an algorithm that identifies high EHR-continuity among oncology patients.
methodsUsing a linked Medicare-EHR database and regression, we sought to 1) measure how often Medicare claims for outpatient encounters were substantiated by visits recorded in the EHR, and 2) predict continuity ratio, defined as the yearly proportion of outpatient encounters reported to Medicare that were captured by EHR data. The prediction model...s performance was evaluated with the coefficient of determination and Spearman...s correlation. We quantified variable misclassification by decile of continuity ratio using standardized difference and sensitivity.
resultsA total of 79,678 subjects met all eligibility criteria. Predicted and observed continuity was highly correlated (σ
conclusionIn the oncology population, restricting EHR-based study cohorts to subjects with high continuity may reduce misclassification without greatly impacting representativeness. Further work is needed to elucidate the best manner of implementing continuity prediction rules in cohort studies.
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