ArticlePharmacoepidemiology and drug safety2025
Quantification of Information Gained by Linking Claims Data to an Electronic Health Record Cohort of Patients With Metastatic Breast Cancer.
Article in Pharmacoepidemiology and drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
2 citing papers in PubMed.
- Characterization and validation of electronic medical record data for pharmacoepidemiologic research.Frontiers in pharmacology · 2026Article
- 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
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
purposeLinking claims data to electronic health record (EHR) data can improve completeness, often at a cost of decreased sample size. Quantifying information gained and differences in patient characteristics between EHR and EHR-claims linked cohorts may inform study design.
methodsUsing ConcertAI Patient360 EHR linked to multiple closed insurance claims sources, we compared an EHR cohort of patients with incident metastatic breast cancer (mBC) to an EHR-claims subcohort (requiring ≥ 90 days claims coverage). We analyzed diagnosis coverage, patient time during lookback and follow-up, baseline characteristics, and rates of 14 adverse events (AEs). Analyses were age stratified due to insurance coverage changes at age 65.
resultsFor the EHR cohort (N = 6289), 1438 (23%) were in the EHR-claims subcohort. A greater proportion were aged ≥ 65 years in the EHR cohort (30%) than in the EHR-claims subcohort (17%). EHR-claims patients had longer observation periods and more unique diagnoses across both age groups. For most AEs, incidences were higher in both age groups in the EHR-claims subcohort than in the EHR cohort.
conclusionsEHR-claims provided more diagnoses and observation time, at the cost of a reduction in sample size and underrepresentation of patients ≥ 65 years. Differing age proportions support age-stratified or standardized analyses for EHR-claims data. Results aid interpretation of differences between EHR and EHR-claims results due to shifts in age, completeness of diagnosis history, and duration of observation.
Indexed as
Identifiers
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.