ArticleAmerican journal of epidemiology2025
A future of data-rich pharmacoepidemiology studies: transitioning to large-scale linked electronic health record + claims data.
Article in American journal of epidemiology, 2025. 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
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
17 citing papers in PubMed.
- Real-World Use of Abrocitinib for Moderate-to-Severe Atopic Dermatitis in the United States Based on Electronic Health Records and Administrative Claims.Advances in therapy · 2026Article
- Tirzepatide Use Is Associated with Reduced Risk of Carpal Tunnel Syndrome in Overweight and Obese Adults.Clinical pharmacology and therapeutics · 2026Article
- Prenatal Prescription Opioid Analgesic Exposure and Academic Performance in Third Grade Children: A Population-Based Cohort Study.BJOG : an international journal of obstetrics and gynaecology · 2026Article
- Methods for incorporating test result information within the high-dimensional propensity score framework: application in UK electronic health record data.BMC medical research methodology · 2026Article
- Assessing the quality of electronic health record data and the claims linked data for target trial emulation studies.JAMIA open · 2026Article
- Characterization and comparison of structured and unstructured electronic health record data mapped to MedDRA for post-marketing surveillance.JAMIA open · 2026Article
- Mapping eligibility criteria in oncology target trial emulations using real-world data: a scoping review.BMC medical research methodology · 2026Article
- Use of Clinical Notes to Assess Neuropsychiatric Events After Montelukast Initiation.JAMA network open · 2026Article
- Performance of the Self-Controlled Case Series for Drug Safety Signal Detection: A Multi-Database Study.Pharmacoepidemiology and drug safety · 2026Article
- Article
- Leveraging electronic health record data for precision medicine insights: the precision medicine registry at NYU Langone Health.npj health systems · 2026Article
- Establishment of a large-scale oral disease registry (NDCS-ODR) in a national specialty center.PloS one · 2026Article
- Strengthening inferential studies in the FDA Sentinel initiative: results from a methodological demonstration project.NPJ digital medicine · 2025Article
- Development and Application of an Algorithm for Statin-Induced Myopathy Based on Electronic Health Record-Derived Structured Elements.Pharmacoepidemiology and drug safety · 2025Article
- A real-world data challenge: guidance for aligning data privacy compliance and fit-for-purpose usability.Health affairs scholar · 2025Article
- Diagnosis and coding of opioid misuse: a systematic scoping review and implementation framework.Pain medicine (Malden, Mass.) · 2025Article
- Multidisciplinary DRG management for rational medication in obstetrics: a cost analysis in Zhejiang Province.BMC health services research · 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
3 authors.
Funding
Abstract
Electronic health record (EHR) data are seen as an important source for pharmacoepidemiology studies. In the US health-care system, EHR systems often identify only fragments of patients' health information across the care continuum, including primary care, specialist care, hospitalizations, and pharmacy dispensing. This leads to unobservable information in longitudinal evaluations of medication effects, causing unmeasured confounding, misclassification, and truncated follow-up times. A remedy is to link EHR data with longitudinal health insurance claims data, which record all encounters during a defined enrollment period across all care settings. Here we evaluate EHR and claims data sources in 3 aspects relevant to etiological studies of medical products: data continuity, data granularity, and data chronology. Reflecting on the strengths and limitations of EHR and insurance claims data, it becomes obvious that they complement each other. The combination of both will improve the validity of etiological studies and expand the range of questions that can be answered. As the research community transitions towards a future state with access to large-scale combined EHR + claims data, we outline analytical templates to improve the validity and broaden the scope of pharmacoepidemiology studies in the current environment where EHR data are available only for a subset of patients with claims data. This article is part of a Special Collection on Pharmacoepidemiology.
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What Socratic 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 Socratic graph.