ArticleJournal of healthcare informatics research2024
Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview.
Article in Journal of healthcare informatics research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The association between posttraumatic stress disorder and migraine: A systematic review.Headache · 2026Pooled it
- Silent Pain or Silent Records? Pain Visibility, Documentation Ethics, and Nursing Management in Neurocritical Care.Nursing philosophy : an international journal for healthcare professionals · 2026Article
- Maternal Health Outcomes Associated With Syphilis Infection During Pregnancy: Evidence From a Large US All-Payer Hospital-Centered Administrative Database.Open forum infectious diseases · 2026Article
- Computable Phenotype for Identifying Undiagnosed Hypermobile Ehlers-Danlos Syndrome: Protocol for a Development and Validation Study.JMIR research protocols · 2026Article
- AI-based multimodal integration of genomics and electronic health records.Nature reviews. Genetics · 2026Review
- Race and Ethnicity Data in the Electronic Health Records: New Insights Through Comparison with American Community Survey Microdata.Journal of racial and ethnic health disparities · 2026Article
- Bias and Fairness Across the Healthcare AI Lifecycle: A Clinician-Oriented Review.Balkan medical journal · 2026Review
- Comparative Real-World Effectiveness of Fixed-Dose Triple Therapy Regimens in COPD: A Retrospective Cohort Study.Journal of clinical medicine · 2026Article
- Childhood Sexual Abuse and Long-Term Risk of Self-Harm, Overdose, and Cardiovascular Disease.medRxiv : the preprint server for health sciences · 2026Article
- Are Traditional Registries Becoming Obsolete in the Modern Digital Health Ecosystem?Journal of medical Internet research · 2026Article
- Cure or coincidence? The need for long-term rigor in pediatric arteriovenous malformation radiosurgery.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2026Article
- Approaches to Collect Comprehensive Electronic Patient Data Across Multiple Providers and Payers for Research: Landscape Analysis.Journal of medical Internet research · 2026Article
- How representative are electronic health records? A record linkage study using individual-level census data.Social science & medicine (1982) · 2026Article
- Follow the data: tracking data quality and completeness in oncology real-world data.JAMIA open · 2026Article
- Defining Prenatal Care Surveillance Metrics Using Electronic Health Record Data.JAMA health forum · 2026Article
- Accuracy of administrative data in ascertaining health conditions: a systematic review.JAMIA open · 2026Review
- Understanding Remission of Long-Term Conditions Through Electronic Health Records: Scoping Review.Journal of medical Internet research · 2026Article
- It's Time to Rethink 'Real-World Evidence': A Call for Terminological Clarity in Health Technology Assessment.Applied health economics and health policy · 2026Article
- Age- and Sex-Dependent Interpretation of C-Reactive Protein Cutoffs: A Sixteen-Year Large-Scale Clinical Laboratory Data Analysis.Diagnostics (Basel, Switzerland) · 2026Article
- Beyond Rurality: Individual Socioeconomic Status and Chronic Disease Prevalence.medRxiv : the preprint server for health sciences · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Electronic Health Records (EHR) are increasingly being perceived as a unique source of data for clinical research as they provide unprecedentedly large volumes of real-time data from real-world settings. In this review of the secondary uses of EHR, we identify the anticipated breadth of opportunities, pointing out the data deficiencies and potential biases that are likely to limit the search for true causal relationships. This paper provides a comprehensive overview of the types of biases that arise along the pathways that generate real-world evidence and the sources of these biases. We distinguish between two levels in the production of EHR data where biases are likely to arise: (i) at the healthcare system level, where the principal source of bias resides in access to, and provision of, medical care, and in the acquisition and documentation of medical and administrative data; and (ii) at the research level, where biases arise from the processes of extracting, analyzing, and interpreting these data. Due to the plethora of biases, mainly in the form of selection and information bias, we conclude with advising extreme caution about making causal inferences based on secondary uses of EHRs.
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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.