ReviewBMC medical research methodology2021
A narrative review on the validity of electronic health record-based research in epidemiology.
Review in BMC medical research methodology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 105 papers, 3 of them syntheses 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
105 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Prediction models for self-harm and suicide: a systematic review and critical appraisal.BMC medicine · 2025Pooled it
- Association between prediabetes and thyroid cancer risk: A meta-analysis.Biomolecules & biomedicine · 2025Pooled it
- Cross-Phenotype Genome-Wide Association Study on the Shared Genetic Susceptibility to Systemic Sclerosis and Primary Biliary Cholangitis.Arthritis & rheumatology (Hoboken, N.J.) · 2025Pooled it
- Perioperative Systemic Analgesia in Patients With Inflammatory Skin Disease: A Matched Cohort Study.Cureus · 2026Article
- Strengths and Limitations of All of Us Data Use for Public Health Research.American journal of public health · 2026Article
- Leveraging Data Science for Conducting Observational Studies: Highlighting Advantages and Limitations Throughout the Evaluation of a Use Case.Mayo Clinic proceedings. Digital health · 2026Article
- A Descriptive Analysis of Morbidity Patterns Among Insured Pet Cats in China Based on Insurance Claims.Veterinary sciences · 2026Article
- Computable Phenotype for Identifying Undiagnosed Hypermobile Ehlers-Danlos Syndrome: Protocol for a Development and Validation Study.JMIR research protocols · 2026Article
- Testosterone Replacement Therapy in Posterior Lumbar Fusion Patients: A Propensity Score-Matched Analysis of Long-Term Outcomes.Global spine journal · 2026Article
- Challenges in Identifying Heart Failure Diagnoses from the Electronic Health Record.Journal of cardiac failure - intersections · 2026Article
- Mitigating bias in the analysis and inferences from using longitudinal EHR data in disease outcomes research.BMC medical research methodology · 2026Article
- Development of Longitudinal, Linked Maternal-Infant Cohorts using the Epic Cosmos Electronic Health Record Dataset.medRxiv : the preprint server for health sciences · 2026Article
- Cardiovascular-Kidney-Metabolic Syndrome: Development of anJMIR diabetes · 2026Article
- Age and sex affect the prevalence and severity of periodontal conditions in an academic setting.Journal of periodontology · 2026Article
- Rural-Urban Differences in Hypertension Prevalence and Control in a Large Regional Health System Cohort.Journal of clinical medicine · 2026Article
- Exploring Technological Solutions for Interoperability Between Patient Electronic Medical Records and Clinical Registries: Scoping Review.Journal of medical Internet research · 2026Article
- Analytic Choices Shape Genomic Risk Estimates from Electronic Health Records: Coronary Heart Disease in eMERGE IV.medRxiv : the preprint server for health sciences · 2026Article
- A comparative analysis estimating aspergillosis and histoplasmosis encounters among inpatients in the United States using multi-regional electronic health record and National Discharge Data, 2014-2020.AJE advances : research in epidemiology · 2026Article
- Rising obesity and shifting disease patterns in Saudi Arabia: a nine-year population-based analysis of chronic disease burden and multimorbidity profiles.BMC public health · 2026Article
- Population differences in wearable device wear time: Rescuing data to address biases and advance health equity.medRxiv : the preprint server for health sciences · 2026Article
45 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Electronic health records (EHRs) are widely used in epidemiological research, but the validity of the results is dependent upon the assumptions made about the healthcare system, the patient, and the provider. In this review, we identify four overarching challenges in using EHR-based data for epidemiological analysis, with a particular emphasis on threats to validity. These challenges include representativeness of the EHR to a target population, the availability and interpretability of clinical and non-clinical data, and missing data at both the variable and observation levels. Each challenge reveals layers of assumptions that the epidemiologist is required to make, from the point of patient entry into the healthcare system, to the provider documenting the results of the clinical exam and follow-up of the patient longitudinally; all with the potential to bias the results of analysis of these data. Understanding the extent of as well as remediating potential biases requires a variety of methodological approaches, from traditional sensitivity analyses and validation studies, to newer techniques such as natural language processing. Beyond methods to address these challenges, it will remain crucial for epidemiologists to engage with clinicians and informaticians at their institutions to ensure data quality and accessibility by forming multidisciplinary teams around specific research projects.
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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.