ReviewAnnals of internal medicine2020
Research and Reporting Considerations for Observational Studies Using Electronic Health Record Data.
Review in Annals of internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 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
49 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial.Implementation science : IS · 2020Trial
- AI-Assisted Literature Mining Reveals Spatiotemporal Heterogeneity and Progression Trajectories of Traditional Chinese Medicine Syndromes in Coronary Heart Disease in China.Journal of evidence-based medicine · 2026Article
- Assessment of Electronic Clinical Monitoring Systems in the Pediatric Intensive Care Unit: Prospective Concordance Study.JMIR formative research · 2026Article
- Assessment of real-world evidence research competencies in federated research networks: a maternal health fellowship program evaluation.JAMIA open · 2026Article
- Cardiovascular-Kidney-Metabolic Syndrome: Development of anJMIR diabetes · 2026Article
- Evolving language of pediatric anxiety in electronic health records.JAMIA open · 2026Article
- Real-world evidence from Germany: representativeness analysis and mortality endpoint validation in electronic health record-derived oncology cohorts.BMC cancer · 2026Article
- Integrating Misclassified EHR Outcomes With Validated Outcomes From a Non-Probability Sample.Statistics in medicine · 2025Article
- Dynamic Prediction and Intervention of Serum Sodium in Patients with Stroke Based on Attention Mechanism Model.Journal of healthcare informatics research · 2025Article
- Beyond Phecodes: leveraging PheMAP to identify patients lacking diagnosis codes in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- An automation framework for clinical codelist development validated with UK data from patients with multiple long-term conditions.BMC medical research methodology · 2025Article
- Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.NPJ primary care respiratory medicine · 2025Article
- A scoping review of OMOP CDM adoption for cancer research using real world data.NPJ digital medicine · 2025Article
- Clinical entity augmented retrieval for clinical information extraction.NPJ digital medicine · 2025Article
- Building a collaborative ecosystem across the IDeA-CTR networks in response to a public health emergency.Journal of clinical and translational science · 2025Article
- A Standardized Guideline for Assessing Extracted Electronic Health Records Cohorts: A Scoping Review.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- Analyzing missingness patterns in real-world data using the SMDI toolkit: application to a linked EHR-claims pharmacoepidemiology study.BMC medical research methodology · 2024Article
- A Common Longitudinal Intensive Care Unit data Format (CLIF) to enable multi-institutional federated critical illness research.medRxiv : the preprint server for health sciences · 2024Article
- CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks.Journal of healthcare informatics research · 2024Article
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 records (EHRs) are an increasingly important source of real-world health care data for observational research. Analyses of data collected for purposes other than research require careful consideration of data quality as well as the general research and reporting principles relevant to observational studies. The core principles for observational research in general also apply to observational research using EHR data, and these are well addressed in prior literature and guidelines. This article provides additional recommendations for EHR-based research. Considerations unique to EHR-based studies include assessment of the accuracy of computer-executable cohort definitions that can incorporate unstructured data from clinical notes and management of data challenges, such as irregular sampling, missingness, and variation across time and place. Principled application of existing research and reporting guidelines alongside these additional considerations will improve the quality of EHR-based observational studies.
Indexed as
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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.