ReviewJournal of cardiovascular translational research2014
The electronic health record for translational research.
Review in Journal of cardiovascular translational research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Sharing EHR data of patients with rare diseases for research - The role of quality assessments in a national federated research data infrastructure.BMC medical informatics and decision making · 2026Article
- Developing a Semantically Based Query Recommendation for an Electronic Medical Record Search Engine: Query Log Analysis and Design Implications.JMIR formative research · 2023Article
- Rare Diseases in Hospital Information Systems-An Interoperable Methodology for Distributed Data Quality Assessments.Methods of information in medicine · 2023Article
- Cross fertilisation of Public Health and Translational Research.Journal of the Indian Institute of Science · 2022Review
- Leveraging medical context to recommend semantically similar terms for chart reviews.BMC medical informatics and decision making · 2021Article
- Natural Language Mapping of Electrocardiogram Interpretations to a Standardized Ontology.Methods of information in medicine · 2021Article
- Salience of Medical Concepts of Inside Clinical Texts and Outside Medical Records for Referred Cardiovascular Patients.Journal of healthcare informatics research · 2019Article
- HiGHmed - An Open Platform Approach to Enhance Care and Research across Institutional Boundaries.Methods of information in medicine · 2018Article
- Extracting similar terms from multiple EMR-based semantic embeddings to support chart reviews.Journal of biomedical informatics · 2018Article
- Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records.BMC medical informatics and decision making · 2018Article
- A multi-site cognitive task analysis for biomedical query mediation.International journal of medical informatics · 2016Article
- Improvement in Cardiovascular Risk Prediction with Electronic Health Records.Journal of cardiovascular translational research · 2016Article
- Merging Electronic Health Record Data and Genomics for Cardiovascular Research: A Science Advisory From the American Heart Association.Circulation. Cardiovascular genetics · 2016Article
- Linking Genes to Cardiovascular Diseases: Gene Action and Gene-Environment Interactions.Journal of cardiovascular translational research · 2015Review
- Review and Updates in Regenerative and Personalized Medicine, Preclinical Animal Models, and Clinical Care in Cardiovascular Medicine.Journal of cardiovascular translational research · 2015Review
- A Modular Architecture for Electronic Health Record-Driven Phenotyping.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
- Left ventricular noncompaction: a distinct cardiomyopathy or a trait shared by different cardiac diseases?Journal of the American College of Cardiology · 2014Review
- Natural language processing algorithms identify wild-type isocitrate dehydrogenase gliomas in electronic health records.Neuro-oncology advancesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
With growing adoption and use, the electronic health record (EHR) represents a rich source of clinical data that also offers many benefits for secondary use in biomedical research. Such benefits include access to a more comprehensive medical history, cost reductions, and increased efficiency in conducting research, as well as opportunities to evaluate new and expanded populations for sufficient statistical power. Existing work utilizing EHR data has uncovered some complexities and considerations for their use but, more importantly, has also generated practical lessons and solutions. Given an understanding of EHR data use in cardiovascular research, expanded adoption of this data source offers great potential to further transform the research landscape.
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.