ReviewExpert review of clinical immunology2015
Intelligent use and clinical benefits of electronic health records in rheumatoid arthritis.
Review in Expert review of clinical immunology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 17 citations in OpenAlex.
- Rapid identification and phenotyping of nonalcoholic fatty liver disease patients using a machine-based approach in diverse healthcare systems.Clinical and translational science · 2025Article
- Management of Rheumatoid Arthritis in Primary Care: A Scoping Review.International journal of environmental research and public health · 2024Article
- Weakly Semi-supervised phenotyping using Electronic Health records.Journal of biomedical informatics · 2022Article
- The medical cyborg concept.EMBnet.journal · 2022Article
- Leveraging unstructured data to identify hereditary angioedema patients in electronic medical records.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2021Article
- Impact of Diverse Data Sources on Computational Phenotyping.Frontiers in genetics · 2020Article
- The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype.Genetic epidemiology · 2019Article
- Article
- Flexible, cluster-based analysis of the electronic medical record of sepsis with composite mixture models.Journal of biomedical informatics · 2018Article
- Learning statistical models of phenotypes using noisy labeled training data.Journal of the American Medical Informatics Association : JAMIA · 2016Article
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 at 1 institution in 1 country.
Funding
Abstract
In the past 10 years, electronic health records (EHRs) have had growing impact in clinical care. EHRs efficiently capture and reuse clinical information, which can directly benefit patient care by guiding treatments and providing effective reminders for best practices. The increased adoption has also lead to more complex implementations, including robust, disease-specific tools, such as for rheumatoid arthritis (RA). In addition, the data collected through normal clinical care is also used in secondary research, helping to refine patient treatment for the future. Although few studies have directly demonstrated benefits for direct clinical care of RA, the opposite is true for EHR-based research - RA has been a particularly fertile ground for clinical and genomic research that have leveraged typically advanced informatics methods to accurately define RA populations. We discuss the clinical impact of EHRs in RA treatment and their impact on secondary research, and provide recommendations for improved utility in future EHR installations.
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.