ArticleEuropean clinical respiratory journal2017
Use of electronic medical records and biomarkers to manage risk and resource efficiencies.
Article in European clinical respiratory journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Machine learning prediction of CKD progression in hyperglycemic elderly adults: a prospective community cohort study.Renal failure · 2026Article
- Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.NPJ primary care respiratory medicine · 2025Article
- Health system characteristics and evidence-based asthma care.Frontiers in allergy · 2025Article
- Optimising the use of electronic medical records for large scale research in psychiatry.Translational psychiatry · 2024Review
- Primary care risk stratification in COPD using routinely collected data: a secondary data analysis.NPJ primary care respiratory medicine · 2019Article
- Defining severe obstructive lung disease in the biologic era: an endotype-based approach.The European respiratory journal · 2019Review
- Personalized medicine for patients with COPD: where are we?International journal of chronic obstructive pulmonary disease · 2019Review
- Asthma Across Age: Insights From Primary Care.Frontiers in pediatrics · 2019Review
- E-Variance: An Application to Assure Clinical Data Integrity and Improve Patient Safety and Workflows in Electronic Medical Records.Healthcare technology lettersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The migration from paper to electronic medical records (EMRs) was motivated by the administrative need to record, retrieve and process increasing amounts of clinical data in the 1980s. In the intervening period, there has been growing recognition of the potential of such records for achieving care efficiencies, informing clinical decision making and real-life research. EMRs can be used to characterise patient groups, management approaches and differential outcomes. Characterisation can also help with identification of potential biomarkers for future risk determination and likely treatment response. The future heralds even greater opportunities through integration of clinical records and a range of technology-based solutions within a more complete electronic health record (EHR). Through application of algorithms based on identified risk predictors and disease determinants, clinical records could also be used to enable risk stratification of patients to optimise targeted interventions, conserving resources to achieve individual patient and system-wide benefit. In this review, we reflect on the evolution of the EMR and EHR and discuss current and emerging opportunities, particularly with respect to biomarkers and targeting of innovative biologic interventions. We also consider some of the critical issues associated with realising the potential of the EHR as a clinical aid and research tool in an age of emerging technologies..
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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.