ArticleClinical trials (London, England)2025
Use of Epic
Article in Clinical trials (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Article
- Commentary on Toerper et al: A step in the right direction for learning health systems.Clinical trials (London, England) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
backgroundPragmatic clinical trials are critical to determine the real-world effectiveness of interventions. Emergency departments serve as key clinical sites for such trials because they provide care to large numbers of patients at the earliest point in their hospital encounter. However, few methods that facilitate efficient emergency department-based pragmatic trials have been described. Our objective was to design and embed randomization schemes directly into the electronic health record to facilitate enrollment of emergency department patients by clinical staff 24 h per day, while maintaining concealed and balanced allocation.
methodsWe designed two multi-center pragmatic trials screening for human immunodeficiency virus (HIV TESTED trial) and hepatitis C virus (DETECT Hep C trial). HIV TESTED included four sites, three arms, and compared two forms of risk-assessed (targeted) to non-risk-assessed (nontargeted) screening for human immunodeficiency virus; DETECT Hep C included three sites, two arms, and compared targeted to nontargeted screening for hepatitis C virus. Participant entry occurred during a patient's emergency department visit in conjunction with standard emergency department care. Patient-visit level randomization schemes were designed in each electronic health record system using Epic
resultsDuring 61 cumulative enrollment months, 365,462 patient visits occurred. After excluding 184,023 visits by designed electronic health record logic or manual nurse input due to age, previously known human immunodeficiency virus or hepatitis C virus, high acuity or altered mental status, 181,439 patient visits were randomized to one of the interventions. Absolute differences between targeted and nontargeted arms differed by 0.2% and 0.4% (HIV TESTED), and 0.1% (DETECT Hep C), and median absolute differences across all baseline characteristics (i.e. age, sex, race, ethnicity, language, payor, arrival mode, and acuity) between arms were 0.02% (range: -0.7% to +0.5%) and -0.07% (range: -0.3% to +0.7%), and -0.02% (range: -0.7% to +0.7%), respectively. Median time required for nurses to execute randomization ranged from 16 to 67 s, depending on the arm.
conclusionIntegration of blinded randomization schemes into electronic health record systems resulted in high-volume balanced enrollment of participants 24 h per day while maintaining concealed allocation. Use of this technology is an important tool to scale performance of high-quality pragmatic trials in emergency department settings while minimizing bias.
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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.