ArticleLearning health systems2023
Evolving a national clinical trials learning health system.
Article in Learning health systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Diverse Recruitment for Clinical Trials Using Three Diversity-Enhancing Interventions: Qualitative Study.JMIR formative research · 2026Article
- Evaluating health organization readiness for implementing a learning health system: a scoping review.Health research policy and systems · 2025Article
- Evaluating adoption and reach in a pragmatic randomized trial of community paramedicine for intermediate acuity patient care.Journal of clinical and translational science · 2024Article
- Evolving a national clinical trials learning health system.Learning health systems · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Clinical trials generate key evidence to inform decision making, and also benefit participants directly. However, clinical trials frequently fail, often struggle to enroll participants, and are expensive. Part of the problem with trial conduct may be the disconnected nature of clinical trials, preventing rapid data sharing, generation of insights and targeted improvement interventions, and identification of knowledge gaps. In other areas of healthcare, a learning health system (LHS) has been proposed as a model to facilitate continuous learning and improvement. We propose that an LHS approach could greatly benefit clinical trials, allowing for continuous improvements to trial conduct and efficiency. A robust trial data sharing system, continuous analysis of trial enrollment and other success metrics, and development of targeted trial improvement interventions are potentially key components of a Trials LHS reflecting the learning cycle and allowing for continuous trial improvement. Through the development and use of a Trials LHS, clinical trials could be treated as a system, producing benefits to patients, advancing care, and decreasing costs for stakeholders.
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.