ArticleBMC neurology2019
The protocol-guided rapid evaluation of veterans experiencing new transient neurological symptoms (PREVENT) quality improvement program: rationale and methods.
Article in BMC neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02769338 (Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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.
Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) (QUE 15-280)
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.
- Methods used to design audit and feedback interventions to change clinical practice: a scoping review.Frontiers in health services · 2026Pooled it
- Identifying transient ischemic attack (TIA) patients at high-risk of adverse outcomes: development and validation of an approach using electronic health record data.BMC neurology · 2022Trial
- Acceptability of a complex team-based quality improvement intervention for transient ischemic attack: a mixed-methods study.BMC health services research · 2021Trial
- Seeding Structures for a Community of Practice Focused on Transient Ischemic Attack (TIA): Implementing Across Disciplines and Waves.Journal of general internal medicine · 2021Trial
- Implementation Evaluation of a Complex Intervention to Improve Timeliness of Care for Veterans with Transient Ischemic Attack.Journal of general internal medicine · 2021Trial
- Using a "Kickoff" to build implementation partner teams and action plans for active implementation of a quality improvement project.Frontiers in health services · 2025Article
- Real-world analysis of two ischaemic stroke and TIA systolic blood pressure goals on 12-month mortality and recurrent vascular events.Stroke and vascular neurology · 2024Article
- Review
- Conceptualizing learning health systems: A mapping review.Learning health systems · 2023Article
- The Perils of a "My Work Here is Done" perspective: a mixed methods evaluation of sustainment of an evidence-based intervention for transient ischemic attack.BMC health services research · 2022Article
- Observational
- Quality of Care and Outcomes for Patients with Acute Ischemic Stroke and Transient Ischemic Attack During the COVID-19 Pandemic.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2022Article
- Implementation Science to Improve Quality of Neurological Care.Pediatric neurology · 2021Review
- Multi-tiered external facilitation: the role of feedback loops and tailored interventions in supporting change in a stepped-wedge implementation trial.Implementation science communications · 2021Article
- Article
- Empowering Implementation Teams with a Learning Health System Approach: Leveraging Data to Improve Quality of Care for Transient Ischemic Attack.Journal of general internal medicine · 2020Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 6 institutions in 1 country.
Funding
Abstract
backgroundTransient ischemic attack (TIA) patients are at high risk of recurrent vascular events; timely management can reduce that risk by 70%. The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurological Symptoms (PREVENT) developed, implemented, and evaluated a TIA quality improvement (QI) intervention aligned with Learning Healthcare System principles.
methodsThis stepped-wedge trial developed, implemented and evaluated a provider-facing, multi-component intervention to improve TIA care at six facilities. The unit of analysis was the medical center. The intervention was developed based on benchmarking data, staff interviews, literature, and electronic quality measures and included: performance data, clinical protocols, professional education, electronic health record tools, and QI support. The effectiveness outcome was the without-fail rate: the proportion of patients who receive all processes of care for which they are eligible among seven processes. The implementation outcomes were the number of implementation activities completed and final team organization level. The intervention effects on the without-fail rate were analyzed using generalized mixed-effects models with multilevel hierarchical random effects. Mixed methods were used to assess implementation, user satisfaction, and sustainability. DISCUSSION: PREVENT advanced three aspects of a Learning Healthcare System. Learning from Data: teams examined and interacted with their performance data to explore hypotheses, plan QI activities, and evaluate change over time. Learning from Each Other: Teams participated in monthly virtual collaborative calls. Sharing Best Practices: Teams shared tools and best practices. The approach used to design and implement PREVENT may be generalizable to other clinical conditions where time-sensitive care spans clinical settings and medical disciplines.
trial registrationclinicaltrials.gov: NCT02769338 [May 11, 2016].
Indexed as
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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.