Trial reportJournal of clinical anesthesia2021
Visualization of aggregate perioperative data improves anesthesia case planning: A randomized, cross-over trial.
Trial report in Journal of clinical anesthesia, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Visual communication of public health data: a scoping review.Frontiers in digital health · 2025Pooled it
- A Web-Based Reporting System for Reviewing Local Practice Patterns of Anesthesiologists Derived from the Electronic Medical Record.Journal of medical systems · 2023Article
- Visualizing Opioid-Use Variation in a Pediatric Perioperative Dashboard.Applied clinical informatics · 2022Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
STUDY
objectiveA challenge in reducing unwanted care variation is effectively managing the wide variety of performed surgical procedures. While an organization may perform thousands of types of cases, privacy and logistical constraints prevent review of previous cases to learn about prior practices. To bridge this gap, we developed a system for extracting key data from anesthesia records. Our objective was to determine whether usage of the system would improve case planning performance for anesthesia residents.
designRandomized, cross-over trial.
settingVanderbilt University Medical Center. MEASUREMENTS: We developed a web-based, data visualization tool for reviewing de-identified anesthesia records. First year anesthesia residents were recruited and performed simulated case planning tasks (e.g., selecting an anesthetic type) across six case scenarios using a randomized, cross-over design after a baseline assessment. An algorithm scored case planning performance based on care components selected by residents occurring frequently among prior anesthetics, which was scored on a 0-4 point scale. Linear mixed effects regression quantified the tool effect on the average performance score, adjusting for potential confounders. MAIN
resultsWe analyzed 516 survey questionnaires from 19 residents. The mean performance score was 2.55 ± SD 0.32. Utilization of the tool was associated with an average score improvement of 0.120 points (95% CI 0.060 to 0.179; p < 0.001). Additionally, a 0.055 point improvement due to the "learning effect" was observed from each assessment to the next (95% CI 0.034 to 0.077; p < 0.001). Assessment score was also significantly associated with specific case scenarios (p < 0.001).
conclusionsThis study demonstrated the feasibility of developing of a clinical data visualization system that aggregated key anesthetic information and found that the usage of tools modestly improved residents' performance in simulated case planning.
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Registered trials
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