Evidence map›Paper›PMID 29350246›Full record

ArticlePediatric cardiology2018

Data-Driven Quality Improvement Project to Increase the Value of the Congenital Echocardiographic Report.

Pei-Ni Jone, Ruthanne Gould, Cindy Barrett, Adel K Younoszai, Brian Fonseca

Abstract read
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In one paragraph

Article in Pediatric cardiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Clinical workflow of sonographers performing fetal anomaly ultrasound scans: deep-learning-based analysis.Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2022
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Pei-Ni JonePediatric Cardiology, Children's Hospital Colorado, University of Colorado School of Medicine, 13123 East 16th Avenue, B100, Aurora, CO, 80045, USA. pei-ni.jone@childrenscolorado.org.
Ruthanne GouldPediatric Cardiology, Children's Hospital Colorado, University of Colorado School of Medicine, 13123 East 16th Avenue, B100, Aurora, CO, 80045, USA.
Cindy BarrettPediatric Cardiology, Children's Hospital Colorado, University of Colorado School of Medicine, 13123 East 16th Avenue, B100, Aurora, CO, 80045, USA.
Adel K YounoszaiPediatric Cardiology, Children's Hospital Colorado, University of Colorado School of Medicine, 13123 East 16th Avenue, B100, Aurora, CO, 80045, USA.
Brian FonsecaPediatric Cardiology, Children's Hospital Colorado, University of Colorado School of Medicine, 13123 East 16th Avenue, B100, Aurora, CO, 80045, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Echocardiography is the primary diagnostic modality for congenital heart disease patients. The written report is used to communicate with the care team and organization is often divided into the body with detailed findings and the conclusions with important findings summarized. Strategies to increase workflow efficiency include batch writing of reports after performance of multiple echocardiograms and the use of report templates which may contribute to discrepancies within report leading to potential downstream medical errors. The aim of this project was to measure the rate of inconsistencies in the echocardiogram reports and through an iterative series of process improvement decrease this rate while maintaining sonographer efficiency and diagnostic accuracy. The discrepancy rate, diagnostic error rate, and sonographer productivity were collected one-year prior and during the iterative quality improvement process. The primary outcome and discrepancies in reports were determined by two reviewers: an experienced pediatric echocardiographic cardiologist and a senior sonographer. Minor discrepancies were defined as contradictions between the body and the conclusion of the report that were unlikely to affect patient care. Major discrepancies were defined as discrepancies between the body and the conclusion that had significant potential to affect patient care. Sonographer productivity was measured as studies per sonographer per month. Our primary intervention was to initiate a quarterly QI meeting and to decrease the batch writing of preliminary echocardiogram reports. No major discrepancies were identified pre- or post-intervention. The minor discrepancies decreased from 40.7 to 6%. Sonographer productivity was not significantly changed with a slight increase from 100 studies/sonographer/month during the baseline to 101 studies/sonographer/month during the intervention. There was no change in major or minor diagnostic error rate. Our quality improvement intervention increased the value of our reports by significantly decreasing minor discrepancies without negatively impacting sonographer productivity or diagnostic accuracy.

Indexed as

Quality ImprovementClinical CompetenceDiagnostic ErrorsEchocardiographyHeart Defects, CongenitalHumansPilot ProjectsQuality of Health CareEchocardiographyEfficiencyQuality improvementQuality intervention

Identifiers

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Registered trials

None linked

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.