Improving Detection of Fetuses at Risk – Who Needs Systematic Training?

Overview

Detection of growth restricted fetuses relies primarily on abdominal ultrasound examinations during pregnancy. Many clinicians, however, have not received systematic training and may therefore perform inadequately. We wish to examine, whether systematic, simulation-based training can improve diagnostic accuracy of estimated fetal weight by ultrasound at different levels of clinical experience.

Full Title of Study: “Improving Detection of Fetuses at Risk – Who Needs Systematic Training?”

Study Type

  • Study Type: Interventional
  • Study Design
    • Allocation: Randomized
    • Intervention Model: Parallel Assignment
    • Primary Purpose: Other
    • Masking: None (Open Label)
  • Study Primary Completion Date: March 1, 2018

Detailed Description

Participants are physicians working at obstetric departments. Participant characteristics (age, experience in years and number of monthly scans) are recorded. Participants perform two abdominal growth scans prior to randomization and estimated fetal weight is compared to birth weight. Mean absolute percentage error is calculated as a measure of diagnostic accuracy. Participants are then randomized to either control (no intervention) or intervention. The latter group receives training on the Metaphor Scantrainer trans abdominal ultrasound simulator until they pass a previously validated test. After completing the training the participants use a mannikin to practice systematic approach and 'knobology'. All participants then perform another two growth scans. Diagnostic accuracy before and after the intervention or control period is compared. We wish to examine the effect of systematic training on the diagnostic accuracy of estimated fetal weight by ultrasound across different levels of clinical experience. If an effect can be found in the inexperienced participants, simulation-based training in obstetric ultrasound could be implemented as a part of basic obstetric training and/or as a means of maintaining skills.

Interventions

  • Other: simulation-based training
    • As described under group descriptions

Arms, Groups and Cohorts

  • Experimental: Intervention
    • Simulation-based training: Virtual-reality simulation training on the Medaphor Scantrainer Transabdominal Simulator until expert level is reached. Then training on a physical mannikin until an average OSAUS-score of 3 or more is attained.
  • No Intervention: Control
    • No intervention.

Clinical Trial Outcome Measures

Primary Measures

  • Diagnostic accuracy of estimated fetal weight by ultrasound.
    • Time Frame: 1 month
    • percentage error of fell weight estimate compared to actual fetal weight

Secondary Measures

  • Ratings of ultrasound images
    • Time Frame: 1 month
    • Images are rated using the image-scoring method by Salomon et al. (Salomon et al. Feasibility and reproducibility of an image-scoring method for quality control of fetal biometry in the second trimester. Ultrasound Obstet Gynecol 2006;27;34-40) The images are scores on the number of landmarks, correct caliper placement and image optimization. A minimum of 0 and a maximum of 16 points can be given (best possible score).

Participating in This Clinical Trial

Inclusion Criteria

  • proficiency in the Danish language – no prior experience with obstetric ultrasound simulation – doctors who work within the field of gynecology and obstetrics Exclusion Criteria:

  • lack of proficiency in the Danish language – prior experience with obstetric ultrasound simulation

Gender Eligibility: All

Minimum Age: N/A

Maximum Age: N/A

Are Healthy Volunteers Accepted: Accepts Healthy Volunteers

Investigator Details

  • Lead Sponsor
    • Copenhagen Academy for Medical Education and Simulation
  • Provider of Information About this Clinical Study
    • Principal Investigator: Lisbeth Andreasen, MD – Copenhagen Academy for Medical Education and Simulation
  • Overall Official(s)
    • Ann Tabor, DMSc, Study Director, Copenhagen University Hospital at Herlev

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