Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial

Suha Jaudi; Louise Chevalier; Nicolas Fries; Alain Daher; Sophie Tezenas du Montcel; Marc Dommergues

doi:doi:10.11648/j.edu.20190805.17

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Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial

Suha Jaudi, Louise Chevalier, Nicolas Fries, Alain Daher, Sophie Tezenas du Montcel, Marc Dommergues

Published in Education Journal (Volume 8, Issue 5)

Received: 30 May 2019 Accepted: 13 August 2019 Published: 5 September 2019

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Abstract

Continuing medical education in the field of fetal ultrasound imaging is based on expert audit of still images, a time consuming approach. Our objective was to determine if self-evaluation of the images a professional produced is as effective as audit and feedback by an expert as a method of continuous medical education. We designed a prospective blinded randomized controlled trial. 321 ultrasonographers uploaded on a continuous medical education website a first set of 30 biometry images (10 cephalic, 10 abdominal and 10 femoral) from 10 consecutive second or third trimester normal screening scans. In arm 1: participants (N = 151) assessed their own images online according to a standardized procedure, and received feedback with detailed recommendations for change, automatically generated based on their assessment. The images were also audited by an expert, but participants remained blinded to the expert’s rating. In arm 2: participants (N = 177) had their images assessed by an expert and received a feedback, formatted as in arm 1, automatically generated based on the expert’s assessment Three to 6 months later, participants uploaded a second set of images, audited by an expert. A total of 19,680 images were audited. In the self-assessment group, the percentage of images meeting all criteria (IMAC) rose from 55 to 62.2 (p < 0.0001). In the expert-assessment and feedback group, the percentage of IMAC rose from 54.2 to 59.1 (p < 0.0001). Improvement in image quality was equivalent in both groups with a difference in IMAC increase of 2.3 percentage points (95%CI: -1.7 to + 6.4). In conclusion, online training based on self-assessment of fetal ultrasound images was as effective as expert audit and feedback. NCT02074592.

Published in	Education Journal (Volume 8, Issue 5)
DOI	10.11648/j.edu.20190805.17
Page(s)	226-231
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Continuing Medical Education, Online Audit and Feedback, Ultrasound Image Quality, Fetal Biometry, Self-training, Fetal Ultrasound Screening, Quality Assurance

References

[1]	Ivers N, Jamtvedt G, Flottorp S, Young JM, Odgaard-Jensen J, French SD, O'Brien MA, Johansen M, Grimshaw J, Oxman AD. (2012) Audit and feedback: effects on professional practice and healthcare outcomes. Cochrane Database Syst Rev. 2; 6. Art. No: CD000259.
[2]	AIUM. org: AIUM Ultrasound Practice Accreditation. http://www.aium.org/accreditation/accreditation.aspx [04/08/2019].
[3]	Fetalmedicine.com: The Fetal Medicine Foundation Training & Certification http://www.fetalmedicine.com/fmf/training-certification/certificates-of-competence/ [05/05/2017].
[4]	CFEF. org: Collège Français d’Echographie Foetale F. M. C. E. P. P. https://www.epp-echofoetale.fr/ [04/08/2019].
[5]	SFAPE.com: Société Française pour l’Amélioration des Pratiques Echographiques 2ème trimestre/3ème trimestre Analyse d’images. http://www.sfape.com/ [04/08/2019].
[6]	Heidi Andrade & Anna Valtcheva (2009) Promoting Learning and Achievement Through Self-Assessment, Theory Into Practice, 48: 1, 12-19.
[7]	Salomon L. J., Alfirevic Z, Berghella V, BilardoC,. Hernandez-Andrade E, Johnsen S. L., Kalache K., Leung K.-Y., Malinger G., Munoz H., Prefumo F,. Toi A and. Lee W on behalf of the ISUOG. Clinical Standards Committee Practice guidelines for performance of the routine mid-trimester fetal ultrasound scan Ultrasound Obstet Gynecol. 37 (1): 116-26.
[8]	Sureau C., Henrion R. Rapport du Comité National Technique de l’Echographie de Dépistage Prénatal 2005 http://www.ladocumentationfrancaise.fr/rapports-publics/054000356/index.shtml [05/05/2017].
[9]	Dommergues M, Bessis R, Henrion R. (2006) Rapport du Comité national technique de l'échographie de dépistage prénatal: quelles conséquences pour la pratique? Gynécologie Obstétrique & Fertilité, 34: 1090–1095.
[10]	Salomon LJ, Bernard JP, Duyme M, Doris B, Mas N, Ville Y (2006.) Feasibility and reproducibility of an image-scoring method for quality control of fetal biometry in the second trimester Ultrasound Obstet Gynecol. 27 (1): 34-40.
[11]	Jaudi S, Granger B, Herpin CN, Fries N, Du Montcel ST, Dommergues M (2013). Online audit and feedback improve fetal second-trimester four-chamber view images: a randomised controlled trial. Prenat Diagn. 33 (10): 959-64.
[12]	International Society of Ultrasound in Obstetrics & Gynecology (2006). Cardiac screening examination of the fetus: guidelines for performing the 'basic' and 'extended basic' cardiac scan. Ultrasound Obstet Gynecol; 27: 107-13.
[13]	RCOG. org. uk: Logbook for fetal anatomy https://www.rcog.org.uk/en/careers-training/resources--support-for-trainees/useful-resources-for-trainees/trog-news/ultrasound-updates/.
[14]	Jaudi S, Du Montcel ST, Fries N, Nizard J, Desfontaines VH, Dommergues M (2011). Online evaluation of fetal second trimester four chamber view images: a comparison of six evaluation methods. Ultrasound Obstet Gynecol; 38 (2): 185-190.
[15]	Sairam S, Awadh A. M. A, Cook K, Papageorghiou A. T, Carvalho J. S (2009). Impact of audit of routine second-trimester cardiac images using a novel image scoring method. Ultrasound Obstet Gynecol; 33: 545-551.
[16]	Jamtvedt G, Young JM, Kristoffersen DT, O'Brien MA, Oxman AD (2006). Does telling people what they have been doing change what they do? A systematic review of the effects of audit and feedback. Qual Saf Health Care; 15 (6): 433-436.
[17]	Koch, Gary G. Intraclass correlation coefficient. In: Kotz S, Johnson N (1982). Encyclopedia of Statistical Sciences. New York: John Wiley & Sons; p. 213–217.
[18]	Gordon MJ (1991). A review of the validity and accuracy of self-assessments in health professions training. Acad Med; 66: 762-9.
[19]	Davis DA, Mazmanian PE, Fordis M, Van Harrison R, Thorpe KE, Perrier L. (2006). Accuracy of physician self-assessment compared with observed measures of competence: a systematic review. JAMA; 296: 1094-102.

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APA Style

Suha Jaudi, Louise Chevalier, Nicolas Fries, Alain Daher, Sophie Tezenas du Montcel, et al. (2019). Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial. Education Journal, 8(5), 226-231. https://doi.org/10.11648/j.edu.20190805.17

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ACS Style

Suha Jaudi; Louise Chevalier; Nicolas Fries; Alain Daher; Sophie Tezenas du Montcel, et al. Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial. Educ. J. 2019, 8(5), 226-231. doi: 10.11648/j.edu.20190805.17

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AMA Style

Suha Jaudi, Louise Chevalier, Nicolas Fries, Alain Daher, Sophie Tezenas du Montcel, et al. Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial. Educ J. 2019;8(5):226-231. doi: 10.11648/j.edu.20190805.17

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@article{10.11648/j.edu.20190805.17,
  author = {Suha Jaudi and Louise Chevalier and Nicolas Fries and Alain Daher and Sophie Tezenas du Montcel and Marc Dommergues},
  title = {Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial},
  journal = {Education Journal},
  volume = {8},
  number = {5},
  pages = {226-231},
  doi = {10.11648/j.edu.20190805.17},
  url = {https://doi.org/10.11648/j.edu.20190805.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20190805.17},
  abstract = {Continuing medical education in the field of fetal ultrasound imaging is based on expert audit of still images, a time consuming approach. Our objective was to determine if self-evaluation of the images a professional produced is as effective as audit and feedback by an expert as a method of continuous medical education. We designed a prospective blinded randomized controlled trial. 321 ultrasonographers uploaded on a continuous medical education website a first set of 30 biometry images (10 cephalic, 10 abdominal and 10 femoral) from 10 consecutive second or third trimester normal screening scans. In arm 1: participants (N = 151) assessed their own images online according to a standardized procedure, and received feedback with detailed recommendations for change, automatically generated based on their assessment. The images were also audited by an expert, but participants remained blinded to the expert’s rating. In arm 2: participants (N = 177) had their images assessed by an expert and received a feedback, formatted as in arm 1, automatically generated based on the expert’s assessment Three to 6 months later, participants uploaded a second set of images, audited by an expert. A total of 19,680 images were audited. In the self-assessment group, the percentage of images meeting all criteria (IMAC) rose from 55 to 62.2 (p < 0.0001). In the expert-assessment and feedback group, the percentage of IMAC rose from 54.2 to 59.1 (p < 0.0001). Improvement in image quality was equivalent in both groups with a difference in IMAC increase of 2.3 percentage points (95%CI: -1.7 to + 6.4). In conclusion, online training based on self-assessment of fetal ultrasound images was as effective as expert audit and feedback. NCT02074592.},
 year = {2019}
}

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TY  - JOUR
T1  - Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial
AU  - Suha Jaudi
AU  - Louise Chevalier
AU  - Nicolas Fries
AU  - Alain Daher
AU  - Sophie Tezenas du Montcel
AU  - Marc Dommergues
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DO  - 10.11648/j.edu.20190805.17
T2  - Education Journal
JF  - Education Journal
JO  - Education Journal
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EP  - 231
PB  - Science Publishing Group
SN  - 2327-2619
UR  - https://doi.org/10.11648/j.edu.20190805.17
AB  - Continuing medical education in the field of fetal ultrasound imaging is based on expert audit of still images, a time consuming approach. Our objective was to determine if self-evaluation of the images a professional produced is as effective as audit and feedback by an expert as a method of continuous medical education. We designed a prospective blinded randomized controlled trial. 321 ultrasonographers uploaded on a continuous medical education website a first set of 30 biometry images (10 cephalic, 10 abdominal and 10 femoral) from 10 consecutive second or third trimester normal screening scans. In arm 1: participants (N = 151) assessed their own images online according to a standardized procedure, and received feedback with detailed recommendations for change, automatically generated based on their assessment. The images were also audited by an expert, but participants remained blinded to the expert’s rating. In arm 2: participants (N = 177) had their images assessed by an expert and received a feedback, formatted as in arm 1, automatically generated based on the expert’s assessment Three to 6 months later, participants uploaded a second set of images, audited by an expert. A total of 19,680 images were audited. In the self-assessment group, the percentage of images meeting all criteria (IMAC) rose from 55 to 62.2 (p < 0.0001). In the expert-assessment and feedback group, the percentage of IMAC rose from 54.2 to 59.1 (p < 0.0001). Improvement in image quality was equivalent in both groups with a difference in IMAC increase of 2.3 percentage points (95%CI: -1.7 to + 6.4). In conclusion, online training based on self-assessment of fetal ultrasound images was as effective as expert audit and feedback. NCT02074592.
VL  - 8
IS  - 5
ER  -

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Author Information

Suha Jaudi

Department of Obstetrics and Gynecology, Hopital Universitaire Pitié Salpêtrière Charles Foix APHP and Sorbonne Universite, Paris, France; Collège Francais d'Echographie Foetale (French College for Fetal Ultrasound, CFEF), Montpellier, France
Louise Chevalier

Department of Biostatistics, Hopital Universitaire Pitié Salpêtrière Charles Foix APHP and Sorbonne Université, Paris, France
Nicolas Fries

Collège Francais d'Echographie Foetale (French College for Fetal Ultrasound, CFEF), Montpellier, France
Alain Daher

Department of Obstetrics and Gynecology, Hopital Universitaire Pitié Salpêtrière Charles Foix APHP and Sorbonne Universite, Paris, France
Sophie Tezenas du Montcel

Department of Biostatistics and URC, Hopital Universitaire Pitié Salpetriere Charles Foix APHP and Sorbonne Universite, Paris, France; ER4 Modélisation et Recherche Clinique, Sorbonne Université, Paris, France
Marc Dommergues

Department of Obstetrics and Gynecology, Hopital Universitaire Pitié Salpêtrière Charles Foix APHP and Sorbonne Universite, Paris, France; Collège Francais d'Echographie Foetale (French College for Fetal Ultrasound, CFEF), Montpellier, France

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Plain Text BibTeX RIS

APA Style

Suha Jaudi, Louise Chevalier, Nicolas Fries, Alain Daher, Sophie Tezenas du Montcel, et al. (2019). Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial. Education Journal, 8(5), 226-231. https://doi.org/10.11648/j.edu.20190805.17

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ACS Style

Suha Jaudi; Louise Chevalier; Nicolas Fries; Alain Daher; Sophie Tezenas du Montcel, et al. Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial. Educ. J. 2019, 8(5), 226-231. doi: 10.11648/j.edu.20190805.17

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AMA Style

Suha Jaudi, Louise Chevalier, Nicolas Fries, Alain Daher, Sophie Tezenas du Montcel, et al. Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial. Educ J. 2019;8(5):226-231. doi: 10.11648/j.edu.20190805.17

Copy | Download

@article{10.11648/j.edu.20190805.17,
  author = {Suha Jaudi and Louise Chevalier and Nicolas Fries and Alain Daher and Sophie Tezenas du Montcel and Marc Dommergues},
  title = {Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial},
  journal = {Education Journal},
  volume = {8},
  number = {5},
  pages = {226-231},
  doi = {10.11648/j.edu.20190805.17},
  url = {https://doi.org/10.11648/j.edu.20190805.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20190805.17},
  abstract = {Continuing medical education in the field of fetal ultrasound imaging is based on expert audit of still images, a time consuming approach. Our objective was to determine if self-evaluation of the images a professional produced is as effective as audit and feedback by an expert as a method of continuous medical education. We designed a prospective blinded randomized controlled trial. 321 ultrasonographers uploaded on a continuous medical education website a first set of 30 biometry images (10 cephalic, 10 abdominal and 10 femoral) from 10 consecutive second or third trimester normal screening scans. In arm 1: participants (N = 151) assessed their own images online according to a standardized procedure, and received feedback with detailed recommendations for change, automatically generated based on their assessment. The images were also audited by an expert, but participants remained blinded to the expert’s rating. In arm 2: participants (N = 177) had their images assessed by an expert and received a feedback, formatted as in arm 1, automatically generated based on the expert’s assessment Three to 6 months later, participants uploaded a second set of images, audited by an expert. A total of 19,680 images were audited. In the self-assessment group, the percentage of images meeting all criteria (IMAC) rose from 55 to 62.2 (p < 0.0001). In the expert-assessment and feedback group, the percentage of IMAC rose from 54.2 to 59.1 (p < 0.0001). Improvement in image quality was equivalent in both groups with a difference in IMAC increase of 2.3 percentage points (95%CI: -1.7 to + 6.4). In conclusion, online training based on self-assessment of fetal ultrasound images was as effective as expert audit and feedback. NCT02074592.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Online Self-Evaluation of Fetal Ultrasound Images for Medical Continuing Education: A Randomised Controlled Trial
AU  - Suha Jaudi
AU  - Louise Chevalier
AU  - Nicolas Fries
AU  - Alain Daher
AU  - Sophie Tezenas du Montcel
AU  - Marc Dommergues
Y1  - 2019/09/05
PY  - 2019
N1  - https://doi.org/10.11648/j.edu.20190805.17
DO  - 10.11648/j.edu.20190805.17
T2  - Education Journal
JF  - Education Journal
JO  - Education Journal
SP  - 226
EP  - 231
PB  - Science Publishing Group
SN  - 2327-2619
UR  - https://doi.org/10.11648/j.edu.20190805.17
AB  - Continuing medical education in the field of fetal ultrasound imaging is based on expert audit of still images, a time consuming approach. Our objective was to determine if self-evaluation of the images a professional produced is as effective as audit and feedback by an expert as a method of continuous medical education. We designed a prospective blinded randomized controlled trial. 321 ultrasonographers uploaded on a continuous medical education website a first set of 30 biometry images (10 cephalic, 10 abdominal and 10 femoral) from 10 consecutive second or third trimester normal screening scans. In arm 1: participants (N = 151) assessed their own images online according to a standardized procedure, and received feedback with detailed recommendations for change, automatically generated based on their assessment. The images were also audited by an expert, but participants remained blinded to the expert’s rating. In arm 2: participants (N = 177) had their images assessed by an expert and received a feedback, formatted as in arm 1, automatically generated based on the expert’s assessment Three to 6 months later, participants uploaded a second set of images, audited by an expert. A total of 19,680 images were audited. In the self-assessment group, the percentage of images meeting all criteria (IMAC) rose from 55 to 62.2 (p < 0.0001). In the expert-assessment and feedback group, the percentage of IMAC rose from 54.2 to 59.1 (p < 0.0001). Improvement in image quality was equivalent in both groups with a difference in IMAC increase of 2.3 percentage points (95%CI: -1.7 to + 6.4). In conclusion, online training based on self-assessment of fetal ultrasound images was as effective as expert audit and feedback. NCT02074592.
VL  - 8
IS  - 5
ER  -

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