Details der Publikation - Educational impact of hand motion analysis in the evaluation of FAST examination skills

Educational impact of hand motion analysis in the evaluation of FAST examination skills

Purpose Increasing pressure pushes towards the objective competence assessment of clinical operators. Hand motion analysis (HMA) was introduced to measure surgical and clinical procedures; its recent application to FAST examinations leaves unsolved issues. This study aimed at determining optimal HMA parameters to discriminate between operators’ skill levels, and which FAST tasks are experience-dependent. Methods Ten experienced (EG) and 13 beginner (BG) sonographers performed a FAST examination on one female and one male model. A motion capture system returned the duration, working volume, number of movements (absolute and time normalized), and hand path length (absolute and time normalized) of each view. Results BG took more time in completing specific views, with a higher working volume (p = 0.003) and longer hands path (p < 0.001). The number of movements was lower in the EG (p < 0.001) and differed between views (p = 0.014). No significant Group/Model differences were found for the normalized number of movements. The LUQ view required a higher number of movements (p < 0.001). Conclusions HMA identified kinematic parameters discriminating between proficiency level and critical subtasks in the FAST examination. These findings could be the base for a focused HMA-based evaluation of performances following a proctored training period. There is room to incorporate HMA into simulation metrics and evidence-based credentialing standards for clinical ultrasound applications..

Medienart:	E-Artikel

Erscheinungsjahr:	2019
Erschienen:	2019

Enthalten in:	Zur Gesamtaufnahme - volume:46
Enthalten in:	European journal of trauma and emergency surgery - 46(2019), 6 vom: 15. März, Seite 1421-1428

Sprache:	Englisch

Beteiligte Personen:	Zago, Mauro [VerfasserIn] Sforza, Chiarella [VerfasserIn] Mariani, Diego [VerfasserIn] Marconi, Matteo [VerfasserIn] Biloslavo, Alan [VerfasserIn] Greca, Antonio La [VerfasserIn] Kurihara, Hayato [VerfasserIn] Casamassima, Andrea [VerfasserIn] Bozzo, Samantha [VerfasserIn] Caputo, Francesco [VerfasserIn] Galli, Manuela [VerfasserIn] Zago, Matteo [VerfasserIn]

Links:	Volltext [lizenzpflichtig]

BKL:	44.80$jUnfallmedizin$jNotfallmedizin 44.65$jChirurgie
Themen:	Competence FAST Initial assessment Management Skill assessment Ultrasound

Anmerkungen:	© Springer-Verlag GmbH Germany, part of Springer Nature 2019

doi:	10.1007/s00068-019-01112-6

funding:
Förderinstitution / Projekttitel:

PPN (Katalog-ID):	OLC2121511180

Internformat


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520			\|a Purpose Increasing pressure pushes towards the objective competence assessment of clinical operators. Hand motion analysis (HMA) was introduced to measure surgical and clinical procedures; its recent application to FAST examinations leaves unsolved issues. This study aimed at determining optimal HMA parameters to discriminate between operators’ skill levels, and which FAST tasks are experience-dependent. Methods Ten experienced (EG) and 13 beginner (BG) sonographers performed a FAST examination on one female and one male model. A motion capture system returned the duration, working volume, number of movements (absolute and time normalized), and hand path length (absolute and time normalized) of each view. Results BG took more time in completing specific views, with a higher working volume (p = 0.003) and longer hands path (p < 0.001). The number of movements was lower in the EG (p < 0.001) and differed between views (p = 0.014). No significant Group/Model differences were found for the normalized number of movements. The LUQ view required a higher number of movements (p < 0.001). Conclusions HMA identified kinematic parameters discriminating between proficiency level and critical subtasks in the FAST examination. These findings could be the base for a focused HMA-based evaluation of performances following a proctored training period. There is room to incorporate HMA into simulation metrics and evidence-based credentialing standards for clinical ultrasound applications.
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Educational impact of hand motion analysis in the evaluation of FAST examination skills

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