Simulation-based clinical assessment identifies threshold competence to practise physiotherapy in Australia : a crossover trial

P. Moss, A. Barnett-Harris, D. Lee, K. Gupta, S. Pritchard, N. Sievers, M. Te, Felicity Blackstock

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Abstract

Background: Although evidence exists for the efficacy of high-fidelity simulation as an educational tool, there is limited evidence for its application in high-stakes professional threshold competency assessment. An alternative model of simulation-based assessment was developed by the Australian Physiotherapy Council (APC), using purpose-written standardised patients, mapped to the appropriate threshold level. The aim of this two-phase study was to investigate whether simulation-based clinical assessments resulted in equivalent outcomes to standard, real-life assessments for overseas-trained physiotherapists seeking registration to practice in Australia. Methods: A randomised crossover trial comparing simulation-based assessment to real-life assessment was completed. Participants were internationally trained physiotherapists applying for registration to practice in Australia, voluntarily recruited from the Australian Physiotherapy Council (APC) assessment waiting list: study 1 n = 25, study 2 n = 144. Study 1 participants completed usual APC real-life assessments in 3 practice areas, completed on different days at APC partner healthcare facilities. Participants also underwent 3 practice area-matched simulation-based assessments, completed on the same day at purpose-designed simulation facilities. Study 2 participants completed 3 simulation-based assessments and 1 real-life assessment that was randomly allocated for order and practice area. Assessment of competency followed the standard APC procedure of 90-minute examinations using The Moderated Assessment Form (MAF). Results: The overall pass rate was higher for real-life assessments in both studies: study 1, 50% versus 42.7%; study 2, 55.6% versus 44.4%. Chi-square analysis showed a high to moderate level of exact matching of pass/fail grades across all assessments: study 1, 73.4% (p < 0.001); study 2, 58.3% (p = 0.027). Binary logistic regression showed that the best predictors of real-life pass/fail grade were simulation-based MAF pass/fail grade (study 1, OR 7.86 p < 0.001; study 2, OR 2.037, p = 0.038) and simulation-based total MAF score (study 1, OR 1.464 p < 0.001; study 2, OR 1.234, p = 0.001). Conclusion: Simulation-based assessment is a significant predictor of clinical performance and can be used to successfully identify high stakes threshold competence to practice physiotherapy in Australia.

Original languageEnglish
Article number21
Number of pages9
JournalAdvances in Simulation
Volume7
Issue number1
DOIs
Publication statusPublished - Dec 2022

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