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R. Gurbutt1, D. Gurbutt2, P. Hartwick3, N. Nowlan4, M. Morley5

1University of Leeds (UNITED KINGDOM)
2Higher Education Academy UK (UNITED KINGDOM)
3Carleton university (CANADA)
43D Virtual Crafting (CANADA)
5Algonquin College (CANADA)
Simulation environments offer many advantages (see Byrne, Heavey and Byrne, 2010) and are relevant to preparing learners for clinical roles, although the reported evidence on the value of modelling in health care remains uncertain because the evidence of implementation is limited (Fone et al, 2012). Simulation offers a safe environment for students to develop their decision making skills as they explore information seeking, discuss interpretation and problem recognition, sometimes make mistakes and receive peer coaching and peer review of their performance. Whilst this has traditionally occurred in practice settings the risks to client safety and care quality support a case for creative ways to build competency in decision making. It is necessary however, to ensure that the simulation is educationally rather than technologically led so the quality of learners’ experiences can be confidently anticipated. Several factors including technical, educational, sociological and professional shape this design as well as regional, national and international contexts. These have to be accommodated in real world simulation design.

This poster highlights a range of factors addressed during a clinical decision making simulation design about a given healthcare topic - in this case dementia related mental health assesment and decision making. The simulation is the result of shared discussions between academics in the UK and Canada and addresses methods of gaining inter-professional working and internationalisation dimensions in decision making. It also required choices to be made about technical matters underpinning the creation, editing, publishing and accessibility of the simulation. Design factors can be managed to generate variations in the learning experience including: (i) Scenario Complexity (content) and different types of participant behaviour (such as imposing task time restrictions) (ii) inter-professional learning (e.g. between Nursing and social care students) (iii) internationalisation (e.g. by synchronous engagement with students from other settings and nations) (iv) Research informed practice (e.g. health and social care policies and practice guides) (v) synchronous and asynchronous learning in the simulation (e.g. tutor led, tutor facilitated or a tutor not present) (vi) reflection and review (e.g. a virtual breakout area and question prompts or a debrief to review issues identified, the decisions proposed and their implications). This design is deliberately flexible so that it can be adapted to generate new iterations around the same or different clinical topic themes.

Fone D, S Hollinghurst, M Temple, A Round, N Lester, A Weightman, K Roberts, E Coyle, G Bevan and S Palmer. 2012. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. Journal of Public Health Medicine Vol. 25, No. 4, pp. 325–335
Byrne J., C. Heavey, .J. Byrne 2010. A review of Web-based simulation and supporting tools. Simulation Modelling Practice and Theory 18 (2010) 253–276