Exploring the role of high-fidelity simulation for pre-foundation assistantship students to improve preparedness for...

BACKGROUND: In the UK, new medical graduates frequently feel underprepared in managing acutely unwell patients. Clinical experiential learning gained, can be opportunistic and variable. Simulation-based medical education (SBME) has previously been shown to improve preparedness for practice. At Imperial College London, a half day high-fidelity simulation course for final year students during their pre-foundation assistantship (PFA) placement was set up focusing on the assessment and management of acutely unwell patients including appropriate escalation and use of the adult life support algorithm. METHODS: Using student self-reported questionnaires, this study aimed to explore if there was any added value in implementing a high-fidelity simulation in preparing PFA students for Foundation Year 1 (FY1) training and to identify factors influencing effectiveness. RESULTS: Pre-session and post-session questionnaires completed by students demonstrated an improvement in self-reported confidence and preparedness for practice. Median confidence in diagnosing and managing medical emergencies and in using the Advanced Life Support algorithm improved by 1 point on a 5-point Likert scale. Students also felt more prepared for Foundation training and managing an acute medical situation with more distant supervision, with median preparedness and distance of supervision respectively improving by 1 point. Key themes from student questionnaires suggested hands-on learning, debriefing and faculty continuity were beneficial aspects of the course. CONCLUSIONS: High fidelity simulation delivered in the pre-foundation period improved the self-reported confidence and preparedness of students for practice, aligning with previous research supporting the effectiveness of SBME to improve preparedness for practice. It adds to existing literature regarding the added value of SBME incorporation during the pre-foundation period and which features optimise the simulation learning environment.