Implementing, embedding and sustaining simulation-based education: What helps, what hinders

Objectives: Although there is much evidence to support the use of simulation-based education (SBE) in undergraduate education of health care professionals, less attention has been paid to how SBE, viewed as a complex intervention, is implemented and becomes embedded and sustained. This paper aims to explore factors that inhibited or promoted SBE becoming normal practice in undergraduate health care professional programmes. Methods: Participants involved in the organisation, design and delivery of SBE in the north of England were recruited purposefully from higher education institutions (HEI) and National Health Service (NHS) Trusts through local networks for qualitative telephone interviews. Transcripts were analysed inductively using a hybrid approach involving simultaneous inductive open coding and deductive coding using normalisation process theory (NPT) as a theoretical lens. Findings: A total of 12 NHS staff from 11 trusts and seven individuals from four HEIs were interviewed. There was considerable variation in the approach taken to implementation across organisations, which resulted in varying degrees of embeddedness. Implementation was challenged or enabled by organisational leadership, professional buy-in and the development and maturity of the strategic approach. Variation in understanding of the scope and pedagogical aims of SBE led to inequity between professions and organisations in investment and participation, as well as design and delivery of SBE. Conclusions: Given the complexity of SBE, best practice in implementation should be considered fundamental to the successful delivery of SBE. The findings provide an explanation of how contextual factors can support or hinder implementation to maximise potential benefits and learning outcomes; this understanding can be used to better inform development of SBE strategies and highlight potential factors needed to navigate contextual barriers so that learning outcomes can be maximised.