Rebecca Delpino

University College Birmingham, UK

Title: Improving patient outcomes in clinical Skills and simulation-based education: A realist review examining contributions of XR immersive technologies

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Biography

Rebecca Delpino is a highly experienced registered adult nurse, who qualified in 1993 at the Queen Elizabeth Medical Centre in Birmingham. With over two decades of clinical practice, she has built a strong foundation in trauma and orthopedics, as well as across a range of medical and surgical ward settings. Rebecca has also held a number of senior leadership roles over the past 18 years, including Ward Sister, Ward Manager, and Clinical Night Sister. Her extensive experience reflects a deep commitment to patient care, team leadership, and clinical excellence in acute healthcare environments.

Abstract

Background: The paper aims to examine circumstances that lead to improvement of patient outcomes by contribution of XR immersive technologies in clinical skills and simulation-based education. The realist approach that is fundamentally concerned with theory development and refinement[1,2,3] of complex interventions is adopted to enable development of new knowledge and highlight success and areas of development.

Methods/Design: Quality guidance and checklist of ‘RAMESES’ (Realist and meta-review Evidence Synthesis: Evolving Standards) were used to gain an understanding of the different contexts of how interventions worked. A realist review included secondary data analysis using a database search of MEDLINE, CINAHL, BNI, EMBASE, PubMed and Google Scholar. Main terms used were ‘digital technology’ ‘XR in Healthcare/Extended Reality’ and their related synonyms. Once key data were extracted realist analysis was undertaken to identify impact of context and underlying causal mechanisms that can lead to different outcomes.

Realist and meta-narrative review approaches are relatively new approaches to systematic review and are theory driven, guiding the process from the beginning, with data extraction and synthesis being key aspects of theory refinement[4]. Much of the focus being on interactions between interventions, Context (C), Mechanism (M) and Outcomes (O) configuration, aim to identify patterns and refine the theory.

Results: Literature search initially provided 179 inclusion-relevant papers. 37 studies that were primarily focused on research-related immersive experiences were chosen for data extraction. Context of emerging technologies in selected studies included:

• Virtual Reality (VR),

• Augmented Reality (AR),

• Mixed Reality (MR)

• Extended Reality (XR)

These were then themed through connections and chains of inference into the following categories:

• Skills

• Knowledge

• Quality

• Personal characteristics

• Learner experiences

• Cost-benefit & justification

• Patient safety

• Affective outcomes

The above approaches enabled narrative development to generate new knowledge and identified best applications of XR immersive technologies in clinical skills training and simulation-based education to enhance timely, technology assisted appropriate and cost-effective learning to improve patient outcomes.

Discussion: Characteristics of the immersive experiences contribute to healthcare outcomes. The complexities of these experiences can also enhance learner skills. The foundations of Artificial Intelligence (AI) are built on data, discovery, diversity of learning an assumption that human thinking can be reduced to logical steps that can be mechanised[3]. Replication of human intelligence, exist in various forms such as computing machines, rules based, machine learning, input, and output data, such as software development and smart phones. Arguably, AI evidence standards, safety and harms show failures around ‘clinical benefits for patients’[2] suggesting that solutions are human and not technical.