Variability between human experts and artificial intelligence in identification of anatomical structures by ultrasound in regional anaesthesia: a framework for evaluation of assistive artificial intelligence.

Background: ScanNavAnatomy Peripheral Nerve Block (ScanNav™) is an artificial intelligence (AI)-based device that produces a colour overlay on real-time B-mode ultrasound to highlight key anatomical structures for regional anaesthesia. This study compares consistency of identification of sono-anatomical structures between expert ultrasonographers and ScanNav™.

Methods: Nineteen experts in ultrasound-guided regional anaesthesia (UGRA) annotated 100 structures in 30 ultrasound videos across six anatomical regions.

Patient safety incidents in anaesthesia: a qualitative study of trainee experience from a single UK healthcare region.

Background: Anaesthetic training has always had patient safety as part of the curriculum. However, there is limited emphasis on what happens when things do not go to plan. Our aims were to understand the impact of involvement in patient safety incidents on anaesthetic trainees in our region, to describe the range of support currently offered and put forward suggestions for improvement.

Prospective randomized evaluation of the sustained impact of assistive artificial intelligence on anesthetists' ultrasound scanning for regional anesthesia.

Objectives: Ultrasound-guided regional anesthesia (UGRA) relies on acquiring and interpreting an appropriate view of sonoanatomy. Artificial intelligence (AI) has the potential to aid this by applying a color overlay to key sonoanatomical structures.The primary aim was to determine whether an AI-generated color overlay was associated with a difference in participants' ability to identify an appropriate block view over a 2-month period after a standardized teaching session (as judged by a blinded assessor).

Strategies for adapting under pressure: an interview study in intensive care units.

Background: Healthcare systems are operating under substantial pressures. Clinicians and managers are constantly having to make adaptations, which are typically improvised, highly variable and not coordinated across teams. This study aimed to identify and describe the types of everyday pressures in intensive care and the adaptive strategies staff use to respond, with the longer-term aim of developing practical and coordinated strategies for managing under pressure.

Artificial intelligence for ultrasound scanning in regional anaesthesia: a scoping review of the evidence from multiple disciplines.

Background: Artificial intelligence (AI) for ultrasound scanning in regional anaesthesia is a rapidly developing interdisciplinary field. There is a risk that work could be undertaken in parallel by different elements of the community but with a lack of knowledge transfer between disciplines, leading to repetition and diverging methodologies. This scoping review aimed to identify and map the available literature on the accuracy and utility of AI systems for ultrasound scanning in regional anaesthesia.

Adaptive strategies used by surgical teams under pressure: an interview study among senior healthcare professionals in four major hospitals in the United Kingdom.

Background: Healthcare systems are operating under substantial pressures, and often simply cannot provide the standard of care they aspire to within the available resources. Organisations, managers, and individual clinicians make constant adaptations in response to these pressures, which are typically improvised, highly variable and not coordinated across clinical teams. The purpose of this study was to identify and describe the types of everyday pressures experienced by surgical teams and the adaptive strategies they use to respond to these pressures.

Adopting human factors in early phase and experimental medicine research: A nested pilot study observing controlled human infection with SARS-CoV-2.

Aims: The influence of human factors on safety in healthcare settings is well established, with targeted interventions reducing risk and enhancing team performance. In experimental and early phase clinical research participant safety is paramount and safeguarded by guidelines, protocolized care and staff training; however, the real-world interaction and implementation of these risk-mitigating measures has never been subjected to formal system-based assessment.

Methods: Independent structured observations, systematic review of study documents, and interviews and focus groups were used to collate data on three key tasks undertaken in a clinical research facility (CRF) during a SARS CoV-2 controlled human infection model (CHIM) study.

Cognitive aids in the management of clinical emergencies: a systematic review.

Clinical emergencies can be defined as unpredictable events that necessitate immediate intervention. Safety critical industries have acknowledged the difficulties of responding to such crises. Strategies to improve human performance and mitigate its limitations include the provision and use of cognitive aids, a family of tools that includes algorithms, checklists and decision aids.

Recommendations for anatomical structures to identify on ultrasound for the performance of intermediate and advanced blocks in ultrasound-guided regional anesthesia.

Recent recommendations describe a set of core anatomical structures to identify on ultrasound for the performance of basic blocks in ultrasound-guided regional anesthesia (UGRA). This project aimed to generate consensus recommendations for core structures to identify during the performance of intermediate and advanced blocks. An initial longlist of structures was refined by an international panel of key opinion leaders in UGRA over a three-round Delphi process.

Evaluation of the impact of assistive artificial intelligence on ultrasound scanning for regional anaesthesia.

Background: Ultrasound-guided regional anaesthesia relies on the visualisation of key landmark, target, and safety structures on ultrasound. However, this can be challenging, particularly for inexperienced practitioners. Artificial intelligence (AI) is increasingly being applied to medical image interpretation, including ultrasound.

Assistive artificial intelligence for ultrasound image interpretation in regional anaesthesia: an external validation study.

Background: Ultrasonound is used to identify anatomical structures during regional anaesthesia and to guide needle insertion and injection of local anaesthetic. ScanNav Anatomy Peripheral Nerve Block (Intelligent Ultrasound, Cardiff, UK) is an artificial intelligence-based device that produces a colour overlay on real-time B-mode ultrasound to highlight anatomical structures of interest. We evaluated the accuracy of the artificial-intelligence colour overlay and its perceived influence on risk of adverse events or block failure.

Non-technical Skills for Medical Students: Validating the Tools of the Trade.

The Medical Students' Non-Technical Skills (Medi-StuNTS) is a behavioural marker scheme (BMS) designed to assess non-technical skills (NTS) in medical students in emergency simulations. This study aimed to assess the evidence for validity and usability of Medi-StuNTS by naive, near-peer educators. Nine doctors assessed four students in simulations of common medical emergencies.

Artificial Intelligence: Innovation to Assist in the Identification of Sono-anatomy for Ultrasound-Guided Regional Anaesthesia.

Ultrasound-guided regional anaesthesia (UGRA) involves the targeted deposition of local anaesthesia to inhibit the function of peripheral nerves. Ultrasound allows the visualisation of nerves and the surrounding structures, to guide needle insertion to a perineural or fascial plane end point for injection. However, it is challenging to develop the necessary skills to acquire and interpret optimal ultrasound images.

Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia.

Introduction: Ultrasound-guided regional anesthesia (UGRA) involves the acquisition and interpretation of ultrasound images to delineate sonoanatomy. This study explores the utility of a novel artificial intelligence (AI) device designed to assist in this task (ScanNav Anatomy Peripheral Nerve Block; ScanNav), which applies a color overlay on real-time ultrasound to highlight key anatomical structures.

Methods: Thirty anesthesiologists, 15 non-experts and 15 experts in UGRA, performed 240 ultrasound scans across nine peripheral nerve block regions.

Validation of the Partners at Care Transitions Measure (PACT-M): assessing the quality and safety of care transitions for older people in the UK.

Background: The Partners at Care Transitions Measure (PACT-M) is a patient-reported questionnaire for evaluation of the quality and safety of care transitions from hospital to home, as experienced by older adults. PACT-M has two components; PACT-M 1 to capture the immediate post discharge period and PACT-M 2 to assess the experience of managing care at home. In this study, we aim to examine the psychometric properties, factor structure, validity and reliability of the PACT-M.

In situ deteriorating patient simulation in general practice.

Background: GP practices have limited access to medical emergency training and basic life support is often taught out of context as a skills-based event.

Aim: To develop and evaluate a whole team integrated simulation-based education, to enhance learning, change behaviours and provide safer care.

Method: Phase 1: 10 practices piloted a 3-hour programme delivering 40 minutes BLS and AED skills and 2-hour deteriorating patient simulation.

Simulation past, present and future-a decade of progress in simulation-based education in the UK.

This review will present developments in simulation-based education (SBE) over the past decade with a focus on activity in the UK's National Health Service and the role of the national society (the Association for Simulation Practice in Healthcare). The article covers the evolution of strategic changes for the use of SBE in the UK and the operational challenges faced by clinicians and other faculty in SBE. The expansion of the evidence base to support SBE in healthcare both in technical skills and, more broadly, in interprofessional team training is explored.