Moving beyond the AI sales pitch - Empowering clinicians to ask the right questions about clinical AI.

We challenge the dominant technology-centric narrative around clinical AI. To realise the true potential of the technology, clinicians must be empowered to take a whole-system perspective and assess the suitability of AI-supported tasks for their specific complex clinical setting. Key factors include the AI's capacity to augment human capabilities, evidence of clinical safety beyond general performance metrics and equitable clinical decision-making by the human-AI team.

Understanding the enablers and barriers to implementing a patient-led escalation system: a qualitative study.

Background: The management of acute deterioration following surgery remains highly variable. Patients and families can play an important role in identifying early signs of deterioration but effective contribution to escalation of care can be practically difficult to achieve. This paper reports the enablers and barriers to the implementation of patient-led escalation systems found during a process evaluation of a quality improvement programme Rescue for Emergency Surgery Patients Observed to uNdergo acute Deterioration (RESPOND).

Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units.

Weaning patients from ventilation in intensive care units (ICU) is a complex task. There is a growing desire to build decision-support tools to help clinicians during this process, especially those employing Artificial Intelligence (AI). However, tools built for this purpose should fit within and ideally improve the current work environment, to ensure they can successfully integrate into clinical practice.

Digital health and care: emerging from pandemic times.

In 2020, we published an editorial about the massive disruption of health and care services caused by the COVID-19 pandemic and the rapid changes in digital service delivery, artificial intelligence and data sharing that were taking place at the time. Now, 3 years later, we describe how these developments have progressed since, reflect on lessons learnt and consider key challenges and opportunities ahead by reviewing significant developments reported in the literature. As before, the three key areas we consider are digital transformation of services, realising the potential of artificial intelligence and wise data sharing to facilitate learning health systems.

Assuring safe artificial intelligence in critical ambulance service response: study protocol.

Introduction: Early recognition of out-of-hospital cardiac arrest (OHCA) by ambulance service call centre operators is important so that cardiopulmonary resuscitation can be delivered immediately, but around 25% of OHCAs are not picked up by call centre operators. An artificial intelligence (AI) system has been developed to support call centre operators in the detection of OHCA. The study aims to (1) explore ambulance service stakeholder perceptions on the safety of OHCA AI decision support in call centres, and (2) develop a clinical safety case for the OHCA AI decision-support system.

Am I safe? An Interpretative Phenomenological Analysis of Vulnerability as Experienced by Patients With Complications Following Surgery.

Abdominal surgery carries with it risks of complications. Little is known about patients' experiences of post-surgical deterioration. There is a real need to understand the psychosocial as well as the biological aspects of deterioration in order to improve care and outcomes for patients.

A comparison of machine learning algorithms in predicting COVID-19 prognostics.

ML algorithms are used to develop prognostic and diagnostic models and so to support clinical decision-making. This study uses eight supervised ML algorithms to predict the need for intensive care, intubation, and mortality risk for COVID-19 patients. The study uses two datasets: (1) patient demographics and clinical data (n = 11,712), and (2) patient demographics, clinical data, and blood test results (n = 602) for developing the prediction models, understanding the most significant features, and comparing the performances of eight different ML algorithms.

The contribution of human factors and ergonomics to the design and delivery of safe future healthcare.

Human factors and ergonomics (HF/E) is concerned with the design of work and work systems. There is an increasing appreciation of the value that HF/E can bring to enhancing the quality and safety of care, but the professionalisation of HF/E in healthcare is still in its infancy. In this paper, we set out a vision for HF/E in healthcare based on the work of the Chartered Institute of Ergonomics and Human Factors (CIEHF), which is the professional body for HF/E in the UK.

A systems analysis of the COVID-19 pandemic response in the United Kingdom - Part 1 - The overall context.

The most common reaction to suggesting that we could learn valuable lessons from the way the current pandemic has been/ is being handled, is to discourage the attempt; as it is suggested that it can all be done more accurately and authoritatively after the inevitable Public Inquiry (Slater, 2019). On the other hand, a more constructive approach, is to capture and understand the work that was actually done.This would include normal activities, as well as positive adaptations to challenges and failures that may have occurred.

Will the COVID-19 pandemic transform infection prevention and control in surgery? Seeking leverage points for organizational learning.

Background: In response to the coronavirus disease of 2019 (COVID-19) pandemic, healthcare systems worldwide have stepped up their infection prevention and control efforts in order to reduce the spread of the infection. Behaviours, such as hand hygiene, screening and cohorting of patients, and the appropriate use of antibiotics have long been recommended in surgery, but their implementation has often been patchy.

Methods: The current crisis presents an opportunity to learn about how to improve infection prevention and control and surveillance (IPCS) behaviours.

Human factors/ergonomics to support the design and testing of rapidly manufactured ventilators in the UK during the COVID-19 pandemic.

Background: This paper describes a rapid response project from the Chartered Institute of Ergonomics & Human Factors (CIEHF) to support the design, development, usability testing and operation of new ventilators as part of the UK response during the COVID-19 pandemic.

Method: A five-step approach was taken to (1) assess the COVID-19 situation and decide to formulate a response; (2) mobilise and coordinate Human Factors/Ergonomics (HFE) specialists; (3) ideate, with HFE specialists collaborating to identify, analyse the issues and opportunities, and develop strategies, plans and processes; (4) generate outputs and solutions; and (5) respond to the COVID-19 situation via targeted support and guidance.

Results: The response for the rapidly manufactured ventilator systems (RMVS) has been used to influence both strategy and practice to address concerns about changing safety standards and the detailed design procedure with RMVS manufacturers.

Using FRAM to explore sources of performance variability in intravenous infusion administration in ICU: A non-normative approach to systems contradictions.

Systems contradictions present challenges that need to be effectively managed, e.g. due to conflicting rules and advice, goal conflicts, and mismatches between demand and capacity.

Digital health and patient safety: Technology is not a magic wand.

The use of novel health information technology provides avenues for potentially significant patient benefit. However, it is also timely to take a step back and to consider whether the use of these technologies is safe - or more precisely what the current evidence for their safety is, and what kinds of evidence we should be looking for in order to create a convincing argument for patient safety. This special issue on patient safety includes eight papers that demonstrate an increasing focus on qualitative approaches and a growing recognition that the sociotechnical lens of examining health information technology-associated change is important.

Development and piloting of a software tool to facilitate proactive hazard and risk analysis of Health Information Technology.

Health Information Technology is now widely promoted as a means for improving patient safety. The technology could also, under certain conditions, pose hazards to patient safety. However, current definitions of hazards are generic and hard to interpret, particularly for large Health Information Technology in complex socio-technical settings, that is, involving interacting clinical, organisational and technological factors.