The last 5 years have seen a rapid growth in research applying artificial intelligence or machine learning to improve the quality and safety of healthcare. This coincides with the release of web interfaces (such as ChatGPT from OpenAI and Copilot from Microsoft) that have enabled the general public (including health professionals and researchers) to easily access the latest generation of large language models (LLMs).

LLMs have fundamentally changed how machine learning is used across domains. Unlike previous generation systems that required careful data curation for specific tasks before training, modern LLMs work well with just a few examples or a simple problem description. This progress is mainly due to training on large volumes of web data that allows them to develop an ‘understanding’ of both language and general knowledge which they can then apply to a wide range of tasks.1

To fully comprehend the capabilities and associated...

Performance problems among healthcare professionals can have significant implications for patient safety. Estimates suggest approximately 6–12% of physicians experience performance issues,1 while about one in three healthcare professionals report encountering a poorly performing colleague within the past year.2 Performance problems can arise from individual-level causes including physical illness, substance use disorders, cognitive impairment, mood or personality disorders, and failure to acquire or maintain the knowledge and skills necessary to safely carry out their responsibilities.3 Furthermore, broader systemic issues, including excessive workloads, inadequate resources, lack of institutional support and poor workplace culture, can contribute to or exacerbate performance problems.4 The performance of healthcare professionals is generally evaluated against a set of standards or core competencies of a particular profession that commonly require health professionals to maintain the knowledge, procedural proficiencies, communication skills and professionalism to effectively care for patients. Deficiencies in any...

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.

Methods

We conducted qualitative semi-structured interviews with 20 senior multidisciplinary healthcare professionals from intensive care units (ICUs) in 4 major hospitals in the UK. The interviews explored the everyday pressures faced by intensive care staff and the strategies they use to adapt. A thematic template analysis approach was used to analyse the data based on our previously empirically developed taxonomy of pressures and strategies.

Results

The principal source of pressure described was a shortage of staff with the necessary skills and experience to care for the increased numbers and complexity of patients which, in turn, increased staff workload and reduced patient flow. Strategies were categorised into anticipatory (in advance of anticipated pressures) and on the day. The dynamic and unpredictable demands on ICUs meant that strategies were mostly deployed on the day, most commonly by flexing staff, prioritisation of patients and tasks and increasing modes of communication and support.

Conclusions

ICU staff use a wide variety of adaptive strategies at times of pressure to minimise risk and maintain a reasonable standard of care for patients. These findings provide the foundation for a portfolio of strategies, which can be flexibly employed when under pressure. There is considerable potential for training clinical leaders and teams in the effective use of adaptive strategies.

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The FDA is warning about the risk of a rare but serious allergic reaction with the medicine glatiramer acetate (Copaxone, Glatopa), which is used to treat patients with multiple sclerosis (MS). This serious allergic reaction, called anaphylaxis, can occur at any time while on treatment, after the fi