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MyChart: doctors are left frustrated and patients panic as NHS trusts roll out hospital records app

US tech giant Epic’s hospital records portal has been rolled out by NHS trusts in England. But amid poor integration with the NHS App and low user literacy, users say it causes as many problems as it …

Palantir: Coalition urges NHS organisations to refuse to use controversial tech giant’s software

Every hospital in England has been urged to disobey an NHS directive to use software operated by controversial US analytics software company Palantir. A coalition of human rights, health and patient o …

“Technostress”—the NHS is overloading doctors with devices

Doctors are carrying more and more hardware. Each device is designed to do a job, but together they are giving clinicians “alarm fatigue”—to the detriment of patient safety. Chris Stokel-Walker report …

Getting published: ask editor Helen Surana

What was your journey to becoming co-editor-in-chief of BMJ Innovations? I’m a classic portfolio doctor, and have spent a lot of my career at BMJ Group. I’ve worked on BMJ Learning, BMJ Best Practice, …

Three years ago, Modesta Bene, aged 13, failed her school exams in rural Malawi. No one knew it yet, but Modesta was capable. She just couldn't hear. In January 2020, a Malawian doctor diagnosed Modes …

Ask the editor: 60 seconds with Dr Felix Holl

BMJ Group recently launched BMJ Connections Digital Health & AI, an open-access journal that sits alongside BMJ Digital Health & AI. Both journals publish original research, but the Connections journ …

Mobile-accessible deep learning-based self-assessment tool for measles screening in low-resource settings

What is already known on this topic Measles is highly contagious and poses serious health risks, particularly to young children. Global vaccination coverage declined in 2023, with only 83% receiving t …

Priorities for artificial intelligence education: clinicians’ perspectives

Clinicians are most likely to be motivated to learn about AI framed around its liability implications and determining appropriate confidence in AI algorithms, as these are perceived as important and c …

The impact of skin tone on performance of pulse oximeters used by NHS England COVID Oximetry @home scheme: measurement and diagnostic accuracy study

Arterial haemoglobin oxygen saturation (SaO2) indicates the fraction of oxygenated haemoglobin, relative to total haemoglobin, in arterial blood and provides a useful indicator of hypoxaemia (low bloo …

Déjà vu in healthcare AI: lessons from the world’s pioneer AI clinical decision support system

Recent advances in artificial intelligence (AI) have renewed interest in the possibility of computers assisting, or even replacing, doctors in making clinical decisions. However, computerised clinical …

Impact of acoustic and informational noise on AI-generated clinical summaries

The CAIS generally excelled at capturing a doctor-patient consultation and producing accurate clinical summaries; however, error rate (especially omissions) increased notably when acoustic noise was i …

Clinical AI Scribes in primary care: accuracy, error severity and implications for clinical practice

The CAISs demonstrate high levels of summarisation accuracy. However, there is great disparity between the currently available CAIS products and, while some perform well, none are perfect. Clinicians …

Predicting cardiovascular events from routine mammograms using machine learning

A deep learning algorithm based on only mammographic features and age predicted cardiovascular risk with performance comparable to traditional cardiovascular risk equations. Risk assessments based on …

Early clinical evaluation of a machine-learning system for risk prediction of trauma-induced coagulopathy in the prehospital setting

Early after injury, an ML system performs well compared with expert prehospital clinicians in the prediction of TIC and blood transfusion. The study suggests that ML systems may augment clinical risk …

“How long until I am seen, doc?” Modelling paediatric emergency department waiting times to make personalised predictions

Tailored models created using routine data can be used to give individualised predictions for wait times in paediatric ED, which could be given to patients with the aim of managing expectations and im …

Transforming women’s health through innovation

This BMJ Collection, developed in partnership with Bill and Melinda Gates Foundation, consists of 11 papers. It provides analysis and commentary on the growing global women's health innovation movemen …

Ask our Chief Technology Officer: Ian Mulvany

Ian Mulvany, chief technology officer at BMJ Group, is convinced that AI will transform processes related to the creation of knowledge, particularly academic papers. Wiley on AI recently interviewed M …

Ask our researcher: Fiona Mckenzie on the unexpected drivers of innovation

Original Research: Facilitating innovation in healthcare: insights from the front-line of adoption. A recent study published in BMJ Innovations examined the factors that drive the adoption and scaling …

Unintended consequences of using ambient scribes in general practice

Abi Eccles and colleagues argue that better evidence is crucial to ensure widespread adoption of ambient scribes does not compromise quality of care Ambient scribes have rapidly attracted internationa …

Facilitating innovation in healthcare: insights from the frontline of adoption

Innovation has long shaped healthcare but the art of adopting innovation remains a challenge. In the UK’s National Health Service (NHS), a system founded on the principles of continuous improvement an …

MyChart: doctors are left frustrated and patients panic as NHS trusts roll out hospital records app

Palantir: Coalition urges NHS organisations to refuse to use controversial tech giant’s software

“Technostress”—the NHS is overloading doctors with devices

Getting published: ask editor Helen Surana

Meet Dr Tamsin Holland Brown

Ask the editor: 60 seconds with Dr Felix Holl

Mobile-accessible deep learning-based self-assessment tool for measles screening in low-resource settings

Priorities for artificial intelligence education: clinicians’ perspectives

The impact of skin tone on performance of pulse oximeters used by NHS England COVID Oximetry @home scheme: measurement and diagnostic accuracy study

Déjà vu in healthcare AI: lessons from the world’s pioneer AI clinical decision support system

Impact of acoustic and informational noise on AI-generated clinical summaries

Clinical AI Scribes in primary care: accuracy, error severity and implications for clinical practice

Predicting cardiovascular events from routine mammograms using machine learning

Early clinical evaluation of a machine-learning system for risk prediction of trauma-induced coagulopathy in the prehospital setting

“How long until I am seen, doc?” Modelling paediatric emergency department waiting times to make personalised predictions

Transforming women’s health through innovation

Ask our Chief Technology Officer: Ian Mulvany

Ask our researcher: Fiona Mckenzie on the unexpected drivers of innovation

Unintended consequences of using ambient scribes in general practice

Facilitating innovation in healthcare: insights from the frontline of adoption

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