Digital Health Coffee Time Briefing ☕

  • 27 August 2024
Digital Health Coffee Time Briefing ☕

Your morning summary of digital health news, information and events to know about if you want to be “in the know”.

👇 News

🦾 Warwickshire NHS Trust has used a 3D-printed implant in a patient undergoing wrist surgery. The process involved scanning the patient’s wrist and then converting this into a 3D model that could be 3D-printed. Because the implant is custom-made, it fits the patient’s anatomy perfectly, meaning better functionality and better patient outcomes, the trust said.

📝 South Central Ambulance Service NHS Foundation Trust is looking to engage with suppliers interested in a procurement opportunity around medicines tracking. In a notice, published on 6 August 2024, the trust said it would be performing soft market research to inform their future procurement of an off-the-shelf electronic medicines tracking system to replace current, manual processes.

❤️‍🩹 Scientists in the US have designed a shunt for children born with heart defects that expands when activated by light. Shunts – plastic tubes designed to improve blood flow – are typically implanted at a young age and need to be replaced several times as the child grows. This new shunt expands when exposed to a blue light-emitting catheter, and is designed to reduce the need for children to undergo repeated and invasive, open-chest surgeries.

🩻 Royal Free Hospital NHS Foundation Trust has welcomed a new suite of “state-of-the-art” scanning equipment that will mean faster, more accurate diagnoses for patients. The upgrade includes three X-ray machines, three CT scanners and one MRI scanner, which combined will enable Royal Free’s radiology team to diagnose 11,000 additional patients every year.

💰 Digital health company Surgery Hero has been awarded a research grant of £700,000 from the National Institute for Health and Care Research to fund a three-year trial of its ‘digital surgery clinic’. Surgery Hero allows patients awaiting surgery to manage their care from home. This study aims to provide insights into whether digital interventions can enhance recovery and quality of life for patients undergoing major procedures.

Did you know?

One-third of US nurses suffering from burnout cite electronic health record (EHR) systems as a contributor, with 40% of these nurses planning to quit, a new report by the KLAS Collective as found.

The 2024 Arch Collaborative Nursing Guidebook included feedback from 75,000 nurses who reported their EHR satisfaction via the KLAS Arch Collaborative over the last three years.

It found that 33% of nurses who participated in the research reported burnout symptoms, with 32% of these nurses citing their organisation’s EHR as a contributor. Burned-out nurses were 192% more likely to leave their organisation within the next two years compared to those who don’t report experiencing burnout, the report found.

The reliability – or lack therefore – of EHR systems was identified as a major contributor to nurses’ dissatisfaction, with participants calling out slow loading times (68%), slow login processes (61%), hardware issues (57%) and unplanned downtime (36%) as their biggest bugbears. 

The report makes a series of recommendations for supporting nurses, including improving EHR system maintenance and offering more tailored training.

📖 What we’re reading

Researchers at the University of Massachusetts Amherst published a paper in August 2024 exploring how often large language models (LLMs) tend to hallucinate when producing medical summaries.

In the study, titled Faithfulness Hallucination Detection in Healthcare AI, the research team collected 100 medical summaries from OpenAI’s GPT-4o and Meta’s Llama-3 LLMs. In the 50 summaries produced by GPT-4o, the researchers identified 327 instances of medical event inconsistencies, 114 instances of incorrect reasoning and three instances of chronological inconsistencies. 

The research team found 271 instances of medical event inconsistencies, 53 instances of incorrect reasoning and one chronological inconsistency in the 50 summaries generated by Llama-3.

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