Let’s take a brief look at some of the stories that have caught our eye from the health tech industry over the last few days, from news from NHS trusts to recent health tech research from universities.
Princess Alexandra Hospital launches new electronic health record
The Princess Alexandra Hospital NHS Trust has announced the launch of their new electronic health record programme on Twitter, stating that it will “transform the way we provide care.”
In April, the trust announced that it had signed a 10-year agreement to modernise its hospital systems with Oracle Health EHR.
Another tweet shared the EHR timeline, with the project’s launch leading to a design and build phase expected to run from this month to January 2024; system testing to run until July 2024; staff training and full dress rehearsal to take place over August and September 2024; and go-live to occur in October 2024.
Phil Holland, chief information officer, said that the EHR is “a vital component of our huge digital transformation programme”, adding: “Not only will it provide numerous benefits and efficiencies – for patients and staff – it will underpin our vision to be the most digitally enabled hospital in the country. This will support the patient journey by using technology and digital solutions at every step, from arrival and wayfinding to scheduling and treatment.”
Barts Health to procure secure data environment
Barts Health NHS Trust has opened an opportunity to procure a secure data environment worth an estimated £550,000.
The deadline to apply is 10 August 2023 at 11am, with delivery of the contract set to run for one year between 29 August 2023 and 28 August 2024.
Suppliers interested in participating in the tender are encouraged to register and apply via the Atamis e-sourcing portal which can be found here.
Queen Mary University and University of Sussex create sustainable smart wearables
Researchers from Queen Mary University and the University of Sussex have used biodegradable materials to create smart wearable skin-on devices, capable of monitoring real-time biomechanical and vital sign measurements.
Inspired by techniques used in gastronomy, the scientists used seaweed and salt to create graphene capsules made up of a solid seaweed and graphene gel layer, surrounding a liquid graphene ink core. As the graphene capsules are very sensitive to pressure, their electrical properties “change dramatically” when squeezed or compressed.
“When assembled into networks, the tiny capsules can record muscular, breathing, pulse and blood pressure measurements in real-time with ultrahigh precision,” Queen Mary University states. As such, they can form an “electronic skin” and utilised as “highly efficient strain sensors”.
Dr Dimitrios Papageorgiou from Queen Mary University, says: “Our discoveries offer a powerful framework for scientists to reinvent nanocomposite wearable technologies for high precision health diagnostics, while our commitment to recyclable and biodegradable materials is fully aligned with environmentally conscious innovation.”
University College London Hospitals enables test results via patient portal
University College London Hospitals has enabled users of their patient portal to access test results online, either the day following the test or on a three-week delay in cases of complex results such as imaging reports.
Luke O’Shea, director of innovation, highlighted on Twitter that 180,000 patients are estimated to use the patient portal, and added that the development was motivated by patients requesting the functionality.
UCLH’s website has been updated to provide guidance and support for portal users around the change.
AI used to predict development of Parkinson’s from smart watch data
Researchers from the Cardiff University have discovered that by using artificial intelligence to analyse smart watch data, they could “accurately predict those who would go on to later develop Parkinson’s disease”.
Focusing on the data measuring speed of movement, the researchers compared a subset of participants who had already received a diagnosis of Parkinson’s to another group who had been diagnosed up to seven years after the smart watch data was collected. The AI algorithm was found to be capable of identifying participants who would later go on to develop the disease.
Dr Cynthia Sandor from the UK Dementia Research Institute at Cardiff University and leader of the study, said: “We have shown here that a single week of data captured can predict events up to seven years in the future. With these results we could develop a valuable screening tool to aid in the early detection of Parkinson’s. This has implications both for research, in improving recruitment into clinical trials, and in clinical practice, in allowing patients to access treatments at an earlier stage, in future when such treatments become available.”
