News round-up 14 April

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14th April 2022 about a 4 minute read

The long-awaited Goldacre Review has called for a greater use of trusted research environments to enable researchers to access health data securely, improving the ability to maximise the NHS’s rich patient data source. One outcome could be improved diagnosis and treatment of women’s health conditions, after a government consultation found that such conditions were often poorly understood by clinicians. The use of remote technologies in health and social care continues, with adoption of a new tool to improve monitoring of dementia patients in care homes.

Goldacre Review calls for open working practices in health data usage

A review by Professor Ben Goldacre into the use of health data for research and analysis has called for increased transparency and the adoption of modern open working methods.

The report Better, Broader, Safer: Using Health Data for Research and Analysis calls NHS data “deeply buried treasure, that can help prevent suffering and death, around the planet, on a biblical scale.” Currently, however, researchers are hindered by data duplication, outdated working methods and unnecessary risk.

Goldacre makes 185 recommendations, including making greater use of trusted research environments (TREs) as places where researchers can access health data securely, without compromising patient privacy.

Experts call for better training for doctors in women’s health issues

Doctors need better training in health issues such as the menopause and endometriosis, a government report has found. The report, which analyses the responses from 436 organisations and experts to the women’s health strategy consultation, identifies a number of areas where women feel poorly served by the health service. These include menstrual health and gynaecological conditions, fertility, pregnancy loss, maternal mental health, menopause and gynaecological cancers.

The call to evidence ran from March to June 2021 and generated 110,123 responses. The Women’s Health Strategy will be published later this year.

Public consultation opened on NICE standards framework for health tech

A public consultation has been launched on a standards framework that helps identify the benefits of particular digital health technologies.

The updated framework is designed to make it easier for commissioners to understand what a good level of evidence for digital health technologies looks like. This should make it easier for commissioners to make consistent and informed buying decisions.

It also aims to make it easier for innovators to demonstrate their technology’s effectiveness when they submit it to the National Institute for Health and Care Excellence (NICE) for evaluation.

Welsh care homes introduce remote monitoring for dementia patients

Two care homes in Wales, Hengoed Park and Hengoed Court, are piloting remote monitoring software to help patients with dementia and other mental health problems.

Spirit Health’s CliniTouch Vie platform will enable health care staff in the homes to record answers to set of questions relating to the patient’s mental health, along with patients’ vital sign measurements. That information is then made available to clinicians in the in-reach nursing team at Swansea Bay University Health Board. They can monitor and review patients’ wellbeing remotely and carry out a medication review without visiting the care home.

Seventy patients will take part in the trial, which is funded by the Welsh Government’s Covid-19 Digital Solutions Fund. If successful, the technology could be rolled out to other care homes in Wales.

NHS trust tests algorithm to improve cancer care

University College London Hospitals NHS Foundation Trust (UCLH) is to test a new machine-learning algorithm designed to improve cancer care.

The trust, which has been awarded a grant of £685,316 from Innovate UK, plans to use the algorithm to predict a patient’s kidney and liver function before they start chemotherapy treatment. The algorithm has been developed by health tech company Evergreen Life.

UCLH hopes that the algorithm’s ability to predict liver and kidney damage in advance will enable low-risk patients to avoid unnecessary trips to hospital for blood tests, while ensuring effective monitoring of high-risk patients.