Some exciting news this week about innovation, as researchers develop mathematical models that could lead to a simple blood test for the most common type of brain cancer, while the NHS launches a programme using artificial intelligence to identify patients with risk factors for hepatitis C. But there are yet more revelations about long waits in A&E and a backlog of a million people waiting for community health services.
Several NHS trusts are reporting thousands of 12-hour waits in their A&E departments – far more than recorded in the nationally-published statistics, which use a different measure.
National figures are compiled using the publicly-reported trolley wait figures, which count waits of more than 12 hours from the decision to admit until admission.
This year, however, trusts are required under their standard contract to record the number of patients waiting more than 12 hours from the time they arrived in A&E until discharge, admission or transfer. Many trusts are now reporting these statistics in their public board reports.
HSJ collated the new data from 20 of the largest trusts and compared it with the publicly reported trolley wait figures. It found that some trusts, including Liverpool University Hospitals Foundation Trust, Manchester University FT and Mid and South Essex FT, reported thousands of cases captured under the new measure, compared with tens of cases under the official trolley wait figures.
The NHS has launched a pilot programme that could see thousands more patients given access to potentially life-saving treatment for Hepatitis C.
The new initiative, which will use artificial intelligence (AI) to scan patients’ health records for risk factors such as historical blood transfusions or an HIV diagnosis, will begin next month. It could help up to 80,000 people, who are unknowingly living with the virus, to receive a diagnosis and therefore start treatment sooner.
Anyone identified through the screening process will be invited for a review by their GP and, if appropriate, further screening for hepatitis C. Those who test positive for the virus will be offered treatment that could over time save thousands of lives. In 2020, 314 people died from the condition in England.
More than a million people are on an unpublished national waiting list for community health services, according to NHS England documents leaked to HSJ.
The documents show that more than 321,000 adults are on the list waiting for musculoskeletal services, mostly physiotherapy such as for back and joint pain, while 120,000 are waiting for podiatry.
Just over 75,000 children are waiting to access community paediatric services, including children needing help with developmental delay, long-term health conditions and additional needs. There is also a backlog of more than 74,300 young people for speech and language therapy.
NHS England has launched a project to support heart failure patients with the tools they need to monitor their condition at home.
The initiative, Managing Heart Failure @home, is designed to minimise face-to-face appointments for these patients and reduce unavoidable hospital stays and readmissions.
There are three core elements to Managing Heart Failure @home: personalised care, including equipping patients with the skills they need to manage their own health; remote support and monitoring through the use of technology; and integrated care, which involves better co-ordination between primary, community and secondary care.
Research at the University of Bristol could lead to the development of a simple blood test for glioblastomas (GBMs) – the most common type of brain cancer.
The blood test could detect the cancer earlier, leading to more effective treatment options.
The research, published in the Journal of the Royal Society Interface, involved the development of mathematical models to assess the current use of blood-based biomarkers in the detection of GBMs. Biomarkers are biological molecules that can indicate the presence of an illness such as cancer.
Pairing mathematical models with experimental data, the researchers found that for one particular GBM biomarker called Glial fibrillary acidic protein (GFAP), it was possible to lower the current detection threshold. The ability to detect the presence of GFAP would allow clinicians to use blood tests to identify GBMs at an earlier stage.