The words \u201cpressure\u201d and \u201cNHS\u201d go hand in hand in the UK and unfortunately there is no sign of a reduction in the strain the institution suffers any time soon. As NHS England continues the struggle to reduce its 7.25 million waiting list, new policies are being introduced to move care away from hospitals and into the community, despite GPs\u2019 warning of increased workloads and risk to patients. Add in looming doctor strikes and deepening staff shortages and the backdrop of the health service does not look rosy.
\n In a bid to relieve some of the burden, AI-enabled virtual care is emerging as a tool to manage the growing number of patients outside hospital settings. The technology is being implemented to help around three important areas \u2013 waiting lists, hospital capacity, and corridor care.
\n Michael Macdonnell, Deputy CEO at European virtual care provider Doccla, who has first-hand experience working in the NHS, commented, \u201cThe NHS is facing unprecedented pressure, with a 7.2 million patient waiting list, patients waiting in ambulances and in corridors, without the growing budgets of previous years.\u201d
\n \u201cAI underpins how virtual care works at scale. Machine learning models are used to identify patients at risk of deterioration by combining NHS and proprietary datasets, while continuous data from clinical-grade wearables (e.g.oxygen saturation, blood pressure, ECG) is analysed to detect early warning signs. The lets clinical teams intervene sooner and safely manage far larger patient groups than would otherwise be possible.\u201d <\/p>\n
Doccla and virtual care<\/p>\n
Doccla is a company providing remote patient monitoring and virtual wards to NHS trusts. The Doccla model is \u201cdesigned both to support earlier discharge and to prevent avoidable admissions, particularly for those with long-term conditions.\u201d
\n There is already evidence for Doccla\u2019s effectiveness, with the NHS seeing a 61% reduction in bed days, an 89% reduction in GP appointments, and a 39% drop in non-elective admissions. Not only has this AI-driven software improved efficiency, it is also reportedly saving the NHS approximately \u00a3450 a day compared with the cost of a hospital bed, the company says. Figures suggest that for every \u00a31 spent on such technology, the NHS saves an estimated \u00a33 compared with non-tech models.
\n Mr Macdonnell said, \u201cAt Doccla, we use machine learning to identify patients at risk of deterioration before they reach crisis point. Continuous data from clinical-grade wearables like oxygen saturation, blood pressure and ECGs, are analysed with medical records to detect early warning signs.\u201d
\n The insights are allowing clinical teams to intervene sooner and manage larger caseloads compared with more traditional systems. AI may also be having a positive effect on clinician\u2019s mental states, helping reduce administrative burden. For instance, large language models (LLMs) are being used to streamline clinical notes and present complex information to patients in a more accessible way. AI is not expected to replace clinicians, only make them more effective, so clinicians reading this can breathe a sigh of relief.
\n Clinical trust in this technology remains low and this will only grow through transparency and further evidence of success. Predictive models must also deliver accurate and fair outcomes in diverse patient groups before being deployed at scale in real-world clinical settings.
\n As the UK\u2019s NHS works to move more care away from hospitals and into the community, with its \u201cFit for the Future: 10 Year Health Plan for England,\u201d AI stands at the forefront of this transformation. The future of AI healthcare is set to allow patients to remain more independent and receive the care they need in familiar surroundings.
\n(Image source: Pixabay under licence.)
\n\u00a0<\/p>\n
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The words \u201cpressure\u201d and \u201cNHS\u201d go hand in hand in the UK and unfortunately there is no sign of a reduction in the strain the institution suffers any time soon. As NHS England continues the struggle to reduce its 7.25 million waiting list, new policies are being introduced to move care away from hospitals and [\u2026]<\/p>\n
The post AI helping ease the UK\u2019s NHS burden<\/a> appeared first on AI News<\/a>.<\/p>\n<\/div>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-container-style":"default","site-container-layout":"default","site-sidebar-layout":"default","disable-article-header":"default","disable-site-header":"default","disable-site-footer":"default","disable-content-area-spacing":"default","footnotes":""},"categories":[1,403,401,1120,866,1121],"tags":[3],"class_list":["post-2952","post","type-post","status-publish","format-standard","hentry","category-ai-and-ml","category-healthcare","category-healthcare-wellness-ai","category-medtech","category-nhs","category-uk","tag-ai"],"yoast_head":"\n