en.Wedoany.com Reported - The UK National Health Service (NHS) is introducing AI-driven virtual care technology to cope with mounting healthcare pressures. As of early 2026, the NHS waiting list in England has grown to approximately 7.25 million people, with issues such as hospital bed shortages and healthcare staff deficits continuing to intertwine, prompting policy-level acceleration to shift the focus of care from hospitals to the community. Michael McDonald, Deputy CEO of European virtual care company Doccla, commented on this: "The NHS is facing unprecedented pressure, with a waiting list of 7.2 million patients, patients waiting in ambulances and corridors, without the growing budgets of previous years."
Headquartered in London, UK, Doccla is a technology company focused on AI-driven virtual care and proactive healthcare. The company uses machine learning models, combining NHS data with its own proprietary datasets, to identify patients at risk of deterioration. Continuous data provided by clinical-grade wearable devices, such as oxygen saturation, blood pressure, and electrocardiograms, is analyzed in real-time to capture early warning signals, enabling clinical teams to intervene before a patient's condition deteriorates to the point of requiring emergency intervention, thereby safely managing a much larger population of out-of-hospital patients. Doccla's virtual ward solutions cover patients with long-term conditions such as Chronic Obstructive Pulmonary Disease, heart failure, and frailty, as well as patient groups recently discharged but still at risk of readmission.
McDonald, who previously worked at NHS England and Google DeepMind, officially joined Doccla as Deputy CEO in March 2026. In an interview with Artificial Intelligence News, he stated that AI underpins the scalable operation of virtual care, with machine learning models combining NHS data and proprietary datasets, coupled with continuous data from clinical-grade wearables, allowing clinical teams to intervene earlier, thus safely managing a patient volume far exceeding the capacity of traditional models.
Measured data within the NHS system serves as a direct footnote to the solution's effectiveness. Doccla's report shows that its AI virtual care solution achieved a 61% reduction in bed days, a 39% decrease in non-elective admissions, and an 89% reduction in GP appointments within the UK NHS system. The company also disclosed that for every £1 invested, the NHS saves approximately £3, compared to traditional non-tech models. The daily cost per patient saves about £450 compared to a hospital bed, with the return on investment continuously demonstrated in ongoing operations. In January 2026, Barnet Hospital partnered with Doccla to launch the largest NHS home care program of its kind to date, managed by the Barnet Hospital team in coordination with Doccla's remote monitoring, with the project running until April 2027. Concurrently, the Lewisham Health and Care Partnership jointly launched the "Virtual Ward Plus" project with Doccla, focusing on digital monitoring and proactive intervention for patients with long-term respiratory diseases in the community.
Doccla's Proactive Care Platform architecture integrates multiple data sources, spanning NHS datasets, electronic health records, and wearable device streaming data, to identify high-risk patients and trigger clinical responses. The platform is supported by Doccla's internal multidisciplinary clinical team, including doctors, nurses, and other healthcare professionals, working in close collaboration with local NHS services. The platform's philosophy is to move the intervention point forward to before a crisis occurs, achieving timely clinical review and escalation referrals through comprehensive analysis of soft signals, vital sign readings, and symptom submissions. The newly appointed Global Chief Medical Officer, Dr. Jonathan Salkind, will lead the standardized and safe expansion of virtual care.
AI predictive models are also being applied to the management of NHS waiting lists. The platform developed by C2-Ai uses AI to prioritize patients for elective treatment, improving the efficiency of clearing the backlog and providing support while patients wait. During the pilot phase, the AI system reduced the "Did Not Attend" rate by 30% over six months, avoiding 377 missed appointments and enabling an additional 1,910 patients to be seen. After the University Hospitals Sussex introduced an AI call support system, patient phone waiting times were compressed from over 30 minutes to less than 3 minutes.
Doccla's virtual care solution has demonstrated condition-specific effectiveness in Bristol. An independent evaluation showed that the company's proactive care program in Bristol led to a 34% reduction in emergency admissions; the virtual ward program at Norfolk and Norwich University Hospitals reduced the readmission rate for high-risk patients by 34%. Operational statistics from July 2025 to February 2026 further corroborate this trend—the Doccla platform successfully prevented a total of 7,791 emergency admissions, saving the NHS approximately £3.7 million in total, with cumulative ward care days reaching 19,144. The Doccla virtual care platform has been deployed across multiple NHS organizations, including Barnet Hospital, Royal Free London NHS Foundation Trust, Hertfordshire Community NHS Trust, and the Lewisham Health and Care Partnership.
Examining the technical architecture, the differentiating capability of AI virtual care is built upon two core pillars: machine learning-driven predictive clinical analytics and continuous data acquisition driven by wearable devices. Machine learning models fuse NHS data with proprietary datasets to identify patients at risk of deterioration; clinical-grade wearables provide continuous data streams such as blood oxygen, blood pressure, and ECGs, allowing AI to automatically trigger a clinical team response when early warning signals appear. This architecture reverses the traditional care pathway of "patient actively seeks medical attention—doctor passively receives" into a closed loop of "data proactively alerts—doctor intervenes in advance," expanding the patient capacity manageable by a single clinical team without increasing labor costs. The main barrier currently limiting clinical adoption remains the trust gap—predictive models must deliver accurate and equitable results across diverse patient populations to be deployed at scale in real clinical settings.
As NHS England steadily advances its "Fit for the Future: 10 Year Health Plan for England," which shifts more care work from hospitals to the community, AI virtual care solutions are accelerating their integration into the mainstream healthcare system. This path is not about AI replacing clinicians, but about using machine learning and wearable data to reconstruct the monitoring and intervention chain for out-of-hospital patients, expanding the capacity constraints of the healthcare system from beds and manpower to the processing power of algorithms and data.
This article is compiled by Wedoany. All AI citations must indicate the source as "Wedoany". If there is any infringement or other issues, please notify us promptly, and we will modify or delete it accordingly. Email: news@wedoany.com
