HN has this week launched an exciting and innovative new co-investment fund for NHS trusts and ICBs.
The offer is open to the first ten NHS organisations to express an interest in HN’s proven AI-based programme, which has demonstrated significant system savings across hospital capacity, urgent and elective admissions, and improved patient safety scores and outcomes.
HN’s unique offer is our AI-Guided Clinical Coaching (AICC) programme, which combines data scientific and AI capabilities with digital services, and is delivered by skilled healthcare professionals. The AICC model enables organisations to accurately identify patients at risk of adverse and preventable events such as uncontrolled disease progression, hospitalisation and prolonged hospital stay. It is proven to help restore and recover ailing urgent and emergency care services.
HN is delighted to committed its feasibility study – a detailed analysis of healthcare consumption patterns including patient demographics and inequalities data, and worth up to £90,000 per ICS – to be included as part of this wave 2 scheme. The deadline to register for the new programme is 31 June 2023 in order to be eligible for the innovation fund.
With recent figures showing a waiting list of over 7m, in addition to record numbers of patients waiting more than 12 hours for treatment at A&Es, HN’s innovation fund provides a unique opportunity to support the restoration of urgent and emergency services.
The clinical evidence behind the offer
HN is launching this new scheme following a successful trial of its AI programme, which ran from 2015 to 2022. The randomised controlled trial (RCT) operated across eight acute NHS trusts in England including York Teaching Hospitals NHS Trust and Staffordshire & Stoke-on-Trent ICS. A total of 1,800 patients were enrolled on the trial, identified by HN’s AI tool as being at high risk of using urgent and emergency care services in the next few months. These patients were offered a personalised coaching service over the telephone. Delivered by registered healthcare professionals, the service is designed to support patients with complex conditions and empower them to take control of their health, thus reducing A&E admissions and unplanned emergency care. This moves away from a purely reactive model and has the potential for more person-centred care.
The findings of the trial directly resulted in a 35% reduction in A&E attendances and a 30% reduction per patient in the average total hospital care cost, at one of the trial sites in Staffordshire ICS. Results from other sites show a similar positive impact, in some cases demonstrating up to 59% reduction in unplanned admissions for patients receiving the intervention.
In a clinical trial published in the British Journal of General Practice, one out of four referrals to hospital identified by the AI tool could be prevented by supporting these high-risk patients, with nurse-led, virtual ward support. Patients supported through this novel predictive and preventive clinical pathway also reported increased quality of life, improved physical health and increase in their ability to manage their health conditions.
HN’s analysis also shows a significant positive impact on survival rates of those patients enrolled onto its programme. The full analysis is expected to be published in a peer-reviewed journal before Summer 2023.
Dr Joachim Werr, Founder and Executive Chair of HN said:
“The launch of this new co-investment offer represents an important opportunity for the NHS to embrace AI and machine learning tools proven to have a positive impact on patients and the system alike. Our lengthy and robust trial with the Nuffield Trust has demonstrated that patient outcomes are improved by intervening in a timely and appropriate manner, giving them the confidence and support to live well, at home. With the pressures on the NHS becoming an increasing year-round phenomenon, we are well equipped and can rapidly roll out this important technology to save lives and improve the urgent and emergency care system before winter comes around”.
Mark England, CEO of HN, said:
“By arming ICSs with data and prediction technology, we can begin to manage health and care in a more sustainable and impactful way that delivers better patient outcomes whilst saving costs. Those living with long term conditions and advancing frailty will inevitably increase, so as part of this model we need to shift the focus to patient self-management, through proven methods such as health coaching. HN’s work in this area shows a model that can work and we are excited to scale our work with NHS partners and make an instant and lasting impact to health systems across the country.”
Dr Paddy Hannigan, Chair of the Stafford and Surround CCG and Clinical Lead for Staffordshire & Stoke-on-Trent ICS Digital Programme, said:
“HN’s offer was transformational for us in Staffordshire and it is applicable to every ICS across the country. Data can play a huge role for the NHS if it is collected, analysed and acted upon in the right way. The key to our work with HN was the data-driven case-finding. By using data to better forecast demand and predict outcomes we were able to manage the resources we had accordingly, and of those patients on the intervention, reduce hospital care costs by 30% per patient.”
The potential impact for NHS and its patients
With 25-35% of urgent and emergency care being deemed avoidable and costing the NHS £6 billion annually, the project, through the RCT, has demonstrated that improvements in the patient experience can lead to reduced demand for healthcare services.
Using predictive models to risk-stratify key population segments is a critical approach to delivering the anticipatory care that is at the heart of the NHS Long Term Plan.
If applied to the NHS as a whole, the technology and related clinical nurse-led services, could prevent 5-7% of all unplanned hospital care and save £2,200 per patient. It would require the technology to be made available to the 1-5% of patients with the highest risk of clinical crisis and unplanned care.
Get in touch to find out more
To register your interest in the scheme, complete the short form below.