Finalist

intuitive decision support for surgical wounds healing by secondary intention (iSWHSI)

Bharadhwaj Ravindhran, NHS Humber Health Partnership

Surgical wounds that heal slowly can cause major challenges for patients and the NHS, leading to long recovery times, repeated clinic visits, avoidable treatments and significant emotional and economic strain. Our project, iSWHSI, aims to transform this journey. iSWHSI is an AI powered clinical decision support tool designed to help clinicians and patients better understand how complex wounds are likely to heal. Using routine clinical information and safely anonymised wound images, the system provides clear, personalised predictions about healing time and risks; supporting shared decision making and enabling earlier, more effective care. The tool has already been developed and internally validated using six years of real NHS data. It shows strong accuracy and offers transparent, explainable insights rather than “black box” outputs. We now seek to test iSWHSI across multiple NHS settings in a prospective study. The expected benefits include improved patient experience, fewer unnecessary treatments, reduced inequalities, and substantial cost and carbon savings for the NHS.

Finalist

Personalised and precision medicine in patients with inherited lipid disorders

Anna Beattie, Newcastle Upon Tyne Hospitals NHS Foundation Trust

Patients with inherited lipid disorders are at high risk of cardiovascular disease, yet assessment is traditionally based on population-derived risk factors rather than direct disease measurement. With the introduction of NICE-approved injectable lipid lowering therapies, identifying coronary artery disease is now critical for treatment eligibility, although advanced subclinical atherosclerotic disease may be present in patients who are asymptomatic.
This project introduces cardiac CT screening combined with AI-enabled plaque analysis to detect, quantify, and characterise coronary atherosclerosis. This represents an innovative, data-driven approach that shifts care from risk prediction to direct disease assessment, improving access to treatment and supporting personalised, precision medicine.
By aligning advanced diagnostics with emerging therapies, this pathway facilitates earlier intervention, delivers measurable clinical impact, and ensures patients receive appropriate treatment based on actual disease burden rather than estimated risk

Finalist

MammoBot: Robotic Posture Assistance for Universal Breast Screening Access

Roisin Bradley, York and Scarborough Teaching Hospitals NHS Foundation Trust

NHS breast screening with X-ray mammography saves around 1,300 lives annually across the UK. However, this service remains inaccessible to many women with reduced upper-body strength, including those with spinal injuries, multiple sclerosis, or frailty. Current NHS guidance acknowledges that successful mammograms are unachievable for women “unable to hold the required position” and, as “mammography is the evidence-based method of detecting cancer, it is not possible to offer an alternative”. In 2022/23, NHS England reported 2,859 incomplete mammograms due to restricted mobility, over 8,500 women in three years. To tackle this inequity, we are developing a dual-arm robotic system designed to help individuals with limited upper-body strength achieve and maintain the necessary position for mammography. Our aim is to improve access to breast cancer screening and diagnosis for those currently excluded and to enhance diagnostic quality for individuals who can only tolerate partial imaging.

Finalist

Early Intervention Vocational Rehabilitation Linked to Primary Care Fit Notes

Faye Peary, NHS Multi-System Rehabilitation Service, Airedale NHS Foundation Trust

The Vocational Rehabilitation Pathway within the Multi-System Rehabilitation Service is an NHS initiative helping people stay in or return to work when health conditions affect employment. Traditionally, patients receive a Med3 fit note but limited support, increasing the risk of long-term sickness.

This pathway provides early intervention, linking fit notes to a self-referral service offering specialist support through group programmes, one-to-one sessions, and tailored work-focused rehabilitation.

Since July, 164 patients have received 938 appointments and 42 group sessions, with 90% returning to work.

The model also offers employer resources and a national educational animation to improve understanding of vocational rehabilitation. Scalable and effective, it has the potential to enhance health outcomes, reduce economic inactivity, and transform NHS rehabilitation.

Finalist

The rapid access to parathyroid surgery (RASP) pathway in severe primary hyperparathyroidism

Saba P Balasubramanian, Sheffield Teaching Hospitals NHS Foundation Trust

Primary hyperparathyroidism (PHPT) is a condition where overactive parathyroid glands cause high calcium levels in the blood (hypercalcaemia). Severe hypercalcaemia can be dangerous and often requires emergency hospital treatment. In the NHS, these patients are usually stabilised in hospital and then go through multiple outpatient appointments, scans and tests before surgery. This process can take several months, during which patients remain unwell and are at risk of repeated hospital admissions and complications.
We have developed a new rapid pathway that identifies suitable patients early during their initial admission, completes necessary tests and scans promptly, and prioritises them for surgery within weeks rather than months. This approach reduces delays, avoids repeated hospital visits, and improves patient outcomes while also reducing pressure on NHS resources.

Finalist

SOBS: A New Model for Integrated Obesity and Bariatric Care

Sophie Bradshaw, MY Specialist Obesity and Bariatric Service, Mid Yorkshire Teaching NHS Trust

Previously, the bariatric service operated through a tiered pathway, with patients progressing sequentially through tiers 2 to 4 where they are considered for surgery. While this model was intended to provide structured escalation of care, in practice it generated system-level challenges that limited effectiveness and equity. Taken together, these issues were not about individual services or teams - but a pathway that had become disjointed, inefficient, and misaligned with population need. The decision was made to develop a new model where patients requiring specialist care are referred directly to The Specialist Obesity and Bariatric Service (SOBS).
Despite launching just in June 2025, early findings suggest SOBS meets patient needs more effectively and efficiently by delivering a fully integrated MDT service, including a 12-week pre-surgery group programme, within an accelerated timeline. Positioning SOBS as an innovative, scalable model with expected improvements across post-operative outcomes, as well as implications for policy development.

Finalist

The Who Done It, Delirium

Emily Hitchens, Somerset NHS Foundation Trust

The Who Done It, Delirium is a hands on case study training package in the style of a murder mystery crime kit. It was created December 2023 and is used within training sessions and doctors foundation training. The idea is to contextualise the learning of 'PINCH ME' the reversible causes of delirium, supporting and raising the confidence in clinical staff's recognition and identification of delirium in our most vulnerable patient group.

Finalist

Respirafibre - next generation breathing monitoring to improve patient care

Robert Tidswell, University College London Hospital

One in three NHS patients become more unwell and deteriorate during their stay, needing longer in hospital and tripling treatment costs. Late recognition is common and contributes to 8000 deaths per year. Early recognition of deterioration is critical to limiting these impacts. Changes in breathing rate are the earliest indicator something is wrong, altering hours to days before drops in blood pressure and oxygen levels.
Yet on hospital wards, breathing rate is only checked every 4-12 hours and over 70% of measurements are inaccurate. Existing breathing monitors are too expensive and uncomfortable so busy staff must count breaths manually. This is difficult and time-consuming so frequently ‘guesstimated’ or simply not done.
This creates unacceptable risk to patients, so we have developed Respirafibre – a continuous, accurate, affordable breathing monitor. The breathing sensor is embedded in oxygen masks and nasal prongs high-risk patients are already wearing, providing early detection of deterioration without the need for another device.

Finalist

HELP Flag (High or Elevated Level of Platelets) Pathway Project

Timothy McDonald , Royal Devon University Healthcare NHS Foundation Trust

The High or Elevated Level of Platelets (HELP) Flag Pathway project uses a data-driven approach to support early detection of potential cancer in primary care by analysing routine blood tests and alerting GPs to warning signs. Funded by SBRI Healthcare and led by the University of Exeter in partnership with the Royal Devon University Healthcare NHS Foundation Trust, HELP Flag uses an algorithm to apply personalised age and sex-adjusted thresholds to platelet results, built into existing NHS pathology laboratory systems. When results meet HELP Flag criteria, a digital alert appears in GP systems, prompting monitoring, further tests or referral. HELP Flag is seamlessly integrated into existing laboratory and clinical workflows, enabling timely investigation and referrals while supporting earlier diagnosis. HELP Flag is now live in 60 GP practices in Devon and has expanded to Liverpool, with a further evaluation underway which will help shape widespread national adoption.

Finalist

Pathways App

Seán Harte, John Howard Centre, East London NHS Foundation Trust

The Pathways App is a clinician-led digital innovation developed within East London NHS Foundation Trust (ELFT), co-produced with service-users, staff and carers over 3.5 years. Designed to give service users visibility of their own recovery pathway, the app enables them to track milestones and target barriers that are blocking progress. What began as a co-produced recovery tool evolved into a full digital pathway platform addressing one of the most persistent challenges in secure and complex mental health services: delayed progression caused by siloed operational data. The app has been showcased at over 30 conferences across the UK and has won multiple awards, including the 2024 Royal College of Psychiatrists "Psychiatric Team of the Year: Digital Mental Health Award’ and Highly Commended’ in the ‘Mental Health Innovation of the Year’ category at the 2025 HSJ Awards. The team also have a place on the NHS Clinical Entrepreneur Programme.

Finalist

Score Targetted Enhanced Bowel Preparation Distribution

Dhanushan Gnanendran, York and Scarborough Teaching Hospitals NHS Foundation Trust

This project aims to improve the success of colonoscopy tests by helping more patients arrive with the right bowel preparation first time. Poor bowel preparation is a common problem that can make it harder to detect bowel disease or cancer, and often means patients need to repeat the procedure. The project uses a simple scoring approach during routine pre-assessment to identify people who are more likely to need extra support or a stronger preparation plan. Early pilot work has already shown promising results, with fewer poorly prepared procedures and fewer repeat colonoscopies. The project is now moving from local pilot work towards wider rollout and evaluation across multiple NHS sites. Expected benefits include a better experience for patients, fewer unnecessary repeat tests, earlier and more reliable diagnosis, and better use of limited endoscopy capacity within the NHS.

Finalist

Sexually transmitted infection screening and treatment: improving quality of care on a female psychiatric inpatient ward

Dr Marlene Kelbrick, Northamptonshire Healthcare NHS Foundation Trust

People with mental health problems are at increased risk of developing sexually transmitted illness (STI). However, this patient group experience health inequality with regards to physical health screening and treatment, often underdiagnosed and under treated, compared to the general population. We developed an integrated care pathway model with patient and staff educational material, an STI screening questionnaire used, and offering STI screening as part of physical health assessment to all patients admitted to our female inpatient psychiatric unit, with early supported access to STI treatment (joint mental health and sexual health service pathway). This has been implemented and now embedded as part of routine practice for almost 9 months. We are currently conducting a post-implementation evaluation with regards to patient outcomes.

Finalist

Med Arcade: AI Platform Improving Diagnostic Safety from Fragmented Records

Bernard Cho, Med Arcade Ltd

Every clinician-patient encounter starts the same way: a clinician opening a fragmented, unstructured patient record and trying to piece together years of history in under ten minutes. That failure to synthesise drives over 15 million missed diagnostic opportunities annually, costing £3B in medical negligence claims in the UK.

Med Arcade fixes this problem. Our AI collates and digests the entire patient history, generating a clear clinical summary before the patient walks in. This allows clinicians to take in complex information in seconds, reducing cognitive load and improving decision safety.

The platform has undergone early testing in a Cambridge GP practice, showing significant reductions in review time and clicks, and has secured integration approval with NHS primary care systems. By surfacing critical information clearly and quickly, Med Arcade reduces missed diagnoses and supports safer care.

Finalist

VIOSync SPI: AI Digital Twin for 48-Hour Sepsis Prediction

Dr Ioannis Gkouzionis, Aisthesis Medical Ltd

VIOSync SPI is an AI-powered sepsis prediction platform developed by Aisthesis Medical Ltd. Built on a proprietary Digital Patient Twin architecture (TwinDx®), it continuously integrates multimodal clinical data, including vital signs, laboratory results, and clinical notes, to generate validated 48-hour early warnings of sepsis onset, paired with personalised, evidence-based care recommendations integrated directly into existing hospital workflows. Validated across 50,000+ patients at multiple UK and international hospital sites, VIOSync is NHS DTAC-approved, ISO 13485-certified, and CE MDR filing is underway (expected Q3 2026). By enabling clinicians to identify deteriorating patients significantly earlier than existing tools such as NEWS2, VIOSync SPI has the potential to reduce preventable sepsis mortality, shorten ICU stays, and improve patient safety outcomes at scale. NHS collaboration is with St George’s University Hospitals NHS FT, led by Prof Andrew Rhodes.

Finalist

Vital Vest: Wearable Continuous Lung Function Monitoring for NHS Patients

Dr Jack Callum, Pulmonary Dynamics

Vital Vest is a wearable garment that measures lung function continuously and without the need for specialised equipment or trained technicians. It uses sensors sewn into a compression vest to detect chest and abdominal movement during breathing, translating this into clinically meaningful measurements equivalent to spirometry — the standard lung function test used to diagnose and monitor conditions such as COPD, asthma, and interstitial lung disease (ILD).

Currently at proof-of-concept stage, with demonstrated correlation of r=0.88 against gold-standard spirometry across 150 measurements, the device is being developed by Pulmonary Dynamics Ltd. It is designed to address the profound inaccessibility of spirometry in the NHS, reduce diagnostic delays and misdiagnosis, and enable home-based continuous monitoring for patients who cannot access or perform traditional tests. A UK patent application covering 35 claims has been filed.

Finalist

Sensore: continuous and automated pressure ulcer prevention

Dr. Scott Dean, Sensore Ltd

95% of pressure ulcers are preventable - yet they still cost the NHS over £2.6 billion a year and cause immense patient suffering.
Sensore is changing that, using continuous and automated pressure mapping & smart repositioning alerts to predict and prevent pressure ulcers before they form, turning reactive care into proactive prevention. Sensore is a smart-fabric pressure sensor to continuously monitor, predict and prevent pressure ulcers before they form. It fits any seat or bed and continuously maps pressure distribution throughout the day, and our machine learning model develops personalised risk profiles for each individual user, alerting them when & how to reposition their weight to best prevent ulcer formation. Sensore is designed to support independence, improve comfort and empower better care decisions at home, in clinical settings, or on the go.

Finalist

Aliza Multidisciplinary Management System (AMMS)

Dr Syed Mansoor Yousuf, SMY MEDICAL LTD

Cancer MDT decisions are often made under significant time pressure using fragmented, unstructured information, increasing the risk of delay, variation, and missed opportunities for optimal care. This affects large numbers of patients across NHS cancer services.
AMMS is a clinician-led decision-support system that safely structures clinical information, highlights missing data, and supports more consistent MDT decision-making while maintaining full clinical oversight.
The system has been developed as a prototype using synthetic data and is soon to be integrated into clinical systems, through a carefully governed NHS pilot.
AMMS aims to improve decision quality, reduce delays, and support safer, more consistent patient care.