Best Digital Partner

Winner:

Calderdale and Huddersfield NHS FT
To improve controlled drug (CD) management, CHFT partnered with Solidsoft Reply to create a digital CD Register for Huddersfield Royal Infirmary and Calderdale Royal Hospital. Traditional paper logs are error-prone and inefficient, especially in high-pressure settings like emergency departments. The new electronic system integrates with existing NHS systems, capturing essential workflows for pharmacy, wards, and clinical areas to ensure real-time oversight and compliance.

After extensive testing, staff received comprehensive training, with ongoing feedback driving enhancements. The solution has significantly improved CD documentation accuracy, reduced time delays, and streamlined compliance, creating a safer, more efficient drug management process.

Finalist:

Central London Community Healthcare NHS Trust with Arjo 
CLCH and Arjo introduced the Provizio® SEM Scanner to reduce pressure ulcers by detecting risks up to five days before visible signs appear. This handheld device allows early intervention, improving patient outcomes and safety. Following a rise in pressure ulcers at two CLCH units, Arjo provided scanners and extensive staff training, including designated “SEM coaches” for ongoing support. The scanner informed clinical decisions for over 79% of nurses, detecting early damage even when skin looked healthy. This initiative improved patient care and engagement while positively impacting staff workload, morale, and overall care quality at CLCH. 

Entries have been summarised in less than one hundred words using artificial intelligence

Digital Practice of the Future

Winner:

Central London Community Healthcare NHS Trust
The Provizio Sub-Epidermal Moisture (SEM) scanner helps prevent pressure ulcers (bedsores) by detecting early signs of tissue damage up to five days before visible symptoms appear. This handheld, non-invasive device identifies areas at risk, allowing nurses to intervene earlier and improve patient outcomes.

A quality improvement project in Brent Rehabilitation Wards integrated the SEM scanner into standard care through targeted training, improved documentation, and regular audits, achieving a 90.5% reduction in ulcer incidence. This project’s success demonstrates the SEM scanner’s effectiveness in reducing pressure ulcers and costs, with findings shared across the Trust and on the Life QI platform.

Finalists:

Cambridge University Hospital
This entry proposes a wireless monitoring system to improve neonatal transport care. Currently, documenting infant vital signs during emergency transfers can delay direct nursing care due to connectivity and manual data input challenges. A small study tested wireless monitoring of ECG, temperature, and pulse oximetry, allowing real-time remote viewing of data with minimal data loss. Participants agreed that this system could reduce risks from tangled wires and improve efficiency.

The goal is to develop a device that wirelessly links vital signs and IV infusion data from monitors directly to electronic health records, streamlining care for neonates in transit.

Surgery AI
SurgeryAI is a digital solution designed to improve efficiency and reduce delays in operating theatres through smarter scheduling. By using machine learning, SurgeryAI accurately predicts surgery durations based on factors like surgeon performance and patient characteristics, resulting in a 5-10% improvement in theatre utilisation. This allows more surgeries to be completed without extra resources, easing pressure on healthcare staff and reducing patient waiting times.

With features to track surgical materials, SurgeryAI further streamlines operations. Ready for real-world testing, SurgeryAI aims to enhance patient care, reduce staff burnout, and optimise resource use across healthcare systems globally.

Entries have been summarised in less than one hundred words using artificial intelligence

Digital Practice: Proven Concept

Winner:

Priory
Priory's new Preceptorship Programme replaces a traditional paper-based system with an AI-assisted online portal for flexible, continuous nurse training. Launched in partnership with Breeio, the digital platform provides self-paced learning, skills assessment, and AI-driven reflection and goal-setting tools aligned with NHS England’s framework.

These enhancements, including modules on Clinical Practice and Leadership, enable preceptees to tailor their development and transition effectively from students to registered professionals. Since implementation, participation has doubled, with ongoing support and plans for further interactive features like discussion forums. The initiative aims to streamline professional growth and increase access for Priory’s widely spread nursing staff.

Finalists:

Hertfordshire and West Essex ICS
The Multi-Professional Learner Toolkit App is an innovative, user-friendly digital resource supporting healthcare students in nursing, midwifery, and allied health professions. Designed to address student attrition, it offers accessible, 24/7 support, including resources on wellbeing, academic help, and career development. Piloted in Hertfordshire and West Essex, it has received NHS funding for regional expansion in East England and recognition through the Chief AHP Office Awards. With a sustainable design, the app provides guidance, career mapping, and practical tools to help students succeed in training and transition smoothly into the healthcare workforce, supporting the NHS’s long-term workforce goals.

RateMyShift
RateMyShift is an innovative web app designed to enhance nursing work environments through real-time feedback and communication. Created by nurses for nurses, it enables staff to report their feelings after shifts, allowing managers to receive immediate alerts about who needs support. This tool promotes open dialogue, improves team cohesion, and provides data-driven insights to identify trends and systemic issues. After five years of development, RateMyShift has been tested in four NHS Trusts and aims to improve staff morale and well-being, directly addressing the need for timely support within the NHS workforce.

Entries have been summarised in less than one hundred words using artificial intelligence