Alder Hey Children’s NHS Foundation Trust has published an AI Strategy, outlining current and future AI work along with plans for benefits realisation, implementation, AI workforce development, infrastructure and data architecture.
Kate Warriner, chief transformation and digital officer at the trust, notes the strategy marks “a bold and exciting commitment to harness the power of AI to empower children, young people, families, and our colleagues at Alder Hey”. Kate adds: “Looking ahead, AI will support our teams by simplifying routine tasks, offering real-time insights and predictions, and automating notifications. This will help reduce burnout and free up more time for colleagues to focus on what matters most – delivering exceptional care to the children and young people we serve.”
Driving the transformation are four key themes: enhancing children and young people centred care; empowering colleagues and freeing up time using intelligent automation, AI assistants, and smarter workflows; transforming outcomes for children and young people by delivering precision care through AI-optimised pathways, predictive analytics, and remote monitoring tools; and revolutionising paediatric diagnostics with “cutting edge” innovation.
A roadmap reveals year one focuses across remote monitoring, ambient AI, Microsoft AI collaboration, clinical decision support, AI coding, and medical imaging. For year two, the roadmap highlights patient-facing virtual assistants, automated scheduling, predictive analytics, and wearables. Year three focuses on predictive models for early intervention, intelligent ordering, a patient-reported outcome dataset, and genomics; whilst year four will be AI in virtual care, an AI insights agent, AI-optimised care pathways, and diagnostics. By year five, the trust hopes to have moved to a “complete virtual care model”, to have created a trust LLM, and to be continuing work around rare diseases and AI in Alder Hey Centres of Excellence.
Building a strong foundation
The trust highlights the need for a “strong foundation” to back its AI vision, setting out plans for AI education and workforce development, and ensuring staff have the knowledge to use AI tools safely and effectively. It talks about fostering “a culture of AI literacy” in order to enable clinicians or support staff to recognise opportunities and understand data requirements for AI solutions, as well as the need to enhance understandings of AI methodologies, benefits, and risks, “to build confidence and trust in AI augmented workflows”.
AI projects will be prioritised based on their potential to improve patient outcomes, operational efficiency, and staff well-being, with “rigorous evaluation frameworks” in place to measure clinical and economic impact, clear pathways to adoption, and champions within clinical teams to help with clinical validation or challenges with implementation. Transparency for patients and the public will be key, and risk management strategies, audits, and cyber security practices will be developed to safeguard patient data. A governance framework will check compliance with regulatory requirements and ethical guidelines, whilst the trust commits to establishing “robust machine learning processes to ensure deployed solutions meet performance, clinical safety and regulatory standards”.
Delving into the technical, Alder Hey states its aims around developing a “scalable and interoperable AI infrastructure to support multimodal data integration and advanced analytics”. The first step in this process will be the migration of existing data warehouse infrastructure to a secure cloud platform, but scale to wider data assets. A shift to a “structured, AI ready data ecosystem that supports real time decision making” will also be made, and the trust will look to provide access to high quality data for clinical teams and researchers, supported by the implementation of a Secure Data Environment integrated with the cloud-based data platform.
Plans for AI in practice
The trust moves on to share some examples of strategic initiatives in the pipeline, such as an AI-powered virtual assistant to help guide young people and their families through appointment scheduling, medication reminders, and symptom checking, to better manage care at home. Real-world data and predictive analytics will be used to detect early signs of paediatric conditions, machine learning models will be trained using this data to optimise on clinical outcomes, AI-powered remote monitoring tools and wearables will be deployed to track key health metrics for patients recovering from surgery or with chronic conditions, and AI capabilities will be tested on diagnosing a range of conditions.
For staff, strategic initiatives such as AI-powered documentation, using ambient AI to transcribe and summarise consultations, AI assistants for day-to-day tasks, automated scheduling, and intelligent ordering to automate investigation requests and track results, will be introduced to streamline workflows and improve efficiency. Clinical decision support systems will offer real-time decision support and insights on treatment tailored to patient-specific data, and an AI “insights agent” will be developed to perform analytics and locate content in documents to support staff productivity. Alder Hey is also looking to use AI on top of its EPR and other key systems, and to create a large language model (LLM) to “harness organisational data assets securely and fuel Retrieval Augment Generation (RAG) and Agentic AI developments”.
The pilot of Lyrebird, an AI scribe that uses recorded information from consultations to generate notes in the EPR, has seen 11,000 consultations conducted using the technology, the trust shares. Vejay N. Vakharia, consultant neurosurgeon and CIO for surgery at Alder Hey, points to a “meaningful impact” of the tech on daily clinical practice. “Beyond the convenience and time-saving benefits, I am free to engage with patients and their families, knowing that all the important facts are being accurately recorded. The AI-generated letters are easier for patients to understand by removing unnecessary medical jargon and allow for referral letters to be generated instantly from the consultation,” he said.
Collaboration will be “essential” to the strategy’s delivery, according to the trust, which states: “We will actively forge partnerships with industry leaders, academic institutions, and healthcare organisations to co-develop AI solutions tailored to the unique needs of paediatric healthcare. This approach will allow us to benefit from the latest technological advancements while contributing our expertise as paediatric specialists.” Hosting an AI Summit to focus on paediatric opportunities, establishing a dedicated clinical/MDT group to guide the “sociotechnical integration” of AI solutions to ensure they meet the real needs of healthcare teams and children, and delivering a Digital, Data and AI Collaborative, are other key activities under this header.
Looking ahead: Benefits realisation, resource, and impact
“A comprehensive investment plan for the delivery of the strategy will be developed,” according to Alder Hey. “The investment will cover the necessary resources to deliver on the strategy, including infrastructure, staff training, and project implementation.” It estimates that AI-driven efficiencies “could lead to cost savings or increased productivity of 5 to 15 percent annually”, with a 20-30 percent reduction in administrative tasks for clinicians through AI automation, allowing 10-15 percent more direct clinical interaction time, equating to 4-6 additional hours per week for each clinician.
The trust also estimates impact on patient care, safety, and staff and patient experience, noting that AI-enhanced diagnostic tools and predictive analytics could lead to a 15-20 percent improvement in diagnostic accuracy and prevent 100-200 adverse events per year. The effects of AI tools in streamlining workflows could lead to a 25 percent reduction in clinician burnout and an increase in overall job satisfaction, whilst patient satisfaction could be increased by 10-15 percent in line with shorter waiting times and more personalised care. A 15-20 percent reduction in waiting times might be achieved through AI-optimised scheduling and resource allocation, it adds.
Elsewhere, Alder Hey considers that a self-service data and cloud-based data analytics platform may lead to a 30-40 percent reduction in time spent on manual data gathering, and a 50 percent faster response to data requests. “By positioning ourselves as an AI leader in healthcare, we anticipate attracting £5-10 million in external investments over the next 3-5 years to further scale AI initiatives,” it notes.
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