Symposium 13 - Maximising Impact on Clinical Workforce through Artificial Intelligence and Virtual Hospital

Diagnostic radiology is a rapidly evolving speciality, with advances in technology leading to new innovations in scanner hardware and image processing in the last decade. Artificial intelligence (AI) has been most impactful in health care to date in the radiology field, due to the digitalisation of radiology, and the increasing demands on radiologists due to increasing workload. 
AI is commonly used in all aspects of diagnostic radiology. It is used to help choose the most appropriate imaging tests, improve patient booking systems, and other non clinical use cases. Clinically, it is increasingly used to improve radiologist accuracy, identify cases with urgent time sensitive pathology, enhance image quality, and to reduce both radiation dose and study acquisition time. AI is being used to improve clinical outcomes for patients, as well as address issues with access to services and radiologist resourcing.
The current uses of AI in diagnostic radiology will be presented here, as well as the potential use cases for AI in diagnostic radiology in the years to come. Several key use cases such as stroke imaging and thoracic imaging will be discussed.

This session will cover the experience of the UK health system, the NHS, in introducing Virtual Wards at scale across the country. A process that began as part of the pandemic response in 2020 and is now, four years on, a service reaching around 10,000 people daily, in every part of England, on the NHS. 
Virtual Wards provide hospital-level care within someone's own home, supported by remote monitoring technology, with clinicians reviewing dashboards. Sometimes, care will be provided fully remotely, but often it is a hybrid model with some additional hands-on care provided in the home. 
Tara will share her perspectives on this development, as she was the Chief Digital Officer for the NHS in England at this time, and provide patient perspectives on the new care model. This move is a global phenomenon, and she will illustrate her talk with some examples of how care delivery is shifting towards home, both in the UK and globally.
She will also talk about what the future of healthcare could be, if care was systematically more home based and tech enabled and how this would change the way we think about hospitalisation. 
Tara is keen to share and learn internationally on digital care progress and as well as answering any questions, would like to hear your ideas, suggestions and advice on what is working well locally and how we can accelerate progress to become part of mainstream health care, as part of the Questions and Answers session.

Artificial Intelligence (AI) is revolutionizing healthcare delivery locally and globally. Enhancing diagnostic accuracy, operational efficiency, and patient outcomes are the common primary objectives. Current applications in the Hospital Authority include AI-powered tools for CT brain imaging for hemorrhage, automated chest X-ray interpretation, nasogastric tube position verification, hip fracture detection on radiographs, ECG analysis, and in-patient clinical deterioration prediction. Generative AI further streamlines medical reporting and summaries, reducing administrative burdens. These innovations bring values of augmenting clinical workflows, minimizing errors, and prioritizing urgent cases, as well as positioning HA as a local and regional leader in integrating technology into public healthcare.


Looking ahead, the direction of development of AI in healthcare aims to advance towards Artificial General Intelligence (AGI) and multimodal AI systems capable of synthesizing diverse data streams-imaging, electronic health records, genomics, and real-time monitoring-to enable holistic, personalized care. Such systems could predict disease trajectories, optimize treatment plans, and enable healthcare service transformation towards ambulatory care and hospital-at-home. However, realizing this vision necessitates robust governance frameworks to address ethical, legal, and privacy concerns, particularly regarding data security, algorithmic bias and liability. Regulatory standards must evolve to ensure AI's safe and equitable deployment.


Crucially, the transformative potential of AI hinges on demonstrable clinical efficacy and cost-effectiveness. Rigorous validation with pragmatic data and health-economic analyses is essential to justify scalability. Collaboration among policymakers, clinicians, and technologists will be vital to balance innovation with accountability. As HA navigates this paradigm shift, fostering trust through transparency and interdisciplinary engagement will ensure AI-driven advancements translate into equitable, sustainable healthcare improvements. Ultimately, AI's role as a game-changer in healthcare depends on harmonizing cutting-edge technology with ethical stewardship, evidence-based practice as well as building a workforce with AI literacy.