AI Factories: The Engine of Healthcare Transformation

The recent Dell Tech World 2024 highlighted the transformative power of AI factories in the era of artificial intelligence. These AI factories are not just about technology; they're about transforming the way the NHS operates and delivers patient care. Just like the Industrial Revolution brought about significant change, we're now in the midst of an AI revolution. 

Imagine a world where AI factories within the NHS are generating actionable intelligence, fresh content, and new insights around the clock. These insights could be used to predict disease outbreaks, optimise resource allocation, and even personalise patient care. According to a recent survey by The Health Foundation, nearly 60% of clinicians believe AI will reduce administrative burdens and enhance patient interactions.  

During the pandemic, NHSX created The National COVID-19 Chest Imaging Database (NCCID). This database, containing over 40,000 CT scans, MRIs, and X-rays from more than 10,000 patients across the UK, has been used to track patterns and markers of illness. This has accelerated the diagnosis of COVID-19, leading to quicker treatment plans and a greater understanding of whether the patient may end up in a critical condition. This was never intended to replace clinicians but to support them with decisions, and look for disease markers to ensure timely treatment was provided when the NHS was overwhelmed and over capacity. 

What AI could do for the industry 

Artificial Intelligence (AI) is poised to revolutionise the NHS in numerous ways. One of the key areas where AI can make a significant impact is in automation and service efficiency. Voice recognition, which has been around for some time, can be used to transcribe consultations, which frees up more staff time to deliver care. Furthermore, natural language processing could automate some patient documentation workflows, helping to identify actions, and suggest and automate responses. 

AI can also play a crucial role in diagnostic and decision support. Decision support systems can apply guidelines to consultation data and suggest a diagnosis or management plan to the clinician unlocking further efficiencies and driving exceptional levels of care experience.  

AI systems use the latest technology, research, and evidence to enable healthcare providers to give their patients the best chance of surviving cancer. It takes an integrative approach to a cure; from cancer prevention, screening, point-of-care cancer assessment, and surveillance. AI will be there for every step of a patient’s journey from diagnosis to outcome. This is vital when we know one in three of the population will get cancer. 

The concept of Predictive, Preventive, Personalised, and Participatory medicine, incorporates multiple data sources, such as patient records, biometric data, and genomic data. This information can be used to calculate patient risk more accurately and predict an individual patient’s response to medication using pharmacogenomics. This approach promises to shift from the traditional ‘one-size-fits-all’ form of medicine to a personalised, data-driven disease prevention and treatment methodology. The data is already available; we are just not using it to its best advantages.  

AI has been used to replace a second reader in radiology and histology; increasing image processing capacity and potentially identifying overlooked lesions. This field is rapidly developing, and we may see new diagnostic tools to help interpret images taken by the GP or in the community, such as photographs of skin. This can help with the issues of professional workforce shortages, again, not to replace the clinician but to support and complement.  

AI algorithms can provide continuous monitoring of patients and early recognition of deteriorating patients. An example of how this could work includes the virtual wards used during the COVID-19 pandemic; another efficiency that can support the hospital from overcapacity and demand, to enable care in alternative care environments and your own home.  

In the last decade the boom of consumer technology like smartphones and wearable devices, expedited since the pandemic, can prompt a patient to make a consultation. For example, many smartwatches can detect atrial fibrillation and assess sleep quality. The latest smartphones can detect respiration and heart rates, and smart speakers can detect coughs and snoring. 

AI can be used to spot patterns in population data not previously identified, which will be key for Integrated Care systems and how they support their regional population health. Interventions could be used to reduce the risk level of individuals by giving them targeted advice directly via an app or letter with lifestyle suggestions, such as stopping smoking, exercising, dieting or reducing alcohol intake. 

AI holds immense potential in transforming healthcare, improving patient care, and enhancing healthcare efficiency. As we continue to advance in this field, we can expect to see more innovative applications of AI in healthcare. However, there is a still lot of anxiety when it comes to AI.  

The ethics and considerations of AI in health and care 

The NHS must ensure that AI projects are ethically and securely implemented to maintain the confidence of the public and users through a variety of measures: 

• NHS AI Lab Ethics Initiative: This is a project that helps make sure AI technologies are used in a good and fair way in health and care. It helps us understand how to reduce risks and make sure everything is done ethically. 
• Code of Conduct: This is a set of rules for AI and other technologies that use data. It makes sure that only the best and safest systems are used by the NHS. It also encourages technology companies to protect patient data very carefully. 
• AI in the NHS: A Framework for Adoption: There are some publications that explain how to use AI in healthcare. They focus on the context, how the AI is designed, and ethical issues like making sure it doesn't exclude anyone or make things worse for minority groups. 
• NHS AI Lab Roadmap: The NHS AI Lab is working on several projects to make sure AI is used safely, effectively, and ethically in health and care. This includes exploring what AI can do, building confidence in it, and making sure data is used properly. 
• Data Security: The NHS, like all public sector bodies, is committed to protecting patient data. Any AI system used within the NHS must follow strict rules to protect data and privacy. 
• Transparency and Accountability: The NHS makes sure that AI systems are clear in how they work and that there is someone responsible for their outcomes. 
• Inclusive Design: AI systems should be designed to be fair and not make health inequalities worse. This means thinking about the impact on all groups of people and making sure the systems are accessible to everyone. 

By implementing these measures, you can ensure that AI projects are conducted ethically and securely, ultimately benefiting patients and healthcare providers alike. 

Bringing staff along for the journey 

In the midst of this AI Revolution, it's absolutely essential that we bring our dedicated NHS staff along on this transformative journey. This journey involves a comprehensive approach that includes education, training, and support.  

Every member of our health and care staff should receive training in artificial intelligence (AI), with additional specialist training for those who will be using AI tools in their clinical practice. Recent research, published by the NHS AI Lab and Health Education England (HEE), has provided recommendations for education and training providers in England. These recommendations will help them plan, resource, develop, and deliver new training packages on AI for our health and care staff. The report suggests that more advanced specialist training may be required for other health and care staff, depending on their roles and responsibilities, whether in procurement, implementation, or clinical practice.  

This collaborative research from HEE and the NHS AI Lab represents a significant step forward in developing confidence in AI within our healthcare workforce. It's crucial that all staff receive appropriate training in AI, so that the NHS can fully embrace new AI technologies and ensure they are adopted equitably across the country. 

Conclusion 

In conclusion, the journey to AI for NHS staff involves a comprehensive approach that includes education, training, building confidence, targeted training, and collaboration. By equipping our workforce with the necessary knowledge, skills, and capabilities they will need in AI, we can truly unlock the potential of AI in the NHS. 

These initiatives demonstrate the transformative potential of AI and AI Factories in supporting the NHS's mission to provide high-quality healthcare services. At CDW, we are here to support you in your strategy to use AI across your organisations, not just in small pockets or silos. We will strive to understand your needs, gaps, readiness in infrastructure, data, and culture, and how you can fulfil your use of AI. This includes stakeholder engagement to ensure successful deployment and drive this Revolution in transforming Care. Remember, we're in this together, every step of the way. 

Please get in touch if you want to know more.