The future is now: public health and artificial intelligence

Challenges such as rising chronic diseases, mental health issues, infectious disease outbreaks, and health inequalities demand innovative solutions. This is where AI steps in, offering a powerful toolkit to address these complex problems effectively.

This blog explores the significant role of AI in public health in England, supported by real-world examples.

AI in disease surveillance and predictive analytics

AI has significantly enhanced disease surveillance and predictive analytics, allowing for timely interventions and better resource allocation. In Flu Outbreak Prediction, AI models analyse data from various sources, including social media, health records, and environmental factors, to predict flu outbreaks. This enables healthcare providers to prepare and respond more effectively.

During the COVID-19 pandemic, AI was instrumental in tracking the spread of the virus, predicting hotspots, and analysing patient data to optimise treatment. The NHS used AI to predict patient outcomes and manage hospital resources efficiently.

Predictive analytics can be used for falls prevention and homelessness prevention, predicting at-risk individuals, and enabling pre-emptive measures. Manchester City Council employs predictive analytics to identify and support residents at risk of homelessness.

AI in personalised health interventions

Personalised health interventions are crucial for addressing individual health needs and improving outcomes. AI plays a significant role in tailoring these interventions. Used in Mental Health Support, AI-powered chatbots and virtual therapists provide mental health support, offering personalised advice and coping strategies. These tools are particularly valuable in reaching individuals who might not seek traditional therapy.

There is a significant role for AI in health education, particularly its use in interactive, empathetic chatbots. AI-based chatbots have an advantage over simple E-health educational resources by being more interactive and conversational with natural language flow.

AI in health monitoring and early detection

Early detection of diseases can significantly improve treatment outcomes. AI excels in analysing large datasets to identify early signs of health issues. In Cancer Detection, AI algorithms analyse medical images, such as mammograms and CT scans, to detect cancer at an early stage. The Royal Marsden NHS Foundation Trust uses AI for early detection of breast cancer, improving diagnosis accuracy and treatment outcomes.

AI-powered wearable devices are becoming more sophisticated, such as smartwatches, monitor vital signs and detect anomalies. These devices can alert healthcare providers to potential health issues, enabling early intervention.

AI-enabled sensors in adult social care can monitor health and safety, ensuring timely interventions. For example, Essex County Council uses AI sensors to monitor the well-being of elderly residents in their homes.

AI in resource allocation and efficiency

Efficient resource allocation is essential for delivering high-quality public health services. AI can help optimise resources and improve operational efficiency:

• For translation services and creating easy-read documents, making information accessible to a broader audience. The London Borough of Redbridge uses AI for translating council communications into multiple languages.
• Public-facing chatbots are used in contact centres to provide quick responses to common queries. For example, the London Borough of Enfield's chatbot, Amelia, helps residents with queries ranging from council tax to benefits.
• AI optimises the supply chain for medical supplies and equipment, ensuring timely availability and reducing wastage. The NHS has implemented AI-driven supply chain solutions to enhance efficiency.
• AI can be used to predict patient admissions and hospital bed occupancy, allowing hospitals to manage resources effectively. Cambridge University Hospitals NHS Foundation Trust uses AI to optimise bed management and reduce patient wait times.
• In areas like social care or housing, AI can help manage caseloads and provide tailored support. 

Addressing challenges and ethical considerations

While AI offers numerous benefits, it also presents challenges and ethical considerations. Public health teams must address these to ensure safe and responsible AI adoption. There are concerns about data privacy and the security of sensitive health information. Ensuring robust data protection measures is crucial to maintaining patient confidentiality and trust.

AI systems must be designed to mitigate bias and ensure fair treatment for all individuals, regardless of socio-economic status, race, or gender. Ethical considerations need to consider how algorithmic decision making and biases could exacerbate existing health inequities.

Efforts must be made to include digitally excluded residents and ensure they benefit from AI-driven health interventions.

The integration of AI into public health operations is still in its early stages. However, the potential benefits are immense. To fully harness the power of AI, local authorities will need to foster collaborations, and ensure that ethical considerations are at the forefront of AI deployment. Community engagement and transparency are essential. Educating the public and our own workforce about the benefits and limitations of AI in health can build trust and encourage acceptance of these technologies.

The synergy between public health and artificial intelligence holds great promise. By embracing AI, local authorities can enhance their ability to protect and improve the health of their communities, paving the way for a healthier, more resilient future.

Councillor David Fothergill
Chairman, LGA Community Wellbeing Board