Healthcare is transformed through digital advancements like virtual care and AI has led to a shift from reactive acute care towards more proactive, personalised care. This includes a focus on specialised care in ‘smart’ hospitals and a rise in cost-effective home care enabled by technology like AI-powered contact centres and wearable biosensors. This data-driven approach, with a focus on population health management, aims to achieve a better patient experience, improved patient outcomes, lower costs, improved clinician well-being, and health equity. 

The world in 2030  
 

• AI-powered healthcare: AI is seamlessly integrated into the fabric of all healthcare technologies, from diagnostics and treatment decisions to administrative tasks like scheduling and resource allocation, aimed at supporting healthcare delivery by cohesive multidisciplinary teams.
  
• Proactive and preventative care: Healthcare systems have shifted more resources to prevention and leverage connected care, remote monitoring, and data analytics to identify potential health issues early, enabling timely interventions and a shift towards preventative care.
• Enhanced efficiency: Hospitals operate or share digital command centres utilising technology to optimise activities such as automated workflows, real-time patient monitoring, and flexible infrastructure, leading to improved productivity, patient satisfaction, and resource utilisation.
• Democratised health data: Healthcare data is digitised, secure and readily available to all care providers with GenAI-powered data insights enabling the delivery of 5P (predictive, proactive, personalised, participatory and precise) healthcare.
  

Overcoming cross-cutting constraints
 

There are several cross-cutting constraints that could affect the prediction (not having the right skills and talent, funding models, approach to regulation, and data governance in place). The prediction can be realised by turning the constraints into enablers by:

• employing comprehensive training to equip healthcare professionals with the skills to leverage AI, genomics, and virtual care technologies
• prioritising preventative care and incentivising positive patient outcomes, supported by diverse funding models that bridge investment gaps
• embedding ethical AI frameworks and robust audit processes to ensure compliance with regulatory requirements governing the use of AI-enabled medical devices and chatbots. Data science, cloud technologies and distributed ledgers have improved interoperability and the cyber-resilience, quality and completeness of health data.

Evidence in 2024

• Smart hospitals are rapidly growing: The smart hospital market is projected to reach $148.36 billion by 2029, integrating technologies like IoT, AI, and robotics to enhance patient care and operational efficiency.
• Remote patient monitoring is transforming healthcare: This market is expected to reach $78.4 billion by 2032, driven by its potential to improve patient outcomes, reduce hospital readmissions, and alleviate pressure on healthcare systems.

How AI/Gen AI might impact the sustainability of the healthcare ecosystem
 

• GenAI can streamline healthcare operations by automating tasks like electronic health record updates, improving patient flow, and enabling predictive modelling for crisis preparedness.
• GenAI-powered tools can provide continuous support to staff, personalise patient interactions, and simplify healthcare navigation, leading to increased satisfaction and productivity.
• By automating administrative tasks and providing patient support, GenAI frees up healthcare professionals' time, allowing them to focus on direct patient care.
• To effectively integrate GenAI into their workflows, healthcare professionals need to enhance their data fluency, technical skills, and understanding of ethical AI practices.