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.

Interpreting Global Trends: An Australian Perspective

The current model of healthcare service delivery, in Australia and many jurisdictions globally, is unsustainable. The reliance on expensive acute facilities (e.g. hospitals) must shift to a greater balance of cost-effective care delivered in the community and the home.
Such a shift will require radically improved integration of data across the continuum of health service provision and from consumer-collected sources such as biosensors/wearables and passive sensors within homes or community care facilities.  

This will enable not only improved patient safety, greater access to care, streamlined operational processes, but also unlock the value of AI-enabled command centres and clinical decision supports. 

In 2030, health systems will shift to a greater focus on prevention and wellbeing and smart hospitals will focus on providing care to a smaller number of patients with complex or acute care needs.

Most patients won’t need to go to hospital and will be managed in virtual wards (e.g. at home) via digital command centres and real-time monitoring. Amplar Health’s virtual My Home Hospital (originally initiated as a joint venture with Calvary), is an example of such a model in Australia. Similarly, the Victorian Virtual ED (VVED), is preventing patients presenting to ED by providing virtual triage by trained nurses and clinicians both onshore and offshore. 

Patients will directly engage AI bots to provide and receive information about their care, shortening the time and reducing workforce need for tasks like scheduling and care planning. For clinicians, AI and ambient listening will support clinical decision making by suggesting optimal care pathways based on patient discussions and results of diagnostics. They will streamline the generation of clinical notes and orders and improve clinician engagement with patients. 

Virtual and Augmented Reality will become further embedded into clinical training and things like robotic surgery to improve consistency of care and patient outcomes. 

Australia must embrace these models and create the environment to allow new health innovations to thrive.