Pioneering the next era of care models

Imagine a digital architect that never tires, scours the latest clinical evidence in seconds, and then drafts a care pathway tailored to your community’s real-time needs. That’s the promise of generative AI Model of Care (MOC) driven planning.

By fusing continuous literature surveillance with in-the-moment scenario modeling, AI can help turn static service plans into living blueprints—showing healthcare leaders exactly where and how to modernize delivery, close equity gaps, and repurpose limited workforce capacity. The result? Decisions that are faster, smarter, and measurably aligned with the outcomes patients actually value.

We know the status quo in healthcare is not sustainable. Populations are living longer with increasing medical complexity placing an increasing pressure on the health system to respond. In addition, the rapid pace of technology innovation is creating new expectations, new possibilities, and new ways of working. However, designing new models of care is labour intensive, costly, and tends to be reserved for new capital projects like hospital builds.

We understand that Models of Care renewal is hard work to get it right – it requires thorough analysis, broad stakeholder input, a clear grasp of clinical data, alongside a practical understanding of day-to-day healthcare operations in resource-constrained environments - not to mention creativity inspired by the “art of the possible” to move organizations into the future.

Imagine how AI could enable more robust model of care design that inspires planners, leaders and frontline staff alike to create a truly high-performing health system? Embracing AI tools allow teams to:

• Readily extract actionable insights from clinical data, literature reviews, and patient journeys to inform decisions.
• Model various future scenarios that account for workforce capacity, costs, and resource allocation, enabling proactive planning.
• Mine global repositories of leading practices and research to customize local care models based on evidence and outcomes.
  

Leveraging AI-driven planning too can also have an impact on patients and providers by creating models of care that address wait times, more personalized treatment plans, and improved health outcomes. AI can not only accelerate timelines, improve decision-making, and enable organizations and health system to remain responsive to the changing needs of patients, providers and communities – it can ensure care models are designed for real-world needs and prepare organizations to thrive in 2025 and beyond.

It’s time to think and work differently – moving from reactive planning to a continuous approach that allows swift adaptation to changing workforce needs, financial constraints, and patient demands.

Leaders and front-line providers can adapt service delivery to tackle real-world challenges, fostering resilience and sustainability. How can organizations stay responsive? Consider these innovative AI enabled MOC design approaches:

• Better understand patient experiences: Use AI-powered tools to map out a variety of different journeys patients take through the healthcare system. Each patient is unique, so are their needs and the interventions needed to support them.
• Predict challenges ahead: Implement AI-driven scenario planning to forecast potential difficulties and allocate resources more efficiently. This proactive approach ensures organizations can respond to issues before they escalate.
• Learn from others: Utilize AI to analyze leading practices and research findings. By tapping into this information, organizations can better readily integrate successful strategies into their operations.
• Readily test new ideas: Leverage AI to identify and plan investment in pilot programs that explore new approaches to care. These trials help organizations address complexities in real-time and foster a move from reactive care to proactive management.

We’re rethinking how we tackle complex challenges like Model of Care design—leveraging AI to support modern, adaptive planning. Implementation of AI-driven scenario planning can forecast potential difficulties and allocate resources more efficiently. This proactive approach ensures organizations can respond to issues before they escalate. This is just one step in our ongoing evolution to meet the changing needs of populations and health systems. We’re ready to partner with you, share our tools, and support your planning journey ahead.

Artifical intelligence in action

AI in action is a series of insight articles produced by the KPMG Healthcare team, exploring how AI can be harnessed to address the complex challenges within the Canadian healthcare sector. This initiative seeks to promote health-specific AI applications and encourage responsible adoption. Stay tuned for our upcoming discussions on operational excellence, workforce transformation, and more.