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  • Rod Morgan, Head of Faculty, RPM-Academy

Rethinking Primary Healthcare Delivery: Moving Towards a Next Available Model in Canada

Primary care image depicting chart, stethoscope, pills, etc.
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Primary care is crucial for overall health because it serves as the first point of contact for individuals seeking healthcare, providing preventive services, early detection, and management of chronic conditions, thus promoting better health outcomes and reducing the burden on secondary and tertiary care services.

As the landscape of healthcare evolves, so too must our approaches to delivering primary care. In Canada, the current model for primary care delivery typically relies on a system of batching patients to specific care providers and scheduling appointments accordingly. However, there's a growing recognition of the limitations of this model and the potential benefits of transitioning to a "next available" approach. Let’s delve into the pros and cons of both systems and explore how emerging technologies could facilitate this transition.

The Current Model: Batching Patients to Providers

Under the current system, patients are typically assigned to specific care providers based on various factors such as physician seniority, patient preferences, and existing relationships. This batching process often leads to the following:


  • Continuity of Care: Establishing a long-term relationship between a patient and a primary care provider can lead to better health outcomes, as the provider becomes familiar with the patient's medical history and individual needs.

  • Patient Preferences: Some patients prefer consistency and continuity in their healthcare, feeling more comfortable seeing the same provider for each visit.

  • Efficient Use of Resources: Batching patients to providers and rooms can optimize resource allocation in the short term, especially when considering physician availability and room utilization.


  • Limited Flexibility: Batching patients to specific providers can lead to inefficiencies, especially when providers have varying availability or when patients need to be seen urgently.

  • Bottlenecks and Delays: The process of matching patients to specific providers and rooms can create bottlenecks and delays, particularly during peak times or when unexpected circumstances arise.

  • Missed Opportunities for Care: Patients may face longer wait times or have difficulty accessing care if their preferred provider is unavailable or if appointment scheduling is rigid.

  • Eroded Care-Provider and Clinic Capacity: Inherent inefficiencies in this model result in reduced capacity at a time when millions of Canadians have limited or no access to primary care resources.

Moving Towards a "Next Available" Model

Imagine a system of primary care scheduling where the next available provider sees the next available patient in the next available room. This approach, often referred to as a "pull-based" model, could offer several advantages:

Benefits (to be realized):

  • Increased Access: A next available model ensures that patients can be seen promptly, regardless of their assigned provider, reducing wait times and improving access to care.

  • Efficient Resource Utilization: By eliminating the need to match specific patients to providers and rooms, resources can be used more efficiently, leading to higher overall clinic capacity.

  • Adaptability and Flexibility: This model is more adaptable to fluctuations in demand and unexpected changes, allowing clinics to respond quickly to patient needs and improved overall flow and efficiency.

Challenges and Constraints (to be addressed):

  • Patient-Provider Relationships: Concerns about continuity of care and the importance of patient-provider relationships must be carefully considered and addressed.

  • Technological Infrastructure: Implementing a next available model requires robust technological infrastructure to facilitate real-time scheduling, patient tracking, and communication among staff.

  • Staff Training and Support: Healthcare providers and staff need appropriate training and support to adapt to new workflows and embrace a more flexible approach to patient care.

Applying the Pareto Principle (80/20 Rule)

In discussion with primary care providers, there's often a pushback against the next available model, emphasizing the importance of continuity of care and the depth of providers' knowledge about their patients. However, it's crucial to recognize that healthcare patients form a heterogeneous population.

Applying the 80-20 rule, it's reasonable to assume that care providers may genuinely know, quite well, only about 20% of their patient roster—the ones they see more frequently. For the remaining 80%, a next available model could potentially serve them well. While continuity of care is essential, particularly for patients requiring chronic care management, embracing flexibility and adapting to a next available approach could significantly improve access to care for the majority of patients, ultimately enhancing the efficiency and effectiveness of healthcare delivery.

The Role of Emerging Technologies

Artificial intelligence (AI) and generative artificial intelligence (GAI) hold immense potential in addressing the challenges associated with transitioning to a next available model:

Physician at computer with words "AI" floating over image.
Image Source:

  • Optimized Scheduling: AI algorithms can analyze historical data and real-time inputs to optimize appointment scheduling, ensuring that patients are matched with available providers and rooms efficiently.

  • Predictive Analytics: GAI can predict future patient demand based on various factors, allowing clinics to anticipate fluctuations in demand and adjust staffing and resources accordingly.

  • Virtual Care Solutions: Telehealth platforms powered by AI can provide patients with access to healthcare services from anywhere, reducing the need for physical clinic visits and easing pressure on in-person resources.

Additionally, AI applications can significantly reduce the burden of administrative work that consumes much of care providers' time. Tasks such as appointment notes, updating patient records, preparing requisitions for prescriptions, referrals to specialists, and even assisting with diagnoses can be streamlined through AI solutions.

These systems use natural language processing and machine learning to automate administrative tasks and provide assistance to healthcare professionals. By automating these tasks, AI frees up valuable time for care providers to focus on direct patient care, leading to increased efficiency and improved patient outcomes.

Revealing the Primary Care “Hidden Factory”

Typically, when patients are booked to see care providers, there is often a provision for some of the care provider's "downtime" to allow for necessary follow-ups, even after the patient has left the room. This hidden downtime masks the true amount of time spent on administrative tasks, creating what can be considered a "hidden factory" that can consume 20% or more of a care provider's time. As long as this administrative burden remains hidden, it's actual impact on care-provider capacity is also concealed and underestimated!

"Family physicians spend more time on administrative tasks and less time on patient care compared to other medical and surgical specialists."

A table showing that family physicians spend 21% of their time on administrative tasks.

Transitioning to a next available model offers an opportunity to expose and address this hidden factory. By implementing AI solutions like DAX Copilot, clinics can automate administrative tasks in real-time, reducing the need for dedicated downtime and allowing care providers to focus on patient care during their scheduled hours. This transparency not only improves efficiency but also provides insights into the true costs of administrative work, enabling clinics to allocate resources more effectively and ultimately improve the quality of care.


The future of primary healthcare delivery in Canada lies in embracing a more patient-centric, flexible approach that prioritizes accessibility, efficiency, and transparency. Transitioning from a batching model to a next available model, supported by AI-powered solutions, presents an opportunity to revolutionize healthcare delivery and improve patient outcomes. By leveraging emerging technologies to automate administrative tasks and uncover hidden inefficiencies, clinics can optimize resource allocation, reduce costs, and enhance the overall patient experience. As we continue to innovate and adapt, we move closer to a healthcare system where every patient gets the appropriate first-time quality care from the appropriate care provider at the appropriate time and in the appropriate setting or location.


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