Primary care providers across Alberta are facing increasing pressure to make timely, accurate decisions while managing vast amounts of patient data and administrative tasks. This can lead to decision fatigue and potential errors. AI-powered clinical decision support systems (CDSS) offer a solution by integrating and analyzing diverse data sources, providing evidence-based recommendations, and automating routine tasks. This project aims to improve clinical efficiency, reduce errors, and enhance patient outcomes through intelligent, real-time decision support. The selected company will have the opportunity to validate their solution in real-world clinical settings and contribute to improved patient care and operational efficiency in Alberta.
This Call for Innovation is being posted in collaboration with Health Cities to seek out qualified Canadian companies who can meet the following desired outcomes. Health Cities will assist in identifying clinical implementation sites in Alberta through its network of partners. CAN Health and Health Cities reserve the right to not move forward with this project at its full discretion and, in particular, if there are no qualified Canadian companies that can reasonably meet the desired outcomes.
To qualify for a CAN Health project, the company must meet ALL of the following criteria:
- Headquartered in Canada (additional criteria apply for companies not headquartered in Canada)
- Majority ownership of both the company and the solution by Canadians
- Solution at Technology Readiness Level (TRL)>7, indicating actual technology completed and qualified through tests and demonstrations
- All the data and AI models (if applicable) must be hosted in Canada and comply with all the Canadian privacy regulations
- Possess all regulatory approvals required for commercialization, such as Health Canada approval
- Completion of all required clinical validity/unity studies
- No need for policy changes to be widely adopted
- Strong use cases in the Canadian health care system
If the company is not headquartered in Canada or the solution is not majority owned by Canadians, additional criteria apply:
- Independent autonomy over business operations and product development (for subsidiaries, affiliates or distributors)
- High Canadian job creation potential, especially in executive and senior management positions
- Commitment of over 70% of contract value to Canada
During the company selection process, preference is given to companies/solutions fully owned by Canadians, followed by those majority owned by Canadians, and finally international companies with a significant presence and economic impact in Canada.
For more information on the Call for Innovation process and the commercialization projects funded by CAN Health Network, please refer to the FAQ page on the CAN Health Network website: https://canhealthnetwork.ca/faq/
Problem Statement: Primary care clinics face challenges navigating a complex healthcare environment where physicians must integrate and interpret vast amounts of patient data including medical history, lab results, imaging studies, and real-time monitoring information. This data overload significantly increases the time required for clinical decision-making, heightening the risk of oversight and errors that can compromise patient care. Compounding this issue, the burden of administrative documentation and routine procedural tasks diverts physicians’ attention from direct patient interaction, further diminishing efficiency and the overall quality of care.
Objectives:
The proposed AI-powered clinical decision support system will empower physicians to deliver higher quality care, anticipate and mitigate health issues before they become critical, and improve overall patient outcomes.
Essential (mandatory) outcomes:
The integration of AI-powered clinical decision support systems is anticipated to:
- Integrate and interpret diverse clinical data to provide a comprehensive, real-time view of the patient’s condition.
- Enable evidence-based decision-making through reliable diagnostic and treatment recommendations grounded in current guidelines.
- Increase clinical efficiency by reducing cognitive workload and streamlining administrative tasks such as documentation.
- Demonstrate measurable improvements in patient outcomes, provider satisfaction, or operational performance.
- Foster continuous learning and adaptation to new medical advancements.
Primary care physicians have indicated the need for tools to help them manage the increasing complexity of modern healthcare, which demands accurate and timely clinical decisions amidst vast amounts of patient data. The cognitive load associated with synthesizing diverse data sources, coupled with the pressure to adhere to evidence-based practices, often leads to decision fatigue and potential errors. This situation is exacerbated by administrative burdens that detract from and reduce access to patient care.
