Agenda

Improving patient safety requires more than implementing new processes—it requires designing healthcare systems that account for how people interact with their environments, technology, and workflows. Human Factors (HF) engineering offers a powerful, evidence-based approach to reducing risk, improving efficiency, and enhancing the delivery of safe, high-quality care.

This session explores Ontario’s first Academic Practice Partnership (APP) between William Osler Health System and the Centre for Healthcare Engineering at the University of Toronto, created to integrate Human Factors engineering into healthcare through education, practice, and research. Attendees will learn how this innovative collaboration is bridging the gap between Human Factors theory and frontline clinical practice by embedding engineering expertise into patient safety initiatives, quality improvement projects, and interdisciplinary research.

Key Takeaways:

• Discover how Human Factors engineering can be integrated into quality improvement initiatives to improve patient safety, clinical workflows, and system performance

• Learn how interdisciplinary partnerships between healthcare professionals and engineers can accelerate innovation, strengthen problem-solving, and translate research into practical improvements

• Explore a scalable model for embedding Human Factors into healthcare organizations through integrated education, practice, and research

Artificial intelligence–based clinical decision support is rapidly moving from concept to basic clinical infrastructure, embedded directly into the community and hospital systems that clinicians use on a daily basis. But the majority of models that support these tools rely heavily on international evidence or guidance, often US or UK guidelines, which may differ significantly from Ontario and Canadian standards of care, covered drugs or health policy decisions. As AI-CDS scales, quality leaders face a new question: whose knowledge is truly driving clinical recommendations?

An AI frontier model harness is the software infrastructure and orchestration layer that wraps around a state-of-the-art AI model. If the frontier model is the “brain,” the harness is the body, nervous system, and tools that let it take action in the real world.

This session introduces the Knowledge Base Standard (KBS) – a governance framework developed by Ontario’s Evidence2Practice program (E2P) that works exactly as this type of harness for clinical decision support. E2P is a provincial initiative and has already engaged over 12,000 acute care and nearly 5,000 primary care clinicians in Ontario through its foundational, non-AI phase. The KBS establishes a tiered evidence hierarchy as the final authority for AI-generated recommendations in a mixed EHR environment. This talk is a call to action: as AI-CDS is becoming the default interface to embed evidence at the point of care, quality leaders across Canada need to be asking if the knowledge behind these tools reflects the standards that their clinicians are actually held to.

Key Takeaways:

• Understand the “knowledge legitimacy problem” in AI-CDS and why it’s a quality and patient safety issue, not just a technical one
• Learn the structure and governance logic of a tiered evidence hierarchy that can be adapted across provincial and organizational contexts
• Leave with a framework for auditing your own organization’s AI-CDS tools for evidence provenance and alignment with Canadian standards of care

Climate change is no longer a future risk. It is already shaping patient care, population health, and the resilience of health systems. Increasingly, health leaders are recognizing that environmental sustainability is not separate from quality of care. It is a core determinant of it. The climate crisis is also a health crisis, affecting outcomes through rising temperatures, air pollution, extreme weather events, and disruptions to food, water, and health system infrastructure. At the same time, health systems themselves contribute to environmental impacts that in turn affect population health.

This session will explore how sustainable health care practices can directly improve quality by strengthening patient safety, enhancing system resilience, and supporting better outcomes across populations. Drawing on emerging practices and tools such as the Climate Action Maturity Assessment, it will demonstrate how organizations can integrate sustainability into leadership decision-making, operational processes, and clinical practice.

Key Takeaways:  

• Environmental factors directly impact patient outcomes, safety, and population health, making sustainability central to quality improvement
• Use structured approaches and aligned standards to integrate climate action into governance, operations, and care delivery
• Practical initiatives, from energy use to clinical practices, can improve efficiency, reduce costs, and enhance system resilience while improving care

In 2023, Canadian Mental Health Association (CMHA) Hamilton was experiencing an 18-24 month wait list for Intensive Case Management at a time where the need, coming off the pandemic, was rapidly increasing and intersecting crises of people experiencing homelessness, mental health, and opioid use was making headlines. CMHA Hamilton answered the call.

In 2024 we embarked on a quality care initiative to embed SC2.0 across the organization, improve operations, and increase better outcomes. Connecting four pillars of work (One-at-a-Time Counselling, Recovery College, Measurement Based Care, and Stepped Case Management), we were able to increase low barrier access points to move clients up, out, down, and over the internal system, and reduce our wait list to 3 months. Research, in partnership with McMaster University, reviewed our change project showing promising results and lessons for sustainability. CMHA Hamilton is currently positioned as a leader to spread and scale SC2.0 across our Ontario Health Team and support change projects on a national level through other CMHAs.

Key Takeaways: 

• The components that supported the improvement of quality of care

• Lessons learned for large-scale change initiatives

• How our infrastructure and operations created a climate for quality improvement

• The use and value of co-designing a large-scale quality improvement project

This session will highlight the implementation of a standardized, organization‑wide geriatric education strategy designed to build frontline capacity and embed senior‑friendly practices across diverse clinical settings. Developed in response to the growing needs of our community and aligned with our evolving seniors care strategy, this work reflects a key milestone in our organizational journey toward delivering consistently excellent care for older adults. A central component was the Senior Care Champion (SCC) framework, positioning frontline nurses as unit‑based resources, coaches, and change agents who support proactive, age‑responsive care.

The presentation will describe how the education strategy was scaled across medicine, stroke, continuing care, and other inpatient and outpatient areas, with a strong focus on staff engagement and completion. Participants will learn how SCCs supported local adoption of best practices, reinforced education at the point of care, and helped shift delirium management from reactive to proactive through the ADAPT framework across 17 inpatient units.

Key Takeaways:

• Describe how a standardized, organization–wide geriatric education strategy can build frontline capacity and sustain senior-friendly practices across diverse clinical settings

• Identify key implementation strategies, enablers, and challenges involved in scaling geriatric education and frontline champion roles across multiple programs, including lessons learned from real-world uptake and completion outcomes

• Explain how leveraging unit-based leadership, continuous feedback, and structured education can support a shift in practice in delirium management from reactive to proactive care, driving consistency and improved quality of care for older adults at a system level

What happens when everyone across an organization is empowered to be both a problem seeker and a problem solver?

Since 2021, Lakeridge Health has undertaken a multi-year journey to implement a Daily Management System across its five sites and more than 30 community locations. From tiered huddles and Quality Improvement Boards to leader in coaching, standard work and structured problem solving, the organization has progressively built a system that connects frontline improvement with organizational priorities.

Now implemented in more than 185 areas and generating thousands of improvement ideas, this session will share the practical steps, enabling conditions and lessons learned from scaling Daily Management across a complex health system. Participants will also hear how Lakeridge Health continues to evolve its approach through coaching, staff feedback, psychological safety measures, and automated reporting.

Key Takeaways Include:

• Learn how to plan and scale a Daily Management System across a large, multi-site healthcare organization using a phased implementation approach, model programs and structured education
• Explore the leadership and cultural enablers that sustain daily improvement, including tiered huddles, leader presence, coaching, communities of practice and mechanisms for strengthening psychological safety and staff engagement
• Discover how data, feedback and continuous learning can evolve the system over time, creating greater visibility of organizational issues while turning frontline ideas into meaningful quality improvements

Artificial intelligence is rapidly transforming healthcare, creating new opportunities to improve quality, patient safety, operational efficiency, and clinical decision-making. Yet technology alone cannot solve healthcare’s most pressing challenges. The future of quality improvement lies in combining AI, human-centred design, data analytics, and human factors principles to build healthcare systems that are not only smarter, but also safer, more equitable, and easier for patients and clinicians to navigate.

This executive panel will explore how leading healthcare organizations are moving beyond reactive approaches to quality improvement by leveraging AI, predictive analytics, human-centred design, and real-time data to proactively identify risks, improve patient outcomes, and enhance care delivery. Panelists will share practical examples of how AI is supporting quality measurement, patient safety, operational decision-making, and continuous improvement while addressing critical considerations such as governance, transparency, trust, ethics, and responsible implementation. Attendees will gain valuable insights into how healthcare leaders can successfully integrate emerging technologies without losing sight of the human experience at the centre of care.

Key Takeaways: 

• Explore how artificial intelligence, predictive analytics, and human-centred design are transforming quality improvement and patient safety across healthcare organizations

• Learn practical strategies for using data and digital technologies to proactively identify risks, improve clinical outcomes, and enhance operational performance

• Understand how healthcare organizations can responsibly implement AI by addressing governance, ethics, transparency, human factors, and patient trust

When healthcare harm occurs, accountability processes are often treated primarily as legal or regulatory matters rather than core components of healthcare quality and patient safety. This timely and thought-provoking session explores how fragmented post-harm pathways in Ontario, including complaint processes, regulatory reviews, privacy mechanisms, ombudsman investigations, and litigation, can unintentionally undermine transparency, organizational learning, patient trust, and meaningful resolution.

Drawing on extensive healthcare leadership experience and legal scholarship, Nora Constas will examine how delayed disclosure, inaccessible records, siloed complaint systems, and adversarial approaches can negatively impact both patients and healthcare organizations. Particular attention will be given to the experiences of Indigenous patients and families, who may encounter anti-Indigenous racism, systemic inequities, geographic barriers, and limited access to advocacy supports throughout post-harm processes.

Key Takeaways: 

• Examine how fragmented post-harm accountability mechanisms can hinder patient-centred resolution, organizational learning, transparency, and healthcare quality improvement

• Explore the intersection of patient safety, healthcare quality, and Indigenous health justice, including how anti-Indigenous racism can contribute to harm and mistrust within healthcare systems

• Gain a practical framework for advancing equitable, transparent, and learning-focused accountability processes that support safer, more patient-centred healthcare systems

The Problem: Information Exists, But Decisions are Delayed

Community care organizations generate significant amounts of clinical and operational data, yet critical information is often fragmented across multiple areas of the electronic medical record. Prior to this initiative, Nucleus staff and leaders lacked timely, role-specific visibility into key quality indicators, creating risks of delayed clinical follow-up, slower response to client concerns, and reactive rather than proactive program oversight. Without a consolidated view of quality and performance data, opportunities to identify emerging issues, support timely decision-making, and demonstrate outcomes were often missed.

The Innovation: Transforming Data into Actionable Information

Rather than implementing a new technology platform, Nucleus leveraged existing EMR data to create a practical, scalable approach that delivers meaningful information to staff and leaders when it is needed most. The solution connected clinical, operational, and quality data that previously existed in separate areas of the EMR, enabling proactive monitoring of assessments, faster review of client concerns, and improved visibility into program performance. By building on existing infrastructure, Nucleus demonstrated how community care organizations can use data more effectively to strengthen quality oversight, support frontline decision-making, and improve client outcomes without significant additional investment.

Key Takeaways:

• Describe how existing EMR data can be leveraged to improve quality, safety, and client experience in community care

• Identify opportunities to transform fragmented clinical and operational data into actionable information that supports better decision-making

• Evaluate the impact of data-informed approaches on care coordination, workforce effectiveness, and client outcomes