The UBC Department of Family Practice is saddened by the passing of Dr. Marko Yurkovich, a beloved clinical instructor, and alumnus of our Postgraduate Residency Program, on October 4th, 2025.
Dr. Yurkovich pursued his medical training at the University of British Columbia. He completed the Family Practice Postgraduate Residency Program at the Vancouver-Fraser Site from 2014 to 2016, where he returned as a clinical instructor in 2018.
Dr. Yurkovich founded Genetica Medical & Wellness Centre, where he welcomed and mentored countless UBC medical students and residents. As a true leader in primary care, he was instrumental in advancing initiatives that deepened continuity of care and strengthened team-based practice across the community. He was a beloved teacher, mentor, colleague, and friend, whose unwavering passion for patient-centred care shone through every interaction. His team continues to honour his legacy through their dedication to teaching, compassion, and service to the Downtown West End community he so passionately served.
“We, at the Vancouver Fraser Family Practice Site, remember and honour our former resident and colleague, Marko, following his courageous battle with cancer,” says Raquel Feswick, Site Coordinator, on behalf of the Vancouver-Fraser Site. “His commitment to teaching and his advocacy in the community made a meaningful impact. Marko was a valued member of our community and we will miss him dearly. Our thoughts are with his family and loved ones.”
The Marko Yurkovich Colorectal Cancer Foundation was established to commemorate Dr. Yurkovich’s mission to raise awareness, drive research, and advocate for early onset colorectal cancer. He will be missed.
Tailoring the guide to support the facilitator before, during, and after the debrief (this includes sample phrases that can be used in the moment).
A QR code that links users to references and relevant literature, contact information, and supportive resources such as additional phrases to assist in complex debriefing scenarios.
Coming soon: video examples of clinical event debriefings, highlighting best practices and opportunities for improvement to support new facilitators, as well as a workshop template and lesson plan to support training.
We are hoping that users can go to the link for the download, as with future revisions this will assure they have the most up to date content.
First, thank you to all that joined us at UBC’s Centre for Health Education Scholarship (CHES) Celebration of Scholarship!
Dr. Meera Anand and I led a roundtable discussion titled “DocBot 101: Making Sense of AI Before It Makes Sense of You.” Our goal was to explore how we can prepare learners to critically engage with artificial intelligence before it begins defining those terms for us.
Below is a brief summary of what we gathered from our dialogue.
We began by asking participants to choose one word that captured their perceptions and experiences with AI in health professions education. Their words painted a landscape of complexity and contradiction:
These reflect the promise, expectations, and discomfort of a technology reshaping how we teach, learn, and make decisions in both clinical and academic spaces.
What We Heard from Educators: Participants described learners using AI for summarizing literature, interpreting research, drafting emails, grammar correction, and assessment shortcuts. Some found AI slowed them down due to editing demands. Concerns emerged around students growing reliance on its use for creativity and ideation, yet most agreed AI is now embedded, unavoidable, and must be taught.
Preparing Faculty for the AI Era: Faculty are testing AI in their teaching, particularly for case development, and observing its implementation in hospitals, including Vancouver Coastal Health: VCH AI Hub.
When asked how to prepare faculty for AI’s growing presence, key ideas surfaced:
+ Create formal spaces for dialogue and training. + Develop institutional policies to guide staff and learners. + Use AI to teach ground-truthing, identify confabulations, and strengthen digital literacy. + Integrate AI into professionalism guides to clarify boundaries and etiquette. + Teach how AI scribes and transcription tools err. + Include prompt engineering and assignment design that mitigates over-reliance and academic dishonesty.
The takeaway: educators and administrators share a responsibility to equip learners with the frameworks, skepticism, and confidence to engage with AI responsibly and reflexively.
Learn more about the CHES Celebration of Scholarship here.
When we talk about Artificial Intelligence (AI) in healthcare, our minds often go to diagnostic tools, scribe assistants, or chatbot-based triage systems. But there’s another sector that has been living with AI’s risks and rewards for much longer: cybersecurity. Recently, I attended a lecture by cybersecurity strategist Dr. Craig Jarvis on the growing use of AI in digital defence. His insights translate remarkably well to our clinical context because, at its core, both cybersecurity and healthcare depend on trust, accuracy, and human oversight.
Let’s look at some of the lessons medicine can borrow from AI in cyber defence.
1. AI Can Help but Only If Humans Stay in the Loop
In cybersecurity, automated systems monitor threats, detect anomalies, and even block attacks. But when something unexpected happens, a human expert still needs to interpret, intervene, and decide.
In clinical practice, the same applies. AI tools can summarize patient notes, flag abnormal results, or even draft assessments — but they don’t understand context, patient nuance, or social determinants. We must always ensure “the clinician stays in the loop.”
“Speed is valuable, but not at the expense of human control.”
2. Reduce Toil, Not Thinking
In IT, AI is praised for reducing “toil” or the repetitive, low-value work that consumes time and mental energy. In medicine, the same promise is appealing: fewer administrative burdens, quicker charting, streamlined information retrieval.
But the key is toil reduction without cognitive erosion. If AI saves time, that time should be redirected toward deeper clinical reasoning, patient connection, or teaching moments and not simply faster throughput.
3. The System Is Only as Safe as Its Weakest Prompt
One cybersecurity slide Dr. Jarvis shared reported that 1 in 80 AI prompts carries a high risk of exposing sensitive enterprise data.
In healthcare, that translates to:
Be mindful of what information you input into AI tools.
Avoid typing identifiable patient data into any non-approved system.
Remember that AI retains patterns and once entered, data may not be fully private.
Clinical AI safety begins with data awareness at the prompt level.
4. Diversity Matters: No Single AI Does It All
Cybersecurity systems rely on multiple forms of AI:
Machine learning to detect patterns
Generative AI to summarize or report
Agentic AI to automate tasks and responses
In family medicine, this diversity principle also holds. One model may excel at summarizing notes, another at generating patient education materials, and a third at supporting evidence retrieval. Integrating these tools thoughtfully ensures resilience and balance, not dependence on a single system.
5. Guard Against “Inflated Expectations”
Dr. Jarvis highlighted the case of Cylance, a once-hyped AI cybersecurity company valued at over $1 billion later sold at a massive loss when its promise outpaced its performance.
In healthcare, inflated expectations can be equally dangerous. AI is powerful, but it’s not a replacement for judgment, empathy, or context. Adopting AI responsibly means piloting, evaluating, and refining tools before scaling much like any new clinical guideline.
Bringing It Back to Practice
If we think like cybersecurity professionals, we can reframe how we approach AI in medicine:
Cybersecurity Principle
Clinical Analogue
Human-in-the-loop oversight
Clinician supervision of AI recommendations
Patch management
Regularly update clinical AI tools and policies
Threat detection
Identify AI misuse, bias, or data leakage
Governance frameworks
Clear clinical and ethical accountability
The Bottom Line
AI can help us practice smarter, not just faster, but only if we approach it with the same discipline, skepticism, and care that cybersecurity experts apply to digital defence.
As family physicians and educators, our role is to ensure that AI augments, not replaces, the human connection at the heart of care.
Trust the technology, but verify the outcome and always with compassion and clinical judgment.
Just a reminder that the CFPC has released a series of sample questions (September 2025) that may be useful in your preparation for exams. In this mock exam, you’ll note the new menu-style questioning that the CFPC has recently adopted. If you have any questions regarding the SAMP or SOOs exam, click here.
The UBC Faculty Development Teacher Certificate Program welcomes faculty who teach and assess in the MD Undergraduate Program and Postgraduate Medical Education Program, across all sites.
Program Goal & Structure
The Teacher Certificate Program (TCP) aims to equip teachers in medical education with the basic knowledge and skills to teach effectively. TCP is divided into two programs:
TCP 1: Foundational Teaching is designed to cover core teaching and assessment competencies for those who teach in the MD Undergraduate Program (MDUP) and Postgraduate Medical Education Program (PGME).
TCP 2: Complimentary Topics with a Clinical Teaching Focus provides additional topics that continue to explore important teaching concepts. While all faculty teaching in MDUP and PGME are welcome, please note there will be emphasis on the clinical teaching environment.
The two programs are entirely separate, with no prerequisites, and can be completed in any order.
Each track (TCP 1 & TCP 2) consists of five sessions on topics outlined below delivered by experts. Sessions are delivered on Zoom unless specified. When you have completed all five sessions in a series, a completion certificate will be issued. If you miss a session this year, not to worry, we will likely have another session the following year!
Government of Canada Public advisory: Acetaminophen is a recommended treatment for fever and pain during pregnancy
Issue: Health Canada currently maintains that there is no conclusive evidence that using acetaminophen as directed during pregnancy causes autism or other neurodevelopmental disorders. Acetaminophen is commonly used to relieve pain and reduce fever. It has been used safely by millions of Canadians for decades, including during pregnancy and while breastfeeding. Acetaminophen is a recommended treatment of pain or fever in pregnancy when used as directed. It should be used at the lowest effective dose for the shortest duration needed. Untreated fever and pain in pregnant women can pose risks to the unborn child.
What you should do:
Continue to use acetaminophen for pain and/or fever during pregnancy, as directed. Always follow the directions on the label.
Do not take more than the recommended dose. Taking too much acetaminophen can cause harms including serious harm to your liver.
If you are pregnant or breastfeeding, talk to your health care provider if you have questions about the use of any medications.
Contact a health care provider if:
pain lasts more than 5 days; or
fever lasts more than 3 days.
What Health Canada is doing:
Health Canada’s advice is based on robust, rigorous assessments of the available scientific evidence. Any new evidence that could affect our recommendations will be carefully evaluated.
Health Canada monitors the safety of all medicines authorized for use in Canada, including acetaminophen. All Canadian non-prescription acetaminophen products already carry clear warnings about safe use during pregnancy and breastfeeding, as well as the risk of serious liver injury if too much is taken.
If new scientific evidence demonstrates a risk, Health Canada would take action to update labels, inform health care professionals, and provide advice to Canadians.
Teaching With AI: Reflections From our Dawn Patrol Series
I had a fascinating early-morning conversation with our UBC clinical preceptors about what happens when AI tools, especially scribes, enter our clinical learning spaces. So many questions came up about how the introduction is shifting the dynamic in patient care. Three key takeaways stood out:
🔹 Voice & Accuracy Matter Clinicians note that AI-generated notes don’t reflect their own style or reasoning. These tools often “fill gaps” with information never said, which can distort the record and drive unnecessary tests and investigations. They’re also much longer and less focused. How do we prepare medical learners to build tools that amplify their voice and clinical reasoning rather than overwrite it?
🔹 Prepare for a New Patient Dynamic Patients increasingly arrive with ChatGPT-style interpretations of their labs and expect explanations for why certain tests weren’t ordered or to clarify AI’s output. This shifts the power dynamic in the room. How can we equip clinicians and learners to respond transparently and confidently when patients bring AI into the conversation?
🔹 Patient Consent, Privacy & Ethics From signage to informed consent, we must clearly communicate when AI is used in documentation, how data are stored, and what biases or commercial pressures may influence these tools and their use. How do we educate and onboard patients around the use of AI in their care?
For me, the central question remains: how do we make AI an ally that supports our clinical thinking and teaching, rather than one that quietly reshapes the clinician’s voice and patient narrative?
Join us for our next session on Coaching Clinical Reasoning in the Age of AI Friday, November 21, 2025 0700-0800 I’ll be fowarding out the invite and link in the next week!
Figure A shows the organs that cystic fibrosis can affect. Figure B shows a cross-section of a normal airway. Figure C shows an airway with cystic fibrosis. The widened airway is blocked by thick, sticky mucus that contains blood and bacteria. National Heart Lung and Blood Institute (NIH) – National Heart Lung and Blood Institute (NIH)
“Dr Welsh: This journey really began for me when I was a junior medical student on my pediatrics rotation. I’m walking down the hall, and before I get to the room where I’m supposed to see a patient, I can hear harsh coughing. I go in the room, and there’s a 7- or 8-year-old little girl. It’s obvious she’s breathing hard. I can see her using her accessory muscles of ventilation. I hear her coughing and then I smell for the first time the odor of Pseudomonas aeruginosa, a common organism that affects the lungs of people with CF. I hear from her and her parents about all the things she can’t do and how much of her day is spent with a variety of different therapies.
The sobering part was when we left the room because then my attending told me that she wouldn’t make it to her teens. If she did make it to her teens, she almost certainly would never make it out of her teens. There are certain patients that are burned into your memory. That little girl is burned into my memory.”
How Cystic Fibrosis Went From Fatal to Treatable via JAMA.
Background: Obesity is a complex, chronic, stigmatized disease whereby abnormal or excess body fat may impair health or increase the risk of medical complications, and can reduce quality of life and shorten lifespan in children and families. We developed this guideline to provide evidence-based recommendations on options for managing pediatric obesity that support shared decision-making among children living with obesity, their families, and their health care providers.
Methods: We followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. We used the Guidelines International Network principles to manage competing interests. Caregivers, health care providers, and people living with obesity participated throughout the guideline development process, which optimized relevance. We surveyed end users (caregivers, health care providers) to prioritize health outcomes, completed 3 scoping reviews (2 on minimal important difference estimates; 1 on clinical assessment), performed 1 systematic review to characterize families’ values and preferences, and conducted 3 systematic reviews and meta-analyses to examine the benefits and harms of behavioural and psychological, pharmacologic, and surgical interventions for managing obesity in children. Guideline panellists developed recommendations focused on an individualized approach to care by using the GRADE evidence-to-decision framework, incorporating values and preferences of children living with obesity and their caregivers.
Recommendations: Our guideline includes 10 recommendations and 9 good practice statements for managing obesity in children. Managing pediatric obesity should be guided by a comprehensive child and family assessment based on our good practice statements. Behavioural and psychological interventions, particularly multicomponent interventions (strong recommendation, very low to moderate certainty), should form the foundation of care, with tailored therapy and support using shared decision-making based on the potential benefits, harms, certainty of evidence, and values and preferences of children and families. Pharmacologic and surgical interventions should be considered (conditional recommendation, low to moderate certainty) as therapeutic options based on availability, feasibility, and acceptability, and guided by shared decision-making between health care providers and families.
Read more on Managing obesity in children: a clinical practice guideline via CMAJ.
Family Medicine Residency Site: Abbotsford-Mission 