The 2025 Ogden Surgical Medical Society Conference hosted medical thought leaders from across specialties. What was the burning question on the mind’s of many health professionals? How is artificial intelligence reshaping healthcare—from diagnostics to documentation—and what it means for providers navigating population health and value-based care models?
Greg Osmond, MD, MPH, co-founder of PathologyWatch, and a presenter at this year’s event, positioned the answer as a strategic balance of Pathology, AI, and Population Health.
Here’s a look at the highlights and key takeaways from his session:
Finding the Balance: Pathology, AI, and Population Health
Dr. Osmond opened by framing the most current questions facing clinicians and healthcare organizations today:
- What does an effective balance of pathology, AI, and population health actually look like?
- What can today’s AI really do in clinical practice?
- How can clinics and providers begin to build realistic, AI-enabled workflows?
- And where are we already seeing AI deliver value?
AI in Action: Real-World Applications
Throughout the session, Dr. Osmond highlighted real examples of AI tools currently making waves in healthcare:
- Clinical Documentation: Tools like Nuance DAX Copilot, Microsoft Azure, and Suki.AI help automate note-taking and improve physician efficiency.
- Patient Communication: AI is now generating email responses via EPIC and DAX Copilot, lightening the admin load for busy clinicians.
- Radiology and Diagnostics: Platforms like Viz.AI assist with triage and interpretation in high-volume imaging environments.
- Cardiology: Tools like Cleerly are enabling more precise characterization of coronary artery disease, while Caption Health (GE) supports AI-guided echocardiograms by non-specialists.
- Pathology Diagnostics: Companies like PathAI, PaigeAI, PathologyWatch, and Proscia are transforming the pathology workflow.
- Genomics: Precision medicine platforms such as Tempus are bridging AI with genetic insights to personalize treatment.
Key Insights from Dr. Osmond’s Talk
1. Clinical Context Still Matters
One of the most practical takeaways? Always tell your pathologist what you think you’re sampling—even if you’re unsure. That clinical context shapes how the specimen is interpreted.
“It doesn’t matter if you’re right or wrong—it gives us context to help,” Dr. Osmond said.
For example, distinguishing between lichenoid keratosis and lichenoid interface dermatitis is largely a result of clinical context.
2. Frontline Providers Must Lead the AI Transition
As AI adoption accelerates, Dr. Osmond stressed the importance of input from practicing clinicians. Providers are best positioned to identify workflow friction, operational inefficiencies, and areas where automation makes a real difference.
“AI doesn’t need to be flashy—it needs to solve the right problem and fit into a feasible business model,” he noted.
In short: Those closest to the clinical work need to shape the tools, not just use them.
3. Population Health Needs Real-Time, Actionable Data
From wearable devices to remote patient monitoring, the potential for AI in population health is huge. But to make it work, organizations must link comprehensive clinical data with real-time inputs.
Dr. Osmond challenged the audience to think critically about incentives in value-based care, asking:
- What is the most actionable data?
- What operational model can turn that data into better outcomes?
- How do we build systems that are financially and logistically feasible?
AI in Healthcare: A Moral and Strategic Imperative
The talk ended with a provocative question: What is our obligation when AI or agentic workflows are objectively better—and already available?
The healthcare AI revolution isn’t on the horizon. It’s here. And according to Dr. Osmond, it’s up to providers and healthcare leaders to guide its ethical, effective, and scalable implementation.
“Physicians and healthcare organizations hold the key data. We also hold the responsibility to use it wisely.”
Final Thoughts
As the healthcare industry continues its shift toward proactive, data-driven, value-based models, the integration of AI into healthcare, especially through the lens of population health, isn’t just inevitable—it’s essential.
Dr. Osmond’s insights remind us that while the tools are evolving fast, the mission remains the same: provide high-quality care, reduce friction, and improve outcomes for the communities we serve.