How AI, Data, and Real-World Evidence Are Transforming Oncology Clinical Pathways
Every day, I see how technology can either add to or reduce the complexity of cancer care. The difference isn't the technology itself. It's whether we design it around the needs of clinicians and patients. That's why I believe the future of clinical pathways isn't simply about adopting artificial intelligence (AI). It's about using AI, data, and real-world evidence to make care more connected, more actionable, and ultimately more human.
The pace of change in oncology continues to accelerate. New therapies, expanding clinical evidence, and growing expectations for personalized care mean that pathway programs need to evolve just as quickly. I don't believe the question is whether AI belongs in oncology anymore. The more important question is how we can apply these technologies responsibly to improve decision making while maintaining clinician trust and keeping patients at the center of care.
Technology Should Support Clinical Decision Making
When people hear "AI," they often think about replacing human expertise. I see it differently.
Artificial intelligence is technology that analyzes large amounts of information to identify meaningful patterns and insights. Combined with real-world evidence, which is information gathered during routine patient care outside of traditional clinical trials, AI can help pathway teams identify opportunities, incorporate new evidence more efficiently, and better understand how treatments perform in everyday practice.
Technology should never replace clinical judgment. Instead, it should give clinicians better information at the right moment, reduce administrative burden, and allow them to spend more time focusing on patients.
Building the Next Generation of Clinical Pathways
Creating more intelligent clinical pathways requires more than adopting new technology. It requires building an ecosystem where data, people, and processes work together.
Organizations preparing for the future should focus on:
- Building trusted, high-quality data infrastructure.
- Improving interoperability so information flows across the care continuum.
- Establishing governance that promotes transparency and responsible AI use.
- Using real-world evidence to continuously evaluate and refine pathways.
- Designing solutions that fit naturally into clinician workflows and encourage adoption.
These are not future challenges. They are priorities that oncology organizations are working through today.
Why These Conversations Matter
One of the reasons I'm excited about Clinical Pathways Congress 2026 is that the discussions focus on implementation rather than speculation. The meeting brings together clinicians, pathway leaders, health systems, payers, researchers, and innovators who are all working toward the same goal: improving cancer care through practical collaboration and shared learning.
I'm especially looking forward to participating in Pathway Design 2.0: Integrating Data, AI, and Real-World Evidence. During this session, we'll discuss practical approaches for designing dynamic, data-driven pathways while addressing interoperability, governance, and clinician adoption. More importantly, we'll explore how organizations can move beyond the excitement surrounding AI and begin applying these tools in ways that produce measurable value for clinicians, health systems, and patients.
If your organization is asking how to prepare for the next generation of oncology care, I encourage you to join us in Boston for Clinical Pathways Congress 2026. The conversations happening there will focus on real-world solutions that organizations can take home and begin implementing immediately. I hope you'll join us and be part of shaping the future of oncology clinical pathways.
Event Details
Clinical Pathways Congress 2026
- Dates: November 10-11, 2026
- Location: Four Seasons Hotel Boston
- Event Website: https://www.hmpglobalevents.com/cpc
- Registration: https://www.hmpglobalevents.com/cpc/rates
Session Information
- Pathway Design 2.0: Integrating Data, AI, and Real-World Evidence
- Date/Time: November 10, 1:15 PM – 2:00 PM
- Summary: Explore how data, real-world evidence, and AI are reshaping pathway design and implementation. Learn practical approaches to building dynamic, data-driven pathways while addressing interoperability, governance, and clinician adoption challenges.
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