The Future Is Here: Integrating AI Into Oncology Nursing With Martin Michalowski, PhD, FAMIA, FIAHSI

Building Clinical Decision Support: The MitPlan System

Dr. Michalowski’s presentation centered on the development and application of clinical decision support systems (CDSS) in oncology, with a focus on a system called “MitPlan” (Mitigation Planning). He explained, “We use several AI techniques, including automated planning, explainable AI, data integration, and knowledge representation. Many different things go into solving that problem, which is quite a complex one.” The MitPlan system is designed to address treatment planning for patients with multiple comorbidities, integrating diverse data sources such as clinical practice guidelines and adverse reaction repositories.

A key feature of MitPlan is its emphasis on explainability. Dr. Michalowski noted, “What’s really important from the perspective of deploying these systems in practice is also explaining the rationale behind the decisions that were made as a way to increase trust in systems from a physician’s perspective, a nurse’s perspective, or a caregiver’s perspective, as a way for them to also be able to explain those decisions to the patient.”

AI as an Integrative Platform in Oncology Care

Dr. Michalowski highlighted the transformative potential of AI in integrating vast and varied healthcare data to support better treatment decisions. “AI provides a really good integrating platform, bringing all these data together in a way where you can then reason over these data and make better treatment decisions,” he explained. He emphasized that patient-centered approaches are increasingly possible, with AI systems able to incorporate patient preferences—such as concerns about medication costs or administration modes—into treatment planning.

Beyond decision support, Dr. Michalowski sees AI’s role spanning the entire healthcare process, from documentation and diagnostics to patient education. He advocates for nurses to be actively involved in the design, development, and deployment of these technologies, stating, “It’s a real opportunity, one that is being used in practice today and will only continue to be used even more.”

Research Landscape: From Methodology to Patient Outcomes

Regarding the current state of research, Dr. Michalowski observed, “We are far beyond the point of if these technologies will be integrated, but more when and to what extent.” He described a research landscape that ranges from methodological work—ensuring AI outputs are sound, explainable, and clinically useful—to studies focused on patient education and adherence. He pointed out, “There’s a lot of research showing that better outcomes don’t necessarily come from better drugs, but better adherence to existing treatments.”

Dr. Michalowski stressed the importance of nurse involvement in technology deployment, noting, “Nurses play a very important role in that process; they understand what the issues are and how to articulate those issues to more traditional technology or AI developers. The solutions developed need to really address important problems, rather than solutions being developed and then looking for problems.”

Staying Current: Practical Advice for Oncology Nurses

With the rapid evolution of AI, Dr. Michalowski acknowledged the challenge of staying up to date. He encouraged nurses to engage directly with consumer AI tools, which are now more accessible than ever: “There’s really no excuse not to use it in some way; everyone can use a large language model—ChatGPT, Perplexity, name your model. There’s a very friendly user interface that allows you to interact with the technology to see how it works, to start understanding a little bit of its limitations and its strengths.”

He advocates for raising basic AI competencies among nurses, not expecting them to become computer scientists, but to understand enough to make informed decisions about technology in practice. “If I ask a question—is a large language model or a deep learning approach appropriate here—I think current and future nurses should be able to answer that question,” he said.

Looking Ahead: The Future Nurse and Interdisciplinary Collaboration

Dr. Michalowski expressed optimism about the next generation of nurses, noting a shift in the skillsets of graduate nursing candidates: “I see these nursing candidates showing up interested in deep learning and data ethics and explainable AI, which is really encouraging for me.” He believes this trend will enable true interdisciplinary research and optimize patient outcomes.

He concluded, “It can make nurses’ lives much easier, and patients’ lives better. That’s very exciting, and I really am excited about what the future nurse will look like.”

Key Takeaways for Oncology Professionals

• Embrace AI as an Opportunity: Dr. Michalowski encourages oncology nurses to view AI as a tool to augment their capabilities and improve patient care, rather than as a threat. He emphasizes that AI technologies are here to stay and can significantly enhance the quality of care provided.
• Actively Engage with AI Tools: Nurses should actively use and explore consumer AI tools, such as large language models, to understand their capabilities and limitations. This hands-on experience will enable them to make informed decisions about technology implementation in their practice.
• Advocate for Nurse Involvement: Nurses play a crucial role in the development and deployment of AI technologies. Their unique understanding of clinical workflows and patient needs ensures that AI solutions address real-world problems and improve patient outcomes.
• Focus on Interdisciplinary Collaboration: The integration of AI in oncology nursing requires collaboration between nurses, technologists, and other healthcare professionals. By fostering interdisciplinary partnerships, healthcare teams can leverage AI to optimize patient care and outcomes.
• Raise AI Competencies: It is essential for nurses to develop a basic understanding of AI concepts and methodologies. This knowledge will empower them to participate in technology-related decisions and ensure that AI is used effectively and ethically in their practice.

About Dr. Michalowski

Martin Michalowski, PhD, FAMIA, FIAHSI, is a School of Nursing Foundation Research Professor and a Co-Director of the Center for Nursing Informatics at the University of Minnesota. He is also a co-leader of the Mobile Emergency Triage (MET) Research Group, an international research collaboration, and he serves as Co-Director of the Nursing and Artificial Intelligence Leadership Collaborative. Dr. Michalowski focuses on integrating AI technologies into nursing practice to improve patient outcomes. His work includes developing clinical decision support systems and advocating for increased AI competency among nurses.