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Episode 425: How AI Can Help Healthcare Organizations Improve the Cancer Experience

The ONS Podcast

Release Date: 07/24/2026

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“In oncology specifically, where care is complex, artificial intelligence (AI) can really synthesize large volumes of clinical information, flag risks such as treatment complications, and support adherence to evidence-based pathways. For nurses specifically, this enables them more time for direct patient care, clinical judgment, and care coordination, and really practice to the top of their license while reducing repetitive time and administrative tasks,” Jenn Frith, DNP, RN, OCN®, NE-BC, associate vice president of clinical operations at Duke Cancer Institute in Durham, NC, told Jaime...

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“In oncology specifically, where care is complex, artificial intelligence (AI) can really synthesize large volumes of clinical information, flag risks such as treatment complications, and support adherence to evidence-based pathways. For nurses specifically, this enables them more time for direct patient care, clinical judgment, and care coordination, and really practice to the top of their license while reducing repetitive time and administrative tasks,” Jenn Frith, DNP, RN, OCN®, NE-BC, associate vice president of clinical operations at Duke Cancer Institute in Durham, NC, told Jaime Weimer, MSN, RN, AGCNS-BS, AOCNS®, manager of oncology nursing practice at ONS. Weimer spoke with Frith and Emily Norboge, director of clinical and research informatics at Duke Cancer Institute, about how AI can help healthcare organizations improve the cancer experience. 

Music Credit: “Fireflies and Stardust” by Kevin MacLeod

Licensed under Creative Commons by Attribution 3.0 

Earn 0.5 contact hours of nursing continuing professional development (NCPD) by listening to the full recording and completing an evaluation at courses.ons.org by July 24, 2027. The planners and faculty for this episode have no relevant financial relationships with ineligible companies to disclose. ONS is accredited as a provider of nursing continuing professional development by the American Nurses Credentialing Center’s Commission on Accreditation.

Learning outcome: Learners will report an increase in knowledge related to the use of artificial intelligence in oncology nursing practice.

Episode Notes 

To discuss the information in this episode with other oncology nurses, visit the ONS Communities

To find resources for creating an ONS Podcast club in your chapter or nursing community, visit the ONS Podcast Library.

To provide feedback or otherwise reach ONS about the podcast, email pubONSVoice@ons.org.

Highlights From This Episode

Norboge: “Our AI voice agent has a series of workflows that it can execute. ... If a patient needs help with medical paperwork, the agent will walk the patient through how to do that paperwork. If a patient has a question that they need sent to their provider, it can document that and then send a message to the provider. There’s a series of workflows so it can route to scheduling. It can answer information about test results that is compliant with our policy around test results. The goal of that agent is that it will handle all of those administrative-type tasks that don’t necessarily require a nurse to fill.” TS 5:44

Norboge: “When [patients] call the nurse triage line, the nurse will have to say, ‘I understand you want your test results. I can contact your provider and have them reach out to you about your results.’ But that’s kind of where it ends. What we worked out with the agent is if a patient calls and says, ‘I really want my test results,’ they will in a very nice, standard way, say something similar. You know, ‘I’m not authorized to discuss your test results with you, but I’d be happy to send a message to your provider and ask them to call you.’ But then the agent goes one step further and says, ‘Are you experiencing anxiety about your test results? If so, I can transfer you to the nurse to discuss support for a potential referral to family medical therapy if you would like help managing that anxiety.’ In a clear, helpful way, it can define and help a patient with their needs and not just have a standard of ‘this is our policy and I can’t share it with you.’” TS 11:14

Frith: “Really, transparency is the key. The patient should understand that AI is used more as an enhancement, but not to replace the human connection. That’s not the goal. The nurses can explain that the tools will help ensure accuracy, timeliness, and safety while allowing more time for the direct interaction of the nurse. I think framing AI as an additional layer of support rather than a decision maker helps build trust. And I think maintaining strong communication and presence at the bedside just reinforces that care remains fundamentally human.” TS 15:32

Frith: “I think AI in oncology is going to continue to advance in our predictive analytics, personal care planning, and probably real-time decision support. I think we’ll see a greater integration into symptom management, some early detection of complications, and longitudinal care coordination across our settings. I think nurses will continue to increasingly use AI to anticipate patient needs and prioritize care. I think the role of the nurse won’t diminish. Rather, it will become more elevated in allowing them to practice to scope of practice.” TS 19:58

Frith: “AI represents a meaningful opportunity to strengthen oncology nursing practice by reducing burden and enhancing the clinical insight. It needs to be a very thoughtful implementation. We talked about having strong governance and continued investment in the nursing workforce. I want to reinforce that oncology care remains deeply human, and AI should only be viewed as a tool that enables the nurses to do what they do best, which I feel is deliver safe, compassionate, and high-quality specialized care to our most vulnerable patients.” TS 27:31