Transforming Oncology Care Through Technological Innovation

In discussions about technological innovation in cancer care, artificial intelligence (AI) is at the forefront. AI has gone beyond easing administrative burdens and expediting repetitive tasks, as leaders in oncology are looking to utilize this technology to support clinical decision making and create personalized treatment plans, while maintaining the element of human compassion that only health care professionals can provide.

Attendees of the ACCC 51st Annual Meeting and Cancer Center Business Summit (#AMCCBS) had the opportunity to attend 2 expert-led breakfast tech sessions on Day 2 of the conference that addressed the integration of technology and AI into oncology and their future in the cancer care continuum.

Accelerating ROI for Community Cancer Centers With AI-Powered Decision Making

The first session, led by Talha Basit, CEO of Spiraldot Health, was centered around the ways AI-driven tools can have a massive positive impact on community cancer centers, for whom balancing efficiency with patient-centered care remains an ongoing struggle. Coupled with the pressure of the growing shortage of oncologists, staff burnout, and administrative burdens, the field of oncology faces significant challenges. In response, Basit introduced Spiraldot’s AI-powered clinical decision support tool designed to help community cancer centers deliver high-quality care despite limited resources. 

In a time when AI must prove its reliability and effectiveness, Spiraldot is committed to supporting clinicians, but never replacing them. “We don’t want to replace clinicians; we want to give them superpowers,” Basit asserted. “Providers are burnt out, and we want to support them so they can give the best care possible.” 

Created by staff who have previously worked in health care and designed from the viewpoint of supporting clinicians, Spiraldot’s AI-powered tool is embedded directly within electronic health record (EHR) systems. This seamless integration eliminates the need for clinicians to learn new software and provides real-time insights about patients and their clinical data. Spiraldot also offers AI-driven tumor board support to reduce the administrative burden associated with case preparation; real-time patient insights tailored to each clinical profile; and automated workflows that improve eligibility, appeals, and clinical trial matching. 

Basit emphasized the need to differentiate between genuine AI-driven solutions for oncology and the widespread release of generalized AI models. Large language models like ChatGPT are meant to produce text based on a specific prompt using diverse datasets, while machine learning can be used for classification or prediction and uses a defined, limited data set. Spiraldot has set itself apart by incorporating machine learning into every part of its product stack. “True AI innovation in oncology goes beyond simple automation,” argued Basit. “It actively enhances clinical decision making by integrating public and private datasets, which enables comprehensive, up-to-date treatment insights. 

Expanding AI’s Role in Community Cancer Centers 

As community cancer centers navigate financial pressures and regulatory demands, AI-powered solutions are becoming essential for their sustainability. Spiraldot’s platform extends beyond clinical decision-making support to help institutions optimize revenue cycles, streamline administrative workflows, and improve patient engagement. “If you’re in a community cancer center and don’t have the extensive resources that a large academic center might have, this tool can pull that information for you,” explained Basit. By leveraging AI insights, centers can enhance operational efficiency, reduce costs, and focus on delivering high-quality care. 

AI can also assist in identifying high-risk patients, which then enables providers to implement proactive interventions and personalized treatment plans. This not only improves patient outcomes but also strengthens the financial health of oncology programs by reducing hospital readmissions and ensuring appropriate reimbursement for services. Additionally, Spiraldot’s EHR diagnostic and metrics dashboard allows cancer centers to track key performance indicators, ensuring adherence to accreditation requirements and improving patient care. 

For cancer centers struggling with resource constraints, AI-powered decision support is no longer a luxury—it's a necessity. Leveraging the right solutions ensures that the future of oncology care will be both more efficient and more patient-focused.

Maintaining Human Expertise: The Key to Safe AI Integration

As the AI revolution continues to transform health care, particularly oncology, the conversation regarding balancing technology with human expertise becomes increasingly important. Dave Stewart, President of Path Forward IT, spoke to this issue in the second breakfast tech session of the day at AMCCBS, emphasizing that while AI continues to enhance cancer care, human clinicians must remain at the forefront of decision making.

From enabling early detection and personalized treatment plans to providing predictive analysis, AI is significantly improving the efficiency of diagnosis and reducing the potential for human error. More importantly, it’s helping clinicians deliver better outcomes for patients by identifying subtle patterns and insights that might otherwise be missed.

However, as Stewart noted, AI should not be seen as a crutch or a replacement for human expertise. “Being able to use AI in an effective way means understanding how it works and what it’s doing behind the scenes,” he explained. This understanding is critical because when AI falters or returns results that seem inaccurate, clinicians need to be able to recognize the discrepancy and take action. AI, like any tool, has limitations, and it’s vital that health care professionals maintain a strong grasp of their foundational clinical knowledge to identify when things go awry.

To avoid an overreliance on technology, Stewart recommended implementing AI-free diagnostic training sessions. These sessions force clinicians to rely on their own expertise rather than defaulting to the AI-powered systems they may be accustomed to. This approach ensures that doctors and medical staff continue to develop their critical thinking skills and don’t lose sight of the very knowledge that makes them experts in their field.

Another key point Stewart highlighted was the need for regular manual verification of AI output. This ensures that AI tools remain transparent and trustworthy. By checking AI results manually, providers can cross-check and confirm diagnoses, helping to reduce the risk of errors or algorithmic bias.

Stewart’s approach to AI in health care is succinct: “I like to approach technology as a key enabler for health care, but not a dependency.” The true goal, he explained, is not to resist AI but to ensure that it complements, rather than replaces, the expertise of clinicians. With the right training and strategies, AI can be an invaluable tool—but it should always support, never supplant, the vital human judgment and intuition that are central to quality care.

The recurring theme of Stewart’s presentation is clear: True progress in oncology isn’t driven solely by AI. It’s about striking the right balance between cutting-edge technology and the timeless clinical expertise that forms the foundation of medicine. Health care leaders must prioritize training for scenarios where AI might fail, ensuring that the system remains resilient and clinicians are ready to step in when necessary. By integrating AI thoughtfully and maintaining the balance between technology and expertise, we can ensure that the future of cancer care remains both innovative and deeply human.

Read more coverage of the 51st AMCCBS on the ACCCBuzz Blog.