The dawn of digital health technology in oncology care has arrived. As we witness the rapidly evolving changes in the artificial intelligence (AI) landscape, it is impossible to avoid deep concerns about the potential for widening health equity divides. Oncology has been a primary focus of AI research and development in health care due to AI’s ability to collect and process vast amounts of data in a fraction of the time humans and standard technologies can. AI applications in areas such as pathology, diagnostic imaging, risk prediction, and treatment planning, continue to hold promise in how we diagnose and treat cancer now and in the future.
Health equity has been defined as “systemic disparities in health between groups with different levels of underlying social advantage or disadvantage.”1 The application and utilization of digital health technologies now require multiple and varied resources. Resources such as trained staff for patient navigation and support, technological infrastructure, costly digital devices and software applications, reliable internet, multi-language applications, large unbiased data sets, and an ability to integrate the influence of race and socio-economic status on health outcomes. The existence of a “digital divide,” which refers to the inequitable distribution of digital technologies and the individual and community’s ability to invest in technology, all contribute to the potential for creating significant disparities in equity in oncology care.
Systemic barriers in access to care that have historically existed in marginalized and underserved populations risk deepening the digital divide. In 2022, Canadian researchers completed a literature review on the potential impacts of AI technologies on health equity in oncology. Multiple themes were revealed in the review, including AI’s potential ability to help address health disparities, mitigate bias, and identify social determinants of health. The review also suggested that significant gaps remain in evidential literature related to the ethical challenges in lower-resourced countries. So how do we support the development and implementation of AI technologies that have the potential to revolutionize how society and science treats cancer and commit to ensuring fair, sustainable, and equitable access to them for all?
When we examine the scope of advancements in our decades-long effort to outsmart cancer, we are eager to tap into what may significantly alter the cancer experience for human beings. Have we finally found in AI technology the ultimate weapon in our fight against cancer, but simultaneously risk creating a chasm of inequity? Cancer remains the leading cause of death in the United States. As oncology social workers we see intimately how lives are lost every day. Protecting the human relationship in the care we provide will be of primary importance as we look ahead.
The current dialogue among oncology professionals recognizes that to proceed in an ethical and equitable manner, we must build an infrastructure that emphasizes trust and transparency, but most of all patience. The greatest error we could commit now is in our haste to be first, we put equity last. The need for multidisciplinary collaboration between all stakeholders, including clinicians, tech engineers, social scientists, patients, advocates, governmental agencies, and ethicists, who can prioritize technologies that have the potential to flourish in even the lowest-resourced settings. To achieve this goal, a global health perspective will be required, which unites populations and tech communities in their commitment to build a technological infrastructure that is understandable and accessible to all, with representation from underserved communities in its design and governmental oversight to ensure universal guardrails. The continued collection of data that represents an entire cross-section of individuals from various backgrounds will be one of the biggest challenges. It will require innovation and dedication, putting people first and revenue last, and it will be healthcare’s next enormous challenge and potentially one of its shining moments.
Individuals who live in low-resourced areas and have low health and digital literacy remain the most vulnerable individuals in their ability to navigate new health care technologies. Studies have demonstrated that they often lack the ability to access digital health resources, including information related to the prevention, diagnosis, and treatment of cancer, or access to specialists in their communities. Suggestions for bridging these gaps are now beginning to be explored. The intersection of AI, global health, and cancer care must include all the essential stakeholders who are committed to investing in vulnerable communities. Designing a technology infrastructure that promotes accessibility and incorporates low-barrier and low-cost parameters will be essential. Higher-resourced settings must work alongside lower-resourced settings in the design, integration, and implementation of digital health technology.
Oncology navigation will be a key function in the integration and application of AI technologies in the near future. Oncology social work as a profession should be well positioned to be involved in the design, utilization, and integration of these new technologies and should commit to serve as informed advocates for our patients, particularly those who have experienced systemic barriers in accessing, navigating, and utilizing health care technology. Oncology social work as a profession may consider AI applications in oncology care as an opportunity to design an ethical framework of deliverable services from the ground up, with a goal of global health equity at the forefront. Aligning the profession to maintain high ethical standards and trained clinicians in the implementation of AI in oncology care should be foremost and with a commitment to address potential pitfalls around accessibility.
Through careful, thoughtful, design and integration, as well as the dedicated engagement of numerous stakeholders from multidisciplinary perspectives, we can achieve the balance between scientific advancement for the benefit of all human beings and be at the forefront of what could be the one of the greatest evolutions in oncology care we have ever seen.
Are you interested in learning more about AI advancements in oncology care and the role of oncology social work? Please join AOSW’s newest AI SIG. They meet on the second Tuesday of every month from 12:00-1:00pm E.T. They won’t be meeting in December but will resume on January 11, 2027. Please reach out to co-leaders, Daniel Gaylor (Daniel.Gaylor@moffit.org) and Amy Colver (amy.colver04@gmail.com) with any questions.
References
- Bravemen, P. Gruskin S. Defining Equity in Health. J Epidemiol Community Health 2003, Apr. 57 (4) 254-258
