Opportunities and Barriers to Artificial Intelligence Adoption in Palliative/Hospice Care for Underrepresented Groups

Underrepresented groups (URGs) in the United States, including African Americans, Latino/Hispanic Americans, Asian Pacific Islanders, and Native Americans, face significant barriers to accessing hospice and palliative care. Factors such as language barriers, cultural perceptions, and mistrust in healthcare systems contribute to the underutilization of these services. Recent advancements in artificial intelligence (AI) offer potential solutions to these challenges by enhancing cultural sensitivity, improving communication, and personalizing care. This article aims to synthesize the literature on AI in palliative/hospice care for URGs through the Technology Acceptance Model (TAM), highlighting current research and application in practice. The scoping review methodology, based on the framework developed by Arksey and O’Malley, was applied to rapidly map the field of AI in palliative and hospice care. A systematic search was conducted in 9 databases to identify studies examining AI applications in hospice and palliative care for URGs. Articles were independently assessed by 2 reviewers and then synthesized via narrative review through the lens of the TAM framework, which focuses on technology acceptance factors such as perceived ease of use and usefulness. Seventeen studies were identified. Findings suggest that AI has the potential to improve decision-making, enhance timely palliative care referrals, and bridge language and cultural gaps. Artificial intelligence tools were found to improve predictive accuracy, support serious illness communication, and assist in addressing language barriers, thus promoting equitable care for URGs. However, barriers such as limited generalizability, biases in data, and challenges in infrastructure were noted, hindering the full adoption of AI in hospice settings. Artificial intelligence has transformative potential to improve hospice care for URGs by enhancing cultural sensitivity, improving communication, and enabling more timely interventions. However, to fully realize its potential, AI solutions must address data biases, infrastructure limitations, and cultural nuances. Future research should prioritize developing culturally competent AI tools that are transparent, explainable, and scalable to ensure equitable access to hospice and palliative care services for all populations.