Contributor – Cheryl J. Bostelman, MSN, RN
PhD student, Texas Woman’s University

The world of digital technology is rapidly expanding with new ideas and tools to better life for all. Healthcare has benefited from this technological growth. Artificial intelligence (AI) in healthcare is an asset. Yet, how is AI applicable to other areas of healthcare, such as palliative care? What are the pros and cons of AI usage in palliative care? The healthcare team gathers the information from current patient assessments and medical history, then enters the data into an AI-based machine. Per Ben Shetrit and colleagues (IMAJ, 2024), the AI machine creates an algorithm from the data that will be utilized for patient diagnoses, personalized care plans, and prognosis predictions. The cons to AI in palliative care are data security and privacy, machine bias, inaccurate predictions, and machine “stupidity” (the machine making errors), per Ben Shetrit and colleagues (IMAJ, 2024).

How does the use of AI affect palliative care patients in the long run? You have this machine that regurgitates entered data, yet does the outcome fit the patient and their needs? The main issue in the studies I read was insufficient information or research on the patient experience with AI. According to DePanfilis and colleagues (BMJSC, 2023), there was patient concern noted in the studies that the patient-healthcare provider experience would suffer due to the reliance upon AI by the healthcare provider. A machine can be impersonal and detached.

In Jean Watson’s Theory of Human Caring, nursing care is administered using a humanistic approach. Nursing care is a patient-centered pathway to the humanistic approach. The humanistic approach focuses on being mindful of prioritizing the cultural and spiritual needs of patients and their families (Wei & Watson, 2025). Palliative care patients need compassion, understanding, and empathy at this sensitive time. Ruland and Moore, in the Peaceful End-of-Life Theory, provide explanations of specific nursing approaches to support and achieve peaceful end-of-life conditions for the patient and families. Thesse conditions are: not being in pain, experience of comfort, experience of dignity/respect, being at peace, and closeness to significant others/persons who care

I would not want to interact with only a machine when I am navigating a terminal diagnosis. In nursing, human-to-human interaction is reassuring and calming. Healthcare providers need to interact with patients as well. A machine cannot assess a patient with only data. A complete head-to-toe assessment, along with labs and tests performed, will render a complete picture of the patient and the condition that is ailing them. By integrating Watson’s humanistic approach and AI, healthcare providers can then provide a treatment plan for that patient according to their palliative care-specific needs in a holistic manner with technology-enhanced support (Wei & Watson, 2025).

Another issue that needs to be addressed is the integration of AI into the palliative care treatment plan. Some patients may not have access to AI technologies due to socioeconomic reasons. The healthcare provider must think ahead. Is the palliative care plan too rigid in that only AI is used? Can the care plan be altered to accommodate AI technologies that the patient and/or insurance can afford? The healthcare provider and the interdisciplinary team need to be ready with a backup plan.

There are many types of digital technologies on the market. When choosing an AI machine for patient use, the healthcare provider must consider whether AI is user-friendly. Not everyone is computer savvy or mechanically inclined. For some people, computer and AI-machine usage can cause anxiety and frustration. Patients, family members, and/or friends will need time to learn how to use the AI machine. There will also be the need for a member of the healthcare team or the AI company that provided the machine to be available to answer any questions and troubleshoot problems as needed.
As Ben Shetrit and colleagues (IMAJ, 2024) observe, AI is used in providing palliative care based on their predictive capabilities, prognostic accuracy, and optimization of treatment as well as communication between patients and healthcare providers”. Of course, a machine cannot predict a patient’s exact moment of death. AI can indicate the possible life expectancy and the plan of care at the end of life.

The ultimate goal in palliative and end-of-life care planning is to provide patients with treatment plans that adhere to their specific needs and wishes at that point and time. Per Wicki and colleagues (PMR, 2024), healthcare providers ideally integrate individual differences and medical diagnoses, including the practical, psychosocial, and spiritual demands specific to the palliative care setting. Recognition of quality of life and patient autonomy is essential when utilizing AI in palliative care.

References

Ben Shetrit, S., Daghash, J., & Sperling, D. (2024). The use of artificial intelligence-based technologies in palliative-care: Advancing patient well-being at the end-of-life and enhancing the implementation of the dying patient act. The Israel Medical Association Journal: IMAJ, 26(2), 126-129. https://ima-files.s3.amazonaws.com/556971_441ca73b-75d2-426a-a06c-997e464121fe.pdf

DePanfilis, L., Peruselli, C., Tanzi, S., & Botrugno, C. (2023). AI-based clinical decision-making systems in palliative medicine: ethical challenges. BMJ supportive & palliative care, 13(2), 183-189. https://doi.org/10.1136/bmjspcare-2021-002948

Nursology.net (2025). Watson’s Theory and Philosophy of Human Caring/ Unitary Caring Science | Nursology

Ruland, C. M., & Moore, S. M. (1998). Theory construction based on standards of care: A proposed theory of the peaceful end of life. Nursing Outlook, 46(4), 169-175J. https://doi.org/10.1016/s0029-6554(98)90069-0

Wei, H., & Watson, J. (2025). Preserving Professional Human Caring in Nursing in the Era of Artificial Intelligence. ANS. Advances in nursing science, 10.1097/ANS.0000000000000573. Advance online publication. https://doi.org/10.1097/ANS.0000000000000573

Wicki, S., Clark, I.C., Amann, M., Christ, S.M., Schettle, M., Hertler, C., Theile, G., & Blum, D. (2024). Acceptance of digital technologies in palliative care patients. Palliative Medicine Reports, 5(1), 34-42. https://doi.org/10.1089/pmr.2023.0062

About Cheryl Bostelman

I’ve been a registered nurse since 2006, and I’m currently enrolled as a PhD student in the Nelda C. Stark College of Nursing at Texas Woman’s University. My research interest is in End-of-Life care education and its inclusion in BSN nursing curricula. In nursing programs, students are taught to administer nursing care across the human lifespan. The human population is aging, and population health is also declining. Death is a natural phenomenon that can occur at any time during the human lifespan. Undergraduate nursing students must receive clinical training to administer palliative and hospice care before graduating from baccalaureate nursing programs. According to the AACN guideline, it recommends that one of the four core “Spheres of Nursing Care” of the BSN curriculum be devoted to Palliative, Hospice, and Supportive Care.  My dissertation research focuses on “How Baccalaureate Nurse Educators form their opinions on the AACN Guideline for one of the four core ‘Spheres of Nursing Care’ of the BSN curriculum be devoted to Palliative, Hospice, and Supportive Care: A Qualitative Analysis”.