Recognising dying: Will artificial intelligence (AI) help improve clinical accuracy?

Area of Science:

• Palliative Care
• Medical Informatics
• Health Services Research

Background:

• The UK anticipates a significant increase in palliative care demand, necessitating improved methods for identifying patients nearing the end of life.
• Existing clinical prognostic tools exhibit limitations in accuracy and are susceptible to various biases.
• Artificial intelligence (AI) presents a potential solution for enhancing the prediction of patient deterioration and mortality.

Purpose of the Study:

• To explore the potential of AI in improving the prediction of end-of-life trajectories within palliative care.
• To identify key considerations for the ethical and effective integration of AI into palliative care services.
• To emphasize the irreplaceable human element in recognizing and responding to the needs of dying patients.

Main Methods:

• Review of current literature on AI applications in palliative care prognosis.
• Analysis of challenges and opportunities in implementing AI for end-of-life prediction.
• Discussion of ethical frameworks for human-AI collaboration in clinical settings.

Main Results:

• AI demonstrates promise in enhancing the accuracy of predicting patient deterioration and mortality.
• Early AI integration may support timely interventions and advance care planning.
• Critical factors for AI implementation include data integrity, accountability, and mitigating health inequities.

Conclusions:

• AI can augment clinical judgment in palliative care but cannot replace the human aspects of care.
• Successful AI adoption hinges on a collaborative approach, ensuring technology supports rather than supplants compassionate, person-centred care.
• Ethical considerations and a focus on equity are paramount for responsible AI implementation in end-of-life care.