Leveraging Artificial Intelligence/Machine Learning Models to Identify Potential Palliative Care Beneficiaries: A...

Area of Science:

• Gerontology
• Health Informatics
• Computational Medicine

Background:

• Palliative care aims to improve quality of life for patients with serious illnesses.
• Identifying eligible patients for palliative care can be challenging, especially in chronic and terminal conditions.
• Artificial intelligence (AI) and machine learning (ML) offer novel approaches to patient identification.

Approach:

• A systematic review of electronic databases was performed.
• Five studies meeting inclusion criteria were analyzed.
• AI/ML models were examined for their application in predicting palliative care needs.

Key Points:

• Five studies utilized supervised ML algorithms; one employed natural language processing with deep learning.
• Commonly used AI/ML algorithms included neural networks, logistic regression, and tree-based models.
• Models predicted outcomes such as mortality and service needs relevant to palliative care.

Conclusions:

• AI and ML models present a promising method for identifying palliative care beneficiaries.
• Early identification through AI can facilitate timely and targeted palliative care interventions.
• The evolving capabilities of AI hold significant potential to transform palliative care delivery.