Artificial Intelligence in UK Hospital Medicine: From Innovation to Implementation

Area of Science:

• Healthcare Technology
• Medical Informatics
• Clinical AI

Background:

• The UK healthcare system faces increasing pressure, with Artificial Intelligence (AI) offering potential solutions.
• Expanding AI applications necessitate healthcare professionals understanding the research-to-clinical translation process.
• Successful AI integration requires navigating distinct stages from development to deployment.

Purpose of the Study:

• To provide a structured overview of the AI adoption pathway in healthcare.
• To support clinicians in critically appraising AI's potential and limitations.
• To facilitate informed engagement and optimal integration of AI into clinical practice.

Main Methods:

• Review of the stages involved in translating AI research into clinical application.
• Analysis of challenges and opportunities at each step of the AI adoption pathway.
• Focus on clinician understanding of AI capabilities and limitations.

Main Results:

• AI adoption involves sequential steps: data training/validation, evidence generation, regulatory compliance, procurement, clinical implementation, and monitoring.
• Each stage presents unique challenges impacting successful AI integration.
• Clinicians need to understand AI to ensure appropriate and effective use.

Conclusions:

• A structured understanding of the AI adoption pathway is crucial for healthcare professionals.
• Informed appraisal and optimisation of AI integration can enhance patient care.
• Effective engagement with AI requires knowledge of its capabilities, limitations, and implementation processes.