Realizing the potential of artificial intelligence in healthcare: Learning from intervention, innovation,...

Area of Science:

• Intervention science
• Innovation science
• Implementation science
• Improvement science

Background:

• Artificial intelligence (AI) is crucial for health systems, but factors influencing its implementation and routine use are under-researched.
• Understanding AI's interaction with healthcare contexts and its contribution to health system goals requires further investigation.

Purpose of the Study:

• To describe four scientific fields: intervention, innovation, implementation, and improvement sciences.
• To identify relevant knowledge from these fields for understanding and facilitating AI use in healthcare.

Main Methods:

• Authors' expertise in intervention, innovation, implementation, and improvement sciences.
• Selective literature review.

Main Results:

• These four fields offer substantial, often overlapping, knowledge relevant to AI in healthcare.
• Existing knowledge provides a foundation for AI in healthcare research.

Conclusions:

• Repurposing knowledge from these fields for AI studies requires careful consideration and exploration.
• Inductive research approaches are essential for generating new knowledge to realize AI's potential in healthcare.