Toward Successful Implementation of Artificial Intelligence in Health Care Practice: Protocol for a Research Program

Area of Science:

• Health Informatics
• Artificial Intelligence in Healthcare
• Implementation Science

Background:

• Artificial intelligence (AI) adoption in healthcare is nascent, lacking specific implementation guidance.
• Existing research highlights a gap between AI's potential and its integration into routine clinical practice.
• This program addresses the knowledge-practice gap through stakeholder collaboration and co-design.

Purpose of the Study:

• Develop a theoretically informed framework for AI implementation in health care.
• Conduct empirical studies to refine the AI implementation framework.
• Generate practical insights for successful AI integration into routine health care.

Main Methods:

• Utilize a logic model to structure framework development and evaluation.
• Employ theory-driven and co-produced methods for framework creation.
• Integrate literature reviews, co-design workshops, and empirical investigations with diverse stakeholders.

Main Results:

• Stage 1 activities (model overview, literature reviews, stakeholder mapping) commenced July 1, 2021.
• Stage 1 and Stage 2 activities are scheduled to conclude by June 30, 2026.
• The program is progressing through defined stages of framework development and empirical investigation.

Conclusions:

• There is a critical need for advancing theory and evidence on AI implementation in health care.
• This research program integrates theoretical and empirical approaches to enhance AI adoption.
• The goal is to increase the likelihood of successful and widespread AI application in clinical settings.