Implementing and Scaling Commercial AI in Public Healthcare Settings: Experiences from Norway

Area of Science:

• Health Informatics
• Artificial Intelligence in Healthcare
• Process Evaluation

Background:

• Implementing commercial AI applications in healthcare settings presents unique challenges.
• Understanding the critical factors for successful AI adoption is essential for healthcare organizations.

Purpose of the Study:

• To conduct a formative process evaluation of AI application implementation in a Norwegian hospital trust.
• To identify key areas critical for successful AI adoption in a healthcare setting.

Main Methods:

• A bottom-up implementation strategy was developed, emphasizing a "learning by doing" approach.
• An iterative implementation method, refined across multiple hospitals, was employed.
• Extensive stakeholder involvement and rigorous quality assurance were prioritized.

Main Results:

• The study identified three critical areas for AI adoption: implementation strategies, methods, and effects/values.
• The "learning by doing" strategy and iterative methods fostered enhanced digital maturity.
• Early benefits realization, strengthened user trust, and engagement were key outcomes.

Conclusions:

• A collaborative, iterative approach to AI implementation is crucial for healthcare settings.
• User trust and engagement are vital for the sustained adoption of AI applications.
• The findings offer valuable insights for hospitals implementing AI solutions.