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This study establishes a governance framework and roadmap for implementing artificial intelligence (AI) in clinical settings. It addresses key questions for AI tool selection, assessment, implementation, and monitoring to ensure patient safety and quality care.

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Area of Science:

  • Clinical Informatics
  • Healthcare Management
  • Artificial Intelligence in Medicine

Background:

  • Artificial intelligence (AI) is increasingly integrated into clinical practice.
  • Effective governance is crucial for managing AI implementation, maintenance, and monitoring.
  • Ensuring patient safety and quality care requires robust oversight structures.

Purpose of the Study:

  • To establish a framework for the infrastructure required for clinical AI implementation.
  • To present a roadmap for governing the use of AI tools in healthcare.
  • To address critical questions regarding AI tool selection, assessment, implementation, and post-implementation monitoring.

Main Methods:

  • Development of a governance framework for clinical AI.
  • Creation of a roadmap addressing key implementation and monitoring questions.
  • Analysis of challenges in AI governance for adaptive healthcare environments.

Main Results:

  • A comprehensive framework for clinical AI infrastructure is proposed.
  • A roadmap is provided to guide decisions on AI tool implementation and oversight.
  • Key considerations for assessing, implementing, and monitoring AI applications are outlined.

Conclusions:

  • Flexible and adaptive governance structures are essential for successful AI integration in healthcare.
  • The proposed framework and roadmap support quality patient care and practice improvement objectives.
  • Proactive governance is vital to navigate the evolving landscape of clinical AI.