Managing Risk and Quality of AI in Healthcare: Are Hospitals Ready for Implementation?

Area of Science:

• Healthcare Management
• Artificial Intelligence in Medicine
• Health Informatics

Background:

• Artificial intelligence (AI) presents significant opportunities for future healthcare systems.
• Healthcare organizations face challenges in safely developing and procuring AI systems.
• Emerging regulations like the EU AI Act necessitate new management and quality assurance systems.

Purpose of the Study:

• To discuss challenges in AI implementation within healthcare settings.
• To identify potential gaps in current management systems (MS) using ISO 42001.
• To perform a gap analysis for AI MS in a tertiary acute hospital.

Main Methods:

• Review of the harmonized standard for AI MS, ISO 42001.
• Gap analysis conducted at a tertiary acute hospital with ongoing AI activities.
• Examination of industry-agnostic AI MS standards in the healthcare context.

Main Results:

• The examination of ISO 42001 revealed a technical debt within the healthcare sector regarding AI implementation.
• Existing management systems in healthcare organizations may not adequately address AI requirements.
• Findings align with previous research on digitalization challenges in healthcare.

Conclusions:

• Successful AI implementation in healthcare requires a strong organizational foundation.
• Emphasis must be placed on enhancing workforce capabilities and data infrastructure.
• Addressing these foundational elements is crucial for ensuring quality assurance in healthcare AI.