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

Abstract

Arian Ranjbar,1 Eilin Wermundsen Mork,1 Jesper Ravn,1 Helga Brøgger,2 Per Myrseth,2 Hans Peter Østrem,3 Harry Hallock2 1Medical Technology and E-Health, Akershus University Hospital, Lørenskog, Norway; 2Group Research and Development, DNV AS, Høvik, Norway; 3Business Assurance, DNV AS, Høvik, NorwayCorrespondence: Arian Ranjbar, Akershus University Hospital, Sykehusveien 25, 1478, Lørenskog, Norway, Tel [phone], Email [email protected]: Artificial intelligence (AI) provides a unique opportunity to help meet the demands of the future healthcare system. However, hospitals may not be well equipped to handle safe and effective development and/or procurement of AI systems. Furthermore, upcoming regulations such as the EU AI Act may enforce the need to establish new management systems, quality assurance and control mechanisms, novel to healthcare organizations. This paper discusses challenges in AI implementation, particularly potential gaps in current management systems (MS), by reviewing the harmonized standard for AI MS, ISO 42001, as part of a gap analysis of a tertiary acute hospital with ongoing AI activities. Examination of the industry agnostic ISO 42001 reveals a technical debt within healthcare, aligning with previous research on digitalization and AI implementation. To successfully implement AI with quality assurance in mind, emphasis should be put on the foundation and structure of the healthcare organizations, including both workforce and data infrastructure.Keywords: artificial intelligence, management systems, quality assurance, risk management, implementation

Keywords

• artificial intelligence
• management systems
• quality assurance
• risk management
• implementation