AI does not necessarily lead to more efficiency in clinical practice

The use of artificial intelligence (AI) in hospitals and patient care is steadily increasing. Especially in specialist areas with a high proportion of imaging, such as radiology, AI has long been part of everyday clinical practice.

However, the question of the extent to which AI actually influences workflows in a clinical setting remains largely unanswered. Researchers at the University Hospital Bonn (UKB) and the University of Bonn have therefore conducted a comprehensive analysis of existing studies on the effect of AI. They were able to show that AI does not automatically lead to an acceleration of work processes. Their results have now been published in the journal npj Digital Medicine.

Although AI is often seen as a solution for handling routine tasks such as monitoring patients, documenting care tasks and supporting clinical decisions, the actual effects on work processes are unclear. Particularly in data-intensive specialties such as genomics, pathology and radiology, where AI is already being used to recognise patterns in large amounts of data and prioritise cases, there is a lack of reliable data on efficiency gains.

"We wanted to find out to what extent AI solutions actually improve efficiency in medical imaging," explains Katharina Wenderott, lead author of the study and a doctoral student at the University of Bonn at the UKB's Institute for Patient Safety (IfPS). "The widespread assumption that AI automatically speeds up work processes often falls short."

"Our results make it clear that the use of AI in everyday clinical practice must be considered in a differentiated way," emphasises Prof. Matthias Weigl, Director of the IfPS at the UKB, who also conducts research at the University of Bonn. "Local conditions and individual work processes have a major influence on the success of implementation."

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Source: Digital Health News, 18 October 2024