City Research Online

Abstract

This paper investigates healthcare policymakers’ and professionals’ perceptions of Artificial Intelligence (AI) Machine Learning (ML) Decision Tree Models and their potential effects on clinical work processes. Semi-structured interviews with Dutch participants revealed nine key themes and 16 subthemes. Findings indicate that AI models are seen as supportive tools that can enhance care quality by automating repetitive tasks, freeing up time for patient-centred care. However, there is scepticism about significant time savings and increased patient turnover. Both groups emphasise the need for seamless integration with existing systems and comprehensive training to mitigate risks and improve adoption.

Publication Type:	Article
Additional Information:	© The Authors. Published by IOS Press. This is an open-access article distributed under the terms of Creative Commons: Attribution NonCommercial License 4.0 (http://creativecommons.org/licenses/by-nc/4.0/).
Publisher Keywords:	Machine Learning; Health Personnel; Policymakers
Subjects:	H Social Sciences > HN Social history and conditions. Social problems. Social reform Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Departments:	School of Health & Medical Sciences School of Health & Medical Sciences > Department of Population Health & Policy
SWORD Depositor:	Symplectic Administrator

Export

Downloads