A survey of patient acceptability of the use of artificial intelligence in the diagnosis of paediatric fractures: an observational study

Abstract

INTRODUCTION: This study aimed to assess carer attitudes towards the use of artificial intelligence (AI) in management of fractures in paediatric patients. As fracture clinic services come under increasing pressure, innovative solutions are needed to combat rising demand. AI programs can be used to diagnosis fractures, but patient perceptions towards its use are uncertain. METHODS: We conducted a cross-sectional survey of carers of paediatric patients presenting to fracture clinic at a tertiary care centre, combining single-best-answer questions and Likert-type questions. We investigated patient perception of clinical review in the emergency department (ED), disruption to school to attend fracture clinic, and attitudes towards AI. RESULTS: Of the paediatric fracture patients participating in this study, 45% were seen within two hours, 29% were seen between two and four hours, and 26% were seen after four hours; 75% were seen by both a nurse and a doctor, 16% were seen only by a nurse and 9% only by a doctor. A total of 61% of children had to take time off school for their appointment and 59% of parents had to take time off. Of all respondents, 56% agreed that more research is needed to reduce waiting times, 76% preferred a nurse or doctor to review their child's radiograph, 64% were happy for an AI program to diagnose their child's fracture, and 82% were happy with an AI program being used as an adjunct to a clinician's diagnosis. CONCLUSIONS: Carer perceptions towards the use of AI in this setting are positive. However, they are not yet ready to relinquish human decision making to automated systems.

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