Perceptions of Artificial Intelligence-Assisted Care for Children With a Respiratory Complaint

Abstract

OBJECTIVES To evaluate caregiver opinions on the use of artificial intelligence (AI)-assisted medical decision-making for children with a respiratory complaint in the emergency department (ED). METHODS We surveyed a sample of caregivers of children presenting to a pediatric ED with a respiratory complaint. We assessed caregiver opinions with respect to AI, defined as “specialized computer programs” that “help make decisions about the best way to care for children.” We performed multivariable logistic regression to identify factors associated with discomfort with AI-assisted decision-making. RESULTS Of 279 caregivers who were approached, 254 (91.0%) participated. Most indicated they would want to know if AI was being used for their child’s health care (93.5%) and were extremely or somewhat comfortable with the use of AI in deciding the need for blood (87.9%) and viral testing (87.6%), interpreting chest radiography (84.6%), and determining need for hospitalization (78.9%). In multivariable analysis, caregiver age of 30 to 37 years (adjusted odds ratio [aOR] 3.67, 95% confidence interval [CI] 1.43–9.38; relative to 18–29 years) and a diagnosis of bronchospasm (aOR 5.77, 95% CI 1.24–30.28 relative to asthma) were associated with greater discomfort with AI. Caregivers with children being admitted to the hospital (aOR 0.23, 95% CI 0.09–0.50) had less discomfort with AI. CONCLUSIONS Caregivers were receptive toward the use of AI-assisted decision-making. Some subgroups (caregivers aged 30–37 years with children discharged from the ED) demonstrated greater discomfort with AI. Engaging with these subgroups should be considered when developing AI applications for acute care.