Abstract
Background: Family engagement is critical in the implementation of artificial intelligence (AI)-based clinical decision support tools, which will play an increasing role in health care in the future. We sought to understand parental perceptions of computer-assisted health care of children in the emergency department (ED). Methods: We conducted a population-weighted household panel survey of parents with minor children in their home in a large US city to evaluate perceptions of the use of computer programs for the care of children with respiratory illness. We identified demographics associated with discomfort with AI using survey-weighted logistic regression. Results: Surveys were completed by 1620 parents (panel response rate = 49.7%). Most respondents were comfortable with the use of computer programs to determine the need for antibiotics (77.6%) or bloodwork (76.5%), and to interpret radiographs (77.5%). In multivariable analysis, Black non-Hispanic parents reported greater discomfort with AI relative to White non-Hispanic parents (odds ratio [OR] 1.67, 95% confidence interval [CI] 1.03–2.70) as did younger parents (18–25 years) relative to parents ≥46 years (OR 2.48, 95% CI 1.31–4.67). The greatest perceived benefits of computer programs were finding something a human would miss (64.2%, 95% CI 60.9%–67.4%) and obtaining a more rapid diagnosis (59.6%; 56.2%–62.9%). Areas of greatest concern were diagnostic errors (63.0%, 95% CI 59.6%–66.4%), and recommending incorrect treatment (58.9%, 95% CI 55.5%–62.3%). Conclusions: Parents were generally receptive to computer-assisted management of children with respiratory illnesses in the ED, though reservations emerged. Black non-Hispanic and younger parents were more likely to express discomfort about AI.
Original language | English (US) |
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Pages (from-to) | 140-147 |
Number of pages | 8 |
Journal | Academic Pediatrics |
Volume | 23 |
Issue number | 1 |
DOIs | |
State | Published - Jan 1 2023 |
Funding
Financial statement: An anonymous family foundation dedicated to supporting research that advances community health in low-resource neighborhoods and the Patrick M. Magoon Institute for Healthy Communities. SR is sponsored by the PEDSnet Scholars Training Program (Department of Pediatrics, Ann and Robert H Lurie Children's Hospital of Chicago).
Keywords
- artificial intelligence
- clinical decision support
- emergency care
- pediatrics
- stakeholder engagement
ASJC Scopus subject areas
- Pediatrics, Perinatology, and Child Health