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Parental perceptions on use of artificial intelligence in pediatric acute care

  • Sriram Ramgopal
    Correspondence
    Address correspondence to: Sriram Ramgopal, MD, Division of Pediatric Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, 225 E Chicago Ave, Box 62, Chicago, IL 60611, Phone: (312) 227-8237, Fax: (312) 227-9475
    Affiliations
    Division of Emergency Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
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  • Marie E. Heffernan
    Affiliations
    Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, United States of America

    Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
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  • Anne Bendelow
    Affiliations
    Data Analytics and Reporting, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
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  • Matthew M. Davis
    Affiliations
    Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, United States of America

    Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
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  • Michael Carroll
    Affiliations
    Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, United States of America

    Data Analytics and Reporting, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
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  • Todd A Florin
    Affiliations
    Division of Emergency Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
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  • Elizabeth R Alpern
    Affiliations
    Division of Emergency Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America
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  • Michelle L. Macy
    Affiliations
    Division of Emergency Medicine, Ann & Robert H. Lurie Children's Hospital of Chicago, Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois, United States of America

    Mary Ann & J. Milburn Smith Child Health Outcomes, Research, and Evaluation Center, Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, Illinois, United States of America
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      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 healthcare 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 1,620 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%).

      Conclusion

      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.
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