Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care.
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 eme...
| Published in: | Academic Pediatrics Vol. 23; no. 1; pp. 140 - 148 |
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| Main Authors: | , , , , , , , |
| Format: | research tables/charts Journal Article |
| Published: |
Elsevier B.V.
Jan/Feb2023
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=174989708&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 174989708 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 18762859 8NBK jtl: Academic Pediatrics issn: 18762859 maglogo: N pubinfo: dt: Jan/Feb2023 vid: 23 iid: 1 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 174989708 174989708 174989708 10.1016/j.acap.2022.05.006 174989708 ppf: 140 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Parental Perceptions on Use of Artificial Intelligence in Pediatric Acute Care. aug: au: Ramgopal, Sriram Heffernan, Marie E. Bendelow, Anne Davis, Matthew M. Carroll, Michael S. Florin, Todd A. Alpern, Elizabeth R. Macy, Michelle L. affil: Division of Emergency Medicine, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Ill sug: subj: Respiration Disorders Acute Care Pediatric Care Health Care Delivery Artificial Intelligence Utilization Parental Attitudes Evaluation Consumer Satisfaction Evaluation Comfort Human Male Female Adolescence Adult Middle Age Illinois Questionnaires Infant, Newborn Infant Child, Preschool Child Logistic Regression Surveys Software Antibiotics Hematologic Tests Radiography, Computed Multivariate Analysis Race Factors Odds Ratio Descriptive Statistics Confidence Intervals Diagnostic Errors Treatment Errors Emergency Service Age Factors Decision Support Systems, Clinical Pediatrics Stakeholder Participation Adolescent: 13-18 years Adult: 19-44 years Middle Aged: 45-64 years Infant, Newborn: birth-1 month Infant: 1-23 months Child, Preschool: 2-5 years Child: 6-12 years Male Female ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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