Preferences for Management of Pediatric Pneumonia: A Clinician Survey of Artificially Generated Patient Cases

Sriram Ramgopal*, Thomas Belanger, Douglas Lorenz, Susan C. Lipsett, Mark I. Neuman, David Liebovitz, Todd A. Florin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background It is unknown which factors are associated with chest radiograph (CXR) and antibiotic use for suspected community-acquired pneumonia (CAP) in children. We evaluated factors associated with CXR and antibiotic preferences among clinicians for children with suspected CAP using case scenarios generated through artificial intelligence (AI). Methods We performed a survey of general pediatric, pediatric emergency medicine, and emergency medicine attending physicians employed by a private physician contractor. Respondents were given 5 unique, AI-generated case scenarios. We used generalized estimating equations to identify factors associated with CXR and antibiotic use. We evaluated the cluster-weighted correlation between clinician suspicion and clinical prediction model risk estimates for CAP using 2 predictive models. Results A total of 172 respondents provided responses to 839 scenarios. Factors associated with CXR acquisition (OR, [95% CI]) included presence of crackles (4.17 [2.19, 7.95]), prior pneumonia (2.38 [1.32, 4.20]), chest pain (1.90 [1.18, 3.05]) and fever (1.82 [1.32, 2.52]). The decision to use antibiotics before knowledge of CXR results included past hospitalization for pneumonia (4.24 [1.88, 9.57]), focal decreased breath sounds (3.86 [1.98, 7.52]), and crackles (3.45 [2.15, 5.53]). After revealing CXR results to clinicians, these results were the sole predictor associated with antibiotic decision-making. Suspicion for CAP correlated with one of 2 prediction models for CAP (Spearman's rho = 0.25). Factors associated with a greater suspicion of pneumonia included prior pneumonia, duration of illness, worsening course of illness, shortness of breath, vomiting, decreased oral intake or urinary output, respiratory distress, head nodding, focal decreased breath sounds, focal rhonchi, fever, and crackles, and lower pulse oximetry. Conclusions Ordering preferences for CXRs demonstrated similarities and differences with evidence-based risk models for CAP. Clinicians relied heavily on CXR findings to guide antibiotic ordering. These findings can be used within decision support systems to promote evidence-based management practices for pediatric CAP.

Original languageEnglish (US)
Pages (from-to)41-49
Number of pages9
JournalPediatric emergency care
Volume41
Issue number1
DOIs
StatePublished - Jan 1 2025

Keywords

  • CAP
  • decision support
  • pneumonia
  • procedurally generated
  • synthetic data

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Emergency Medicine

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