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Exploring potential barriers in equitable access to pediatric diagnostic imaging using machine learning.

Maryam Taheri-Shirazi1, Khashayar Namdar1,2,3,4, Kelvin Ling1

  • 1Department of Diagnostic Imaging, The Hospital for Sick Children (SickKids), Toronto, ON, Canada.

Frontiers in Public Health
|March 13, 2023
PubMed
Summary
This summary is machine-generated.

Patient demographics like age and income, along with appointment timing, significantly impact pediatric diagnostic imaging no-shows and wait times. Inequities exist for low-income and non-English speaking families.

Keywords:
appointment schedulinglogistic regressionno-showrandom forestwaiting room time

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Area of Science:

  • Medical imaging analysis
  • Healthcare access and equity

Background:

  • Pediatric diagnostic imaging appointments, including magnetic resonance imaging (MRI) and ultrasound (US), face challenges with patient no-shows and long waiting room times.
  • Understanding patient-specific and socioeconomic factors influencing these endpoints is crucial for optimizing healthcare delivery in pediatric settings.

Purpose of the Study:

  • To investigate the relationship between patient features and no-show or long waiting room time for pediatric diagnostic imaging appointments.
  • To identify key predictive factors for no-shows and extended wait times to inform operational improvements.

Main Methods:

  • Utilized univariate Logistic Regression (LR) and multivariate Random Forest (RF) models.
  • Analyzed patient features including age, sex, income, distance, non-English speaker percentage, single caregiver percentage, appointment time slot, and day of the week.
  • Validated model performance using Area Under the Receiver Operating Characteristic Curve (AUC).

Main Results:

  • Achieved AUC of 0.82 for predicting no-shows and 0.73 for long waiting room times.
  • Identified age, time slot, and percentage of single caregivers as critical predictors for no-shows.
  • Found age, distance, and percentage of non-English speakers to be most important for predicting long waiting room times.
  • Uncovered significant impact of appointment timing and patient demographics (income, caregivers) on outcomes.

Conclusions:

  • Patient demographics and appointment scheduling significantly influence pediatric diagnostic imaging no-shows and waiting room durations.
  • While no sex-based discrimination was found, inequities related to low income and language barriers persist.
  • Findings highlight the need for targeted interventions to address disparities and improve operational efficiency in pediatric diagnostic imaging.