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Improving Access to Diagnostic Evaluations for Developmental Disabilities Through an Initial Assessment Model.

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A new initial assessment (IA) model significantly reduced waitlists for autism spectrum disorder and developmental delay evaluations in school-age children. This approach optimized care access by identifying children who did not need further specialized assessment.

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Area of Science:

  • Pediatric healthcare delivery
  • Neurodevelopmental diagnostics
  • Healthcare management

Background:

  • Access to timely diagnostic evaluations for autism spectrum disorder (ASD) and developmental delays is crucial for school-age children.
  • Traditional waitlist (WL) models can lead to significant delays in accessing necessary assessments.
  • Optimizing clinical resources is essential for improving patient care pathways.

Purpose of the Study:

  • To evaluate a novel initial assessment (IA) care model designed to enhance access to diagnostic evaluations for school-age children.
  • To determine the impact of the IA model on waitlist volumes for neurodevelopmental assessments.
  • To assess the efficiency of the IA model in identifying children suitable for immediate discharge from the waitlist.

Main Methods:

  • Implementation of an "initial assessment" (IA) model for children aged 7-9 years at a regional pediatric hospital.
  • Utilized electronic health records (EHR) to track IA volume and referral patterns.
  • Cross-referenced EHR referral data with clinician surveys to validate findings.

Main Results:

  • A strong negative association was observed between IA volume and school-age waitlist (WL) volume (r(22) = -0.92, p < 0.001).
  • Increased IA volume correlated with a significant decline in WL volume.
  • Approximately one-third of children evaluated via IA did not require further neurodevelopmental assessment and could be removed from the WL.

Conclusions:

  • The novel IA model demonstrated a strong association with reduced waitlist volumes for neurodevelopmental evaluations in school-age children.
  • Findings support the IA model as a "right-fit" approach to optimize clinical resources.
  • Implementation of the IA model improves access to timely and appropriate neurodevelopmental evaluations.