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

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.