Expediting Autism Spectrum Disorder Diagnoses Through Education, Training, and EMR-integration of the Childhood Autism Rating Scale (CARS-2) Diagnostic Tool
Mikael Guzman Karlsson1, Douglas Wells1, Christina Massrey2, Meagan Newell1, Steven Lazar1, Hasham Dhakwala2, Ramtin Kohandel2, Sreya Rahman2, Morgan Motakef2, Ameya Walimbe1, Abhijit Das1, Melissa Mizerik1, Rima El Atrache2, Paisley Pauli1, Jesse Levine1, Jaime Solis1, Lin Yao1, Lisa Emrick1, Sarah Risen1, Kristen Fisher1, Shannon DiCarlo1
1Baylor College of Medicine/Texas Children's Hospital, 2Baylor College of Medicine
Objective:
To increase formal autism spectrum disorder (ASD) diagnoses within a pediatric neurology division in a large southern academic medical center.
Background:
Early initiation of Applied Behavioral Analysis (ABA) therapy for children with ASD can improve outcomes. However, in the United States, the average age for ASD diagnosis is between 3.8-4.4 years. The American Academy of Pediatrics (AAP) recommends ASD-specific screening at 18 and 24 months. A positive screen should prompt a referral to a specialist for comprehensive evaluation and diagnosis. However, most insurance companies do not cover ABA therapy without a formal diagnosis. This, coupled with limited access to diagnostic tools and lack of confidence in post-diagnosis management, can result in unnecessary subspecialty referrals, further delaying diagnosis and treatment.
Design/Methods:
Using semi-structured interviews and surveys, we performed a needs assessment to evaluate local pediatric neurologists’ experiences with, and barriers to, making, disclosing, and counseling on formal ASD diagnoses; recommending therapeutic interventions; and providing secondary diagnostic referrals. We further designed and implemented a multi-modal educational curriculum that reviewed ASD diagnostic criteria, readily available diagnostic tools, billing for developmental testing, post-diagnosis counseling, and therapy referral procedures. Finally, applying informatics, design, and implementation research principles, we integrated the Childhood Autism Rating Scale-2 (CARS-2) into our electronic medical record (EMR) and optimized provider workflow to facilitate necessary documentation to improve overall diagnostic efficiency.
Results:
Primary outcomes examined the extent of CARS-2 utilization, frequency of ASD diagnosis, and changes in secondary referral patterns to other subspecialty providers.
Conclusions:
Our quality improvement work provides a framework to empower providers with the necessary knowledge and skills to formally diagnose, counsel, and manage patients with a clear ASD diagnosis. Education, training, and EMR integration of the CARS-2 diagnostic tool can narrow the quality care gap by making ASD diagnosis and management more timely, efficient, equitable, and patient-centered.