Evaluation of a pediatric asthma high-risk scoring algorithm.

Area of Science:

• Pediatric Pulmonology
• Health Services Research
• Clinical Informatics

Background:

• Asthma is a leading cause of pediatric hospitalizations and emergency department (ED) visits.
• Identifying high-risk pediatric asthma patients is crucial for timely intervention and resource allocation.

Purpose of the Study:

• To develop and validate an asthma risk scoring algorithm for children insured by Medicaid.
• To assess the algorithm's ability to predict asthma-related hospitalizations and ED visits.

Main Methods:

• Retrospective analysis of health plan claims data from Texas Children's Health Plan.
• Algorithm development using parameters including prior asthma hospitalizations, ED visits, medication dispensing, provider numbers, and follow-up status.
• Risk score performance evaluated by predicting future asthma hospitalizations and ED visits.

Main Results:

• The asthma risk score demonstrated predictive performance, with Area Under the Curve (AUC) ranging from 0.72-0.79 for children aged 3-17 years and 0.65-0.69 for those aged 1-2 years.
• A risk score of 1 or greater identified 20-23% of pediatric asthma patients but accounted for 53-56% of subsequent asthma hospitalizations.
• 16-18% of children aged 3-17 years with a risk score of 9 or greater were hospitalized.

Conclusions:

• The developed asthma risk score effectively stratifies risk for hospitalization and ED visits in Medicaid-insured children.
• The risk score shows better predictive accuracy in older children (3-17 years) compared to younger children (1-2 years).