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A comparison of administrative claims-based risk predictors for pediatric asthma
Annie Lintzenich Andrews1, Daniel L Brinton, Annie N Simpson
1Medical University of South Carolina, 135 Rutledge Ave, MSC 561, Charleston, SC 29425.
Insights
Pharmacy claims data, like asthma medication ratio (AMR) and short-acting beta-agonist (SABA) counts, effectively identify children with asthma unlikely to experience exacerbations. These predictors offer high specificity and negative predictive value for risk monitoring.
Area of Science:
- Pediatric Pulmonology
- Health Services Research
- Data Science in Healthcare
Background:
- Accurate prediction of asthma exacerbations in children is crucial for timely intervention.
- Administrative claims data offer a scalable method for identifying high-risk pediatric asthma patients.
- Existing risk prediction models require validation for emergency department (ED) visits and hospitalizations.
Purpose of the Study:
- To compare the accuracy of seven administrative claims-based risk predictors for forecasting asthma-related ED visits and hospitalizations in children.
- To determine the most effective predictor for identifying pediatric asthma patients at high risk of exacerbation.
Main Methods:
- A retrospective cohort study analyzed MarketScan Medicaid data from 2013-2014.
- Included were 214,452 children aged 2-17 years with asthma.
- Seven predictors were evaluated: asthma medication ratio (AMR), HEDIS criteria, revised HEDIS, quarterly short-acting beta-agonist (SABA) claims, prior ED visit, prior hospitalization, and prior ED visit or hospitalization. Performance metrics included sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).
Main Results:
- HEDIS and revised HEDIS criteria identified excessively large high-risk cohorts (67% and 48%).
- Pharmacy claims-based measures (AMR and SABA count) demonstrated high negative predictive value (97%-99%), effectively ruling out low-risk patients.
- Prior ED visit or hospitalization showed superior sensitivity (49%) compared to pharmacy measures (5%-10%) for identifying high-risk patients.
Conclusions:
- Pharmacy claims-based predictors, specifically AMR and SABA counts, excel at identifying low-risk pediatric asthma patients due to high specificity and NPV.
- These measures are valuable for real-time risk monitoring in pediatric asthma management.
- While prior events offer higher sensitivity, pharmacy claims provide a more focused approach for intervention targeting.
Objectives:
Head-to-head comparisons are needed to determine the most accurate and appropriate administrative claims-based exacerbation risk predictor for emergency department (ED) visits and hospitalizations among children with asthma.
Study Design:
Retrospective cohort study.
Methods:
We analyzed 2013-2014 MarketScan Medicaid data. Children aged 2 to 17 years were included. Seven risk predictors were compared for accuracy in predicting 3-month subsequent ED visits/hospitalizations for asthma: 3-month rolling asthma medication ratio (AMR), Healthcare Effectiveness Data and Information Set (HEDIS) criteria, revised HEDIS criteria, quarterly short-acting β-agonist (SABA) claims, prior ED visit, prior hospitalization, and prior ED visit or hospitalization. Sensitivity, specificity, positive and negative predictive value (NPV), and percentage of population identified as high risk were compared for each risk predictor utilizing the McNemar test to identify statistically significant differences in risk prediction accuracy.
Results:
A total of 214,452 children were included; the mean age was 7.8 years. HEDIS and revised HEDIS identified prohibitively large cohorts as high risk (67% and 48%, respectively). For the remaining measures, the NPV range is narrow (97%-99%), indicating high performance at identifying patients who would not benefit from intervention. The ED visit and ED/hospitalization measures have superior sensitivities (44% and 49%, respectively) compared with pharmacy claims-based measures (AMR [5%] and SABA count [10%]). Pharmacy claims-based measures identify a smaller proportion of patients as high risk and maintain high NPV.
Conclusions:
Pharmacy-based asthma exacerbation risk predictors such as the AMR and SABA count can rule out low-risk patients with a high degree of specificity and NPV, which is a primary goal of real-time risk monitoring in pediatric asthma.
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