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Pharmaceutically-based severity stratification of an asthmatic population
F T Leone1, J R Grana, P McDermott
1U.S. Quality Algorithms, Inc., Blue Bell, PA, USA.
Respiratory Medicine
|December 22, 1999
Summary
This study developed an efficient algorithm to identify asthma severity in Health Maintenance Organization (HMO) members using billing codes. The validated method accurately predicts healthcare resource utilization, aiding targeted interventions for asthmatics.
Area of Science:
- Health Services Research
- Medical Informatics
- Public Health
Background:
- Accurate disease severity identification is crucial for targeted interventions in managed care populations.
- Existing health risk screening instruments often rely on surveys and have limitations.
- Developing efficient algorithms for disease prediction is a significant area of medical research.
Purpose of the Study:
- To present a valid and efficient method for predicting healthcare resource utilization among asthmatics within a Health Maintenance Organization (HMO) population.
- To establish a reliable algorithm for identifying and stratifying asthma severity.
- To validate the severity stratification by correlating it with actual healthcare resource utilization.
Main Methods:
- Utilized diagnosis, procedure, and pharmacy billing codes to identify asthmatics within an HMO database.
- Developed a screening algorithm that assigns points for specific billing codes to identify asthmatic patients.
- Stratified identified asthmatics into severity levels based on pharmacy data and validated this stratification using asthma-related bed days.
Main Results:
- The identification algorithm estimated an asthma prevalence of 3.84% in the studied population, with age-specific prevalence aligning with published data.
- A clear monotonic relationship was observed between pharmacy-based asthma severity levels and inpatient resource utilization.
- Asthmatics in higher severity levels (2-5) demonstrated significantly increased hospital days compared to level 1.
Conclusions:
- The developed algorithm provides a valid and efficient method for identifying asthma severity and predicting healthcare resource utilization in HMO populations.
- This model's findings can be used independently or as adjusters in other predictive models for patient severity.
- The study highlights the utility of administrative and pharmacy data for disease severity assessment and resource utilization prediction.
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