An algorithm for the identification of undiagnosed COPD cases using administrative claims data
Douglas W Mapel1, Floyd J Frost, Judith S Hurley
1Lovelace Clinic Foundation, Albuquerque, New Mexico 87106-4264, USA. Doug@LCFresearch.org
Journal of Managed Care Pharmacy : JMCP
|August 24, 2006
Summary
Healthcare utilization patterns can identify undiagnosed Chronic Obstructive Pulmonary Disease (COPD). This method helps detect at-risk individuals before a formal diagnosis, improving patient outcomes and reducing healthcare burdens.
Area of Science:
- Pulmonary Medicine
- Health Services Research
- Biostatistics
Background:
- Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of mortality in the US.
- A significant number of individuals with airflow obstruction remain undiagnosed.
- Undiagnosed COPD adversely impacts patient health status and increases healthcare utilization.
Purpose of the Study:
- To determine if healthcare utilization patterns can identify patients with undiagnosed COPD.
- To develop and validate a discriminant function algorithm for this purpose.
Main Methods:
- A case-control study matching 2,129 new COPD diagnoses with up to 3 controls by age and gender.
- Analysis of healthcare utilization in the 24 months preceding COPD diagnosis using logistic regression.
- Development and validation of a discriminant function algorithm.
Main Results:
- Nineteen utilization characteristics were significantly associated with preclinical COPD.
- The algorithm identified COPD patients with 60.5% sensitivity and 82.1% specificity in a validation group (N=41,428).
- Models using 12 months of data showed similar performance.
Conclusions:
- Discriminant function algorithms using healthcare utilization data can effectively screen for undiagnosed COPD.
- These algorithms demonstrate sufficient positive predictive value for identifying at-risk individuals.
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