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Identification and validation of vertebral compression fractures using administrative claims data
Jeffrey R Curtis1, Amy S Mudano, Daniel H Solomon
1Center for Education and Research on Therapeutics of Musculoskeletal Disorders, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA. jcurtis@uab.edu
Medical Care
|December 25, 2008
Summary
Administrative claims data can identify prevalent vertebral compression fractures (VCFs) accurately. However, simple algorithms misclassify over half of incident VCFs, requiring more complex methods for better accuracy.
Area of Science:
- Osteoporosis research
- Health informatics
- Epidemiology
Background:
- Vertebral compression fractures (VCFs) are the most common osteoporotic fracture.
- Administrative claims data is a potential source for VCF case finding, but its accuracy needs evaluation.
Purpose of the Study:
- To evaluate the accuracy of administrative claims data algorithms for identifying VCFs.
- To determine the positive predictive values (PPVs) for prevalent and incident VCFs.
Main Methods:
- Adults with VCF diagnosis codes were identified from administrative claims data (2003-2004).
- Persons with malignancy were excluded.
- PPVs of different claims algorithms were calculated for confirmed VCFs (any and incident).
Main Results:
- A simple algorithm (VCF diagnosis code) had an 87% PPV for any VCF but only 46% for incident VCFs.
- A complex algorithm (imaging/visit or hospitalization) improved PPVs to 93% for any VCF and 61% for incident VCFs.
- A total of 259 persons with suspected VCFs were identified.
Conclusions:
- Administrative claims data can accurately identify prevalent VCFs.
- Simple algorithms misclassify over half of incident VCFs.
- More complex algorithms improve accuracy but still result in some misclassification of incident VCFs.