A systematic review of validated methods for identifying transverse myelitis using administrative or claims data
| Autor: | Ryan M. Carnahan, Shanthi Krishnaswami, Melissa L McPheeters, S. Elizabeth Williams |
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| Rok vydání: | 2012 |
| Předmět: |
Pathology
medicine.medical_specialty Databases Factual Myelitis Transverse Transverse myelitis Algorithm Selection Insurance Claim Review Key terms International Classification of Diseases Claims data Controlled vocabulary medicine Humans Medical physics General Veterinary General Immunology and Microbiology business.industry Incidence Public Health Environmental and Occupational Health medicine.disease Infectious Diseases Acute Transverse Myelitis Molecular Medicine Diagnosis code Medline database business Epidemiologic Methods Algorithms |
| Zdroj: | Vaccine. 31 |
| ISSN: | 1873-2518 |
| Popis: | Purpose To identify and assess billing, procedural, or diagnostic code algorithms used to identify transverse myelitis in administrative databases. Methods We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to transverse myelitis. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. Two reviewers independently extracted data regarding participant and algorithm characteristics. Results Three studies met criteria for inclusion in this review. The only algorithm based solely on administrative claims data with a reported positive predictive value included five ICD-9 codes (codes 341.20, 341.21, 341.22, 323.8, 323.9). The positive predictive value for physician-diagnosed acute transverse myelitis was 62%. Conclusions More research is needed to establish an accurate algorithm to identify transverse myelitis in large administrative databases using diagnosis and/or procedure codes. Use of standardized consensus definitions, clear description for algorithm selection, and reporting of validation procedure and results would be most beneficial. |
| Databáze: | OpenAIRE |
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