A systematic review of validated methods for identifying orthopedic implant removal and revision using administrative data Academic Article uri icon

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abstract

  • PURPOSE: To identify studies that have validated administrative and claims database algorithms for identifying patients with orthopedic device revision or removal. METHODS: As a part of the Food and Drug Administration's Mini-Sentinel pilot program, we performed a systematic review to identify algorithms for orthopedic implant removal/revision in administrative and claims databases in the USA or Canada. RESULTS: Five studies examined the validity of database algorithms against a gold standard of documentation in medical records (n = 3) or codes/documentation in another database (n = 2). The positive predictive values (PPV) of the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and/or the Current Procedural Terminology codes for revision total hip arthroplasty (THA) in the US Medicare population compared with medical record review were 92%and 91%, respectively. In another study of the US Medicare population, multiple ICD-9 codes for revision total knee arthroplasty were compared with newly available single ICD-9-CM codes for revision knee arthroplasty; sensitivity was 87% and specificity was 99% (PPV not provided). The fourth study validated the ICD-9-CM codes for revision total knee arthroplasty against Ontario health insurance physician fee service claims as the gold standard and found a PPV of 32%. In the last study in Medicare population, the accuracy of the attribution of revision THA to the same side as the earlier index primary THA was examined; PPV for same laterality of revision THA was 71% (using ICD-9-CM codes). CONCLUSIONS: Validation data, with regard to the ICD-9-CM or the Current Procedural Terminology code algorithms for revision THA in the Medicare population, exist. More validation studies are needed to confirm these findings and examine other large databases.

publication date

  • January 2012

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