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. © 2012 John Wiley & Sons, Ltd.
CITATION STYLE
Singh, J. A., Kundukulam, J. A., & Bhandari, M. (2012). A systematic review of validated methods for identifying orthopedic implant removal and revision using administrative data. Pharmacoepidemiology and Drug Safety, 21(SUPPL. 1), 265–273. https://doi.org/10.1002/pds.2309
Mendeley helps you to discover research relevant for your work.