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Pharmacoepidemiol Drug Saf. 2012 May;21 Suppl 2:53-9. doi: 10.1002/pds.3228.

Evaluation of total hip arthroplasty devices using a total joint replacement registry.

Author information

  • 1Department of Surgical Outcomes and Analysis, Kaiser Permanente, San Diego, CA 92109, USA. liz.w.paxton@kp.org

Abstract

PURPOSE:

The purpose of this paper is to describe the infrastructure of the total joint replacement registry of a large integrated healthcare system's and emphasize challenges associated with orthopedic device classification and evaluation.

METHODS:

Using a large integrated healthcare system innovative infrastructure including electronic health record data, administrative data sources, and registry data collection, we evaluated device choice and outcomes of total hip arthroplasty (THA). Devices were classified into type of bearing surface (alternative versus traditional). Multiple imputation was used to accommodate missing data, and a logistic regression model was applied to assess the impact of patient and surgeon factors on choice of bearing surface. A Cox regression model was used to evaluate risk of aseptic revision while controlling for surgeon, site, and patient characteristics. Adjusted cumulative probability-of-event curves were created, comparing survival of alternative against traditional bearings of devices, with aseptic revision as the outcome of interest.

RESULTS:

The study sample consisted of 25,377 primary THAs with an average follow-up of 2.7 years. Choice of bearing surface varied by surgeon and patient characteristics. After adjusting for patient, surgeon, and hospital covariates, results showed that the risk of aseptic revision associated with alternative bearings did not differ significantly from traditional bearing surfaces (hazard ratio = 1.33; 95% confidence interval: 0.90, 1.98).

CONCLUSIONS:

Clinically rich data from a registry with linkages to electronic health records and other administrative databases improve identification of exposures, outcomes, and patient subgroups in medical device evaluation. These various data sources facilitate refined adjustment for potential confounders such as hospital, surgeon, and patient factors and ensure comprehensive device performance evaluation within registries.

Copyright © 2012 John Wiley & Sons, Ltd.

PMID:
22552980
[PubMed - indexed for MEDLINE]
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