Abstract

BackgroundContinuous monitoring of surgical outcomes after joint replacement is needed to detect which brands’ components have a higher than expected failure rate and are therefore no longer recommended to be used in surgical practice. We developed a monitoring method based on cumulative sum (CUSUM) chart specifically for this application.MethodsOur method entails the use of the competing risks model with the Weibull and the Gompertz hazard functions adjusted for observed covariates to approximate the baseline time-to-revision and time-to-death distributions, respectively. The correlated shared frailty terms for competing risks, corresponding to the operating unit, are also included in the model. A bootstrap-based boundary adjustment is then required for risk-adjusted CUSUM charts to guarantee a given probability of the false alarm rates. We propose a method to evaluate the CUSUM scores and the adjusted boundary for a survival model with the shared frailty terms. We also introduce a unit performance quality score based on the posterior frailty distribution. This method is illustrated using the 2003-2012 hip replacement data from the UK National Joint Registry (NJR).ResultsWe found that the best model included the shared frailty for revision but not for death. This means that the competing risks of revision and death are independent in NJR data. Our method was superior to the standard NJR methodology. For one of the two monitored components, it produced alarms four years before the increased failure rate came to the attention of the UK regulatory authorities. The hazard ratios of revision across the units varied from 0.38 to 2.28.ConclusionsAn earlier detection of failure signal by our method in comparison to the standard method used by the NJR may be explained by proper risk-adjustment and the ability to accommodate time-dependent hazards. The continuous monitoring of hip replacement outcomes should include risk adjustment at both the individual and unit level.

Highlights

  • Continuous monitoring of surgical outcomes after joint replacement is needed to detect which brands’ components have a higher than expected failure rate and are no longer recommended to be used in surgical practice

  • A number of cumulative sum (CUSUM)-based quality control systems are being implemented in various clinical disciplines, with the earliest application being in cardiothoracic surgery [2]

  • For the control dataset described in the “Methods” section, we estimated unknown parameters of the competing risks model with and without shared frailty terms maximizing the likelihood function (2)

Read more

Summary

Introduction

Continuous monitoring of surgical outcomes after joint replacement is needed to detect which brands’ components have a higher than expected failure rate and are no longer recommended to be used in surgical practice. We developed a monitoring method based on cumulative sum (CUSUM) chart for this application. One of the most popular methods is the cumulative sum (CUSUM) chart, a graphical method based on sequential monitoring of cumulative performance over time. A number of CUSUM-based quality control systems are being implemented in various clinical disciplines, with the earliest application being in cardiothoracic surgery [2]. They are used in surveillance of the healthcare quality by QCC [3], and by Dr Foster unit at Imperial College [4]. In this paper we expand the CUSUM methodology and adapt it for monitoring the performance of hip prostheses using the NJR data

Methods
Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call