Dataset Information

Risk-adjusted cUSUM control charts for shared frailty survival models with application to hip replacement outcomes: a study using the NJR dataset.

ABSTRACT: BACKGROUND:Continuous 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. METHODS:Our 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). RESULTS:We 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. CONCLUSIONS:An 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.

SUBMITTER: Begun A

PROVIDER: S-EPMC6882343 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Risk-adjusted cUSUM control charts for shared frailty survival models with application to hip replacement outcomes: a study using the NJR dataset.

Begun Alexander A Kulinskaya Elena E MacGregor Alexander J AJ

BMC medical research methodology 20191127 1

<h4>Background</h4>Continuous 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.<h4>Methods</h4>Our method entails the use of the competing risks model with the Weibull and the Gompertz hazard functions adjusted for observed covar ...[more]

PMID: 31775636

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Project description:ObjectivesTo determine whether an innovative graphical tool for accurate measurement of individual surgeon performance metrics, adjusted for both surgeon-specific and patient-specific factors, significantly alters interpretation of performance data.DesignRetrospective analysis of all total knee replacements (TKRs) conducted at the host institution between 1996 and 2009. The database was randomly divided into training and testing datasets. Using multivariate generalised estimating equation regression models, the training dataset enabled generation of patient-risk and surgeon-experience adjustment factors. To simulate prospective monitoring of individual surgeon outcomes, the testing dataset was mapped on control charts. Weighted ? statistics were calculated to measure the agreement between patient-risk adjusted and fully adjusted control charts.SettingTertiary care academic hospital.ParticipantsAll patients undergoing TKR at the host institution 1996-2009.Main outcome measureOperative efficiency.Results5313 procedures were analysed. Adjusted control charts were generated using a training dataset comprising 3756 procedures performed by 13 surgeons. The operative time gradually declined by 121 min with 25 years of experience (p<0.0001). Charts were tested by monitoring four other surgeons, performing an average of 389 procedures each. Adjustment for surgeon experience significantly altered the interpretation of operative efficiency (?=0.29 (95% CI 0.11 to 0.47)), and enhanced assessment of a surgeon's improvement or diminishment in efficiency over time. Specifically, experience adjustment inverted the interpretation of surgeon efficiency from above average to below average, or from improving to declining performance.ConclusionsAdjustment for surgeon experience is necessary for accurate interpretation of metrics over the course of a surgeon's career. Patient-adjusted and surgeon-adjusted control charts provide an accurate method of monitoring individual operative efficiency.

Dataset Information

Risk-adjusted cUSUM control charts for shared frailty survival models with application to hip replacement outcomes: a study using the NJR dataset.

Publications

Risk-adjusted cUSUM control charts for shared frailty survival models with application to hip replacement outcomes: a study using the NJR dataset.

Similar Datasets

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