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Risk-adjusted monitoring of surgical performance

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Listed:
  • Jianbo Li
  • Jiancheng Jiang
  • Xuejun Jiang
  • Lin Liu

Abstract

We propose a nonparametric risk-adjusted cumulative sum chart to monitor surgical outcomes for patients with different risks of post-operative mortality due to risk factors that exist before the surgery. Using varying-coefficient logistic regression models, we accomplish the risk adjustment. Unknown coefficient functions are estimated by global polynomial spline approximation based on the maximum likelihood principle. We suggest a bisection minimization approach and a bootstrap method to determine the chart testing limit value. Compared with the previous (parametric) risk-adjusted cumulative sum chart, a major advantage of our method is that the morality rate can be modeled more flexibly by related covariates, which significantly enhances the monitoring efficiency. Simulations demonstrate nice performance of our proposed procedure. An application to a UK cardiac surgery dataset illustrates the use of our methodology.

Suggested Citation

  • Jianbo Li & Jiancheng Jiang & Xuejun Jiang & Lin Liu, 2018. "Risk-adjusted monitoring of surgical performance," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-13, August.
    • Handle: RePEc:plo:pone00:0200915
    DOI: 10.1371/journal.pone.0200915
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    References listed on IDEAS

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    1. O. Grigg & V. Farewell, 2004. "An overview of risk‐adjusted charts," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 523-539, August.
    2. Li Zeng, 2016. "Risk-Adjusted Performance Monitoring in Healthcare Quality Control," Springer Series in Reliability Engineering, in: Hoang Pham (ed.), Quality and Reliability Management and Its Applications, pages 27-45, Springer.
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