Benchmarking quality for renal cancer surgery: Canadian Kidney Cancer information system (CKCis) perspective

Keith A. Lawson, Olli Saarela, Zhihui Liu, Luke T. Lavallée, Rodney H. Breau, Lori Wood, Michael A.S. Jewett, Anil Kapoor, Simon Tanguay, Ronald B. Moore, Ricardo Rendon, Frederic Pouliot, Peter C. Black, Jun Kawakami, Darrel Drachenberg, Antonio Finelli

Abstract


Introduction: There is a lack of validated quality metrics to evaluate the care of patients receiving surgery for renal cell carcinoma (RCC). To address this, the Kidney Cancer Research Network of Canada defined a list of quality indicators (QI) to assess hospital-level performance. We have case-mix adjusted these QIs to benchmark RCC surgical care at Canadian academic centres.

Methods: The Canadian Kidney Cancer information system (CKCis) was used to measure six QIs: laparoscopic approach proportion (LA), partial nephrectomy proportion (PN), partial nephrectomy in patients with chronic kidney disease (CKDPN), positive margin rate (PMR), partial nephrectomy complication rate (PNCx), and warm ischemia time (WIT). To benchmark performance, indirect
standardization (observed-to-expected ratio) methodology was employed using multivariate regression models.

Results: Multivariate models for LA, PN, and CKDPN demonstrate good discrimination and were used for benchmarking. National averages of 74% (70‒78%), 73% (70‒75%), and 70% (67‒74%) for the LA, PN, and CKDPN QIs, respectively, were determined and used to benchmark individual hospital performance. Overall, three (23%), two (15%), and two (15%) hospitals performed below expected for LA, PN, and CKDPN, respectively. Hospital identity was an independent predictor of LA, PN, and CKDPN (p<0.001).

Conclusions: Significant variability between CKCis hospitals for three RCC surgical QIs exists. Using the CKCis infrastructure may provide a framework for institution-level audit feedback for quality improvement. Greater CKCis capture rates and further data supporting the construct validity of these QIs are required to extend the use of this dataset to real-world quality initiatives.


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DOI: http://dx.doi.org/10.5489/cuaj.4397

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