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Risk-adjusted morbidity, mortality and failure-to-rescue models for internal provider profiling after major lung resection

Unit of Thoracic Surgery, ‘Umberto I°’ Regional Hospital, Via S. Margherita 23, Ancona, 60129 Italy

*Corresponding author. Tel.: +39 071 5964439; fax: +39 071 5964433.

E-mail address: alexit2000{at}yahoo.com (A. Brunelli).

This work was aimed at developing risk-adjusted outcome models for profiling the internal quality of care after major lung resection. One thousand and sixty-two patients submitted to lobectomy (845) or pneumonectomy (217) from 1994 through 2004 at our unit were analyzed. Risk-adjusted models of 30-day or in-hospital morbidity, mortality and failure-to-rescue (death/complication ratio) were developed by stepwise logistic regression analyses and validated by bootstrap procedures. The regression equations were then used to estimate the outcome risks in 3 successive periods of activity (early: 1994–1997; intermediate: 1998–June/2001; late: July/2001–2004). Observed and predicted morbidity, mortality and failure-to-rescue rates were compared within each period by the z-test. The following regression models were developed: Predicted morbidity: ln R/1–R=–2.1+0.035xage–0.02xFVC+0.6xextended resection+0.7xcardiac co-morbidity (c-index=0.68). Predicted mortality: ln R/1–R=–7.6+0.08xage–0.04xppoFEV1+1.6xextended resection+1.2xcardiac co-morbidity+1.1xcerebrovascular co-morbidity (c-index=0.83). Predicted failure-to-rescue: ln R/1–R=–6.7+0.06xage+1.5xextended resection+1.2xcerebrovascular co-morbidity (c-index=0.71). No differences were noted between observed and predicted outcome rates within each period, despite apparent unadjusted differences between periods. The use of risk-adjusted outcome models prevented misleading information derived from the unadjusted analysis of performance. We are currently using these models for internal quality-of-care audit purposes.

Key Words: Lung cancer surgery; Outcomes; Morbidity; Mortality; Risk modelling; Quality of care

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