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

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+0.035 x age-0.02 x FVC+0.6 x extended resection+0.7 x cardiac co-morbidity (c-index=0.68). Predicted mortality: ln R/1-R=-7.6+0.08 x age-0.04 x ppoFEV1+1.6 x extended resection+1.2 x cardiac co-morbidity+1.1 x cerebrovascular co-morbidity (c-index=0.83). Predicted failure-to-rescue: ln R/1-R=-6.7+0.06 x age+1.5 x extended resection+1.2 x cerebrovascular 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.