Conventional models overestimate the statistical significance of volume-outcome associations, compared with multilevel models.
OBJECTIVE
To compare the use of conventional statistical models with multilevel regression models in volume-outcome analyses of surgical procedures in an empirical case study.


METHODS
Using conventional regression models and multilevel regression models, we estimated the effect of hospital volume and surgeon volume on 30-day mortality and length of postoperative hospital stay in persons who had an esophagectomy, pancreaticoduodenectomy, or major lung resection for cancer in Ontario, Canada, from 1994 to 1999.


RESULTS
The point estimates of volume-outcome associations were similar using either method; however, the 95% confidence intervals estimated by multilevel models were wider than those estimated by conventional models. A significant association between volume and mortality was identified in 2 of 18 (11%) comparisons using conventional analysis but in none of the 18 (0%) comparisons using multilevel analysis, and between volume and length of stay in 15 of 18 (83%) comparisons using conventional analysis and in 1 of 18 (6%) comparisons using multilevel analysis.


CONCLUSIONS
Conventional and multilevel statistical models can yield substantially different results in the analysis of volume-outcome associations for surgical procedures.
Urbach
David R
DR
Institute for Clinical Evaluative Sciences, University of Toronto, G Wing Room 140, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada. david.urbach@ices.on.ca
Austin
Peter C
PC
D000367:Age Factors; D016629:Esophagectomy / Q000401:mortality*; D005260:Female; D006801:Humans; D007902:Length of Stay; D008175:Lung Neoplasms / Q000401:mortality / Q000601:surgery; D008297:Male; D015233:Models, Statistical; D016577:Pancreaticoduodenectomy / Q000401:mortality*; D011013:Pneumonectomy / Q000401:mortality*; D012044:Regression Analysis; D012737:Sex Factors; D016896:Treatment Outcome; D016526:Workload