BACKGROUND: Studies have demonstrated volume-outcome relationships for numerous operations, providing an impetus for regionalization; however, volume-based regionalization may not be feasible or necessary. Our objective was to determine if low-risk patients undergoing surgery at Community Hospitals have perioperative mortality rates comparable with Specialized Centers. METHODS: From the National Cancer Data Base, 940,718 patients from approximately 1430 hospitals were identified who underwent resection for 1 of 15 cancers (2003-2005). Patients were stratified by preoperative risk according to age and comorbidities. Separately for each cancer, regression modeling stratified by high- and low-risk groups was used to compare 60-day mortality at Specialized Centers (National Cancer Institute-designated and/or highest-volume quintile institutions), Other Academic Institutions (lower-volume, non-National Cancer Institute), and Community Hospitals. RESULTS: Low-risk patients had statistically similar perioperative mortality rates at Specialized Centers and Community Hospitals for 13 of 15 operations. High-risk patients had significantly lower perioperative mortality rates at Specialized Centers compared with Community Hospitals for 9 of 15 cancers. Regardless of risk group, perioperative mortality rates were significantly lower for pancreatectomy and esophagectomy at Specialized Centers. Risk-based referral compared with volume-based regionalization of most patients would require fewer patients to change to Specialized Centers. CONCLUSIONS: Perioperative mortality for low-risk patients was comparable at Specialized Centers and Community Hospitals for all cancers except esophageal and pancreatic, thus questioning volume-based regionalization of all patients. Rather, only high-risk patients may need to change hospitals. Mortality rates could be reduced if factors at Specialized Centers resulting in better outcomes for high-risk patients can be identified and transferred to other hospitals.
BACKGROUND: Studies have demonstrated volume-outcome relationships for numerous operations, providing an impetus for regionalization; however, volume-based regionalization may not be feasible or necessary. Our objective was to determine if low-risk patients undergoing surgery at Community Hospitals have perioperative mortality rates comparable with Specialized Centers. METHODS: From the National Cancer Data Base, 940,718 patients from approximately 1430 hospitals were identified who underwent resection for 1 of 15 cancers (2003-2005). Patients were stratified by preoperative risk according to age and comorbidities. Separately for each cancer, regression modeling stratified by high- and low-risk groups was used to compare 60-day mortality at Specialized Centers (National Cancer Institute-designated and/or highest-volume quintile institutions), Other Academic Institutions (lower-volume, non-National Cancer Institute), and Community Hospitals. RESULTS: Low-risk patients had statistically similar perioperative mortality rates at Specialized Centers and Community Hospitals for 13 of 15 operations. High-risk patients had significantly lower perioperative mortality rates at Specialized Centers compared with Community Hospitals for 9 of 15 cancers. Regardless of risk group, perioperative mortality rates were significantly lower for pancreatectomy and esophagectomy at Specialized Centers. Risk-based referral compared with volume-based regionalization of most patients would require fewer patients to change to Specialized Centers. CONCLUSIONS: Perioperative mortality for low-risk patients was comparable at Specialized Centers and Community Hospitals for all cancers except esophageal and pancreatic, thus questioning volume-based regionalization of all patients. Rather, only high-risk patients may need to change hospitals. Mortality rates could be reduced if factors at Specialized Centers resulting in better outcomes for high-risk patients can be identified and transferred to other hospitals.
Authors: Gregory T Kennedy; Benjamin D Ukert; Jarrod D Predina; Andrew D Newton; John C Kucharczuk; Daniel Polsky; Sunil Singhal Journal: J Gastrointest Surg Date: 2018-07-31 Impact factor: 3.452
Authors: Anthony T Corcoran; Elizabeth Handorf; Daniel Canter; Jeffrey J Tomaszewski; Justin E Bekelman; Simon P Kim; Robert G Uzzo; Alexander Kutikov; Marc C Smaldone Journal: BJU Int Date: 2014-07-14 Impact factor: 5.588
Authors: Elizabeth R Berger; Karl Y Bilimoria; Christine V Kinnier; Christina A Minami; Kevin P Bethke; Nora M Hansen; Ryan P Merkow; David P Winchester; Anthony D Yang Journal: J Surg Oncol Date: 2018-11-27 Impact factor: 3.454
Authors: Mary E Charlton; Jennifer E Hrabe; Kara B Wright; Jennifer A Schlichting; Bradley D McDowell; Thorvardur R Halfdanarson; Chi Lin; Karyn B Stitzenberg; John W Cromwell Journal: J Gastrointest Surg Date: 2015-12-09 Impact factor: 3.452
Authors: Ryan P Merkow; Karl Y Bilimoria; Karen L Sherman; Martin D McCarter; Howard S Gordon; David J Bentrem Journal: J Oncol Pract Date: 2013-02-26 Impact factor: 3.840
Authors: Mary E Charlton; Ariana F Shahnazi; Irena Gribovskaja-Rupp; Lisa Hunter; Michele A Mengeling; Elizabeth A Chrischilles; Charles F Lynch; Marcia M Ward Journal: J Gastrointest Surg Date: 2018-09-10 Impact factor: 3.452