title: Variability of NSQIP-assessed surgical quality based on age and disease process.
abstract: BACKGROUND
  Recent national attention has focused on improving upon the surgical quality of hospitals across the United States. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database includes expected morbidity probability for each surgical patient. We sought to investigate the accuracy of this probability across the spectrum of general surgical operations and assess the variability based on the age and disease process.
  
  
  METHODS
  Using the 2008 ACS-NSQIP database, we identified 190,929 operations that would be in the scope of practice of a modern general surgeon; the four most common included breast resection (n = 22,175; 11.6%), colon resection (n = 21,363; 11.2%), cholecystectomy (n = 20,889; 10.9%), and inguinal hernia repair (n = 11,709; 6.1%). We calculated the surgical observed versus expected morbidity rates (O/E) of each operation type and compared them by decile of patient age. We then determined the effect of case mix and patient age on theoretical hospitals performing at the NSQIP average.
  
  
  RESULTS
  There is substantial variability in O/E ratios when comparing these disease processes across deciles of age. For patients undergoing breast resections, 67.2% of morbidities were solely attributed to 30-d reoperations; colon resections had an O/E ratio greater than 1 for all age deciles except over 90 y old. For cholecystectomies and the majority of patients undergoing inguinal hernia repairs, there was a lower morbidity rate than expected. Case mix and patient age were found to independently affect assessment of hospital quality.
  
  
  CONCLUSIONS
  It is conceivable that general surgery case mix and patient age could independently affect the quality assessment of a hospital. This variability may have implications for overall quality measures.
authors.affiliation: Department of Surgery, Mayo Clinic - Florida, Jacksonville, Florida, USA.
authors.forename: Ross F
authors.initials: RF
authors.lastname: Goldberg
authors.forename: Armando
authors.initials: A
authors.lastname: Rosales-Velderrain
authors.forename: Tatyan M
authors.initials: TM
authors.lastname: Clarke
authors.forename: Mauricia A
authors.initials: MA
authors.lastname: Buchanan
authors.forename: John A
authors.initials: JA
authors.lastname: Stauffer
authors.forename: Sarah A
authors.initials: SA
authors.lastname: McLaughlin
authors.forename: Horacio J
authors.initials: HJ
authors.lastname: Asbun
authors.forename: C Daniel
authors.initials: CD
authors.lastname: Smith
authors.forename: Steven P
authors.initials: SP
authors.lastname: Bowers
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D016208:Databases, Factual; D003953:Diagnosis-Related Groups; D005260:Female; D013502:General Surgery / Q000592:standards*; D006801:Humans; D008297:Male; D008875:Middle Aged; D011785:Quality Assurance, Health Care