Surgeon Annual and Cumulative Volumes Predict Early Postoperative Outcomes after Rectal Cancer Resection

Ann Surg. 2017 Jan;265(1):151-157. doi: 10.1097/SLA.0000000000001672.

Abstract

Objective: To determine if 5-year surgeon cumulative and annual volumes predict improved early postoperative outcomes in patients with rectal cancer.

Background: Operative experience has been shown to effect surgical outcomes. The differential role of cumulative versus annual volume has not yet been explored for rectal surgery.

Methods: The Statewide Planning and Research Cooperative System database was used to capture patients undergoing surgery in New York State from 2000 to 2013. A population-based sample of patients undergoing major rectal or rectosigmoid resection as their principal procedure during hospitalization between 2000 and 2013 were identified using International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes. Surgeons were identified using a unique physician number from 1995 to 2013.

Results: The percentage of surgeries performed by high cumulative/high annual (HC/HA) surgeons increased from 38.3% to 58.4% (P < 0.01) with a simultaneous decrease in that performed by low cumulative/low annual (LC/LA) surgeons (52.5% to 29.8%, P < 0.01). HC/HA volume surgeons had a significantly lower rate of surgical complications (odd ratio = 0.71, 95% confidence interval = 0.60-0.83, P < 0.05) as compared with LC/LA volume surgeons. There was no significant difference in rates of anastomotic leak, nonroutine discharges or readmission among all four groups.

Conclusions: The best early postoperative surgical outcomes are achieved in centers where there are high cumulative and high annual volume surgeons caring for these patients. This suggests the need for specialized designation of rectal cancer centers to support ongoing regionalization of care.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Clinical Competence*
  • Databases, Factual
  • Female
  • Hospitals, High-Volume*
  • Humans
  • Linear Models
  • Male
  • Middle Aged
  • New York
  • Outcome Assessment, Health Care
  • Patient Readmission / statistics & numerical data
  • Postoperative Complications / epidemiology
  • Postoperative Complications / etiology*
  • Rectal Neoplasms / surgery*
  • Surgeons / statistics & numerical data*