Variation in cancer surgical outcomes associated with physician and nurse staffing: a retrospective observational study using the Japanese Diagnosis Procedure Combination Database

BMC Health Serv Res. 2012 May 28:12:129. doi: 10.1186/1472-6963-12-129.

Abstract

Background: Little is known about the effects of professional staffing on cancer surgical outcomes. The present study aimed to investigate the association between cancer surgical outcomes and physician/nurse staffing in relation to hospital volume.

Methods: We analyzed 131,394 patients undergoing lung lobectomy, esophagectomy, gastrectomy, colorectal surgery, hepatectomy or pancreatectomy for cancer between July and December, 2007-2008, using the Japanese Diagnosis Procedure Combination database linked to the Survey of Medical Institutions data. Physician-to-bed ratio (PBR) and nurse-to-bed ratio (NBR) were determined for each hospital. Hospital volume was categorized into low, medium and high for each of six cancer surgeries. Failure to rescue (FTR) was defined as a proportion of inhospital deaths among those with postoperative complications. Multi-level logistic regression analysis was performed to examine the association between physician/nurse staffing and FTR, adjusting for patient characteristics and hospital volume.

Results: Overall inhospital mortality was 1.8%, postoperative complication rate was 15.2%, and FTR rate was 11.9%. After adjustment for hospital volume, FTR rate in the group with high PBR (≥19.7 physicians per 100 beds) and high NBR (≥77.0 nurses per 100 beds) was significantly lower than that in the group with low PBR (<19.7) and low NBR (<77.0) (9.2% vs. 14.5%; odds ratio, 0.76; 95% confidence interval, 0.68-0.86; p < 0.001).

Conclusions: Well-staffed hospitals confer a benefit for cancer surgical patients regarding reduced FTR, irrespective of hospital volume. These results suggest that consolidation of surgical centers linked with migration of medical professionals may improve the quality of cancer surgical management.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Comorbidity
  • Databases, Factual
  • Female
  • Hospital Bed Capacity / statistics & numerical data
  • Hospital Mortality / trends
  • Humans
  • Japan / epidemiology
  • Logistic Models
  • Male
  • Middle Aged
  • Neoplasms / surgery*
  • Outcome Assessment, Health Care*
  • Personnel Staffing and Scheduling / standards*
  • Personnel Turnover / statistics & numerical data
  • Personnel Turnover / trends
  • Postoperative Complications / epidemiology
  • Practice Patterns, Nurses' / standards
  • Practice Patterns, Nurses' / statistics & numerical data*
  • Practice Patterns, Physicians' / standards
  • Practice Patterns, Physicians' / statistics & numerical data*
  • Retrospective Studies
  • Surgical Procedures, Operative / adverse effects*
  • Surgical Wound Infection / epidemiology
  • Surgicenters*
  • Treatment Failure
  • Workforce