Literature DB >> 21509426

Prolonged duration of operation: an indicator of complicated surgery or of surgical (mis)management?

P Gastmeier1, D Sohr, A Breier, M Behnke, C Geffers.   

Abstract

PURPOSE: The aim of this study was to investigate whether a prolonged operative time should be regarded as an indicator of quality problems in operating rooms or as patient-specific risk factors when analyzing surgical site infection (SSI) rates.
METHOD: Data from the SSI component of the German national nosocomial infection surveillance system (KISS) were used to address this question. Eight procedure categories tracked by at least 30 departments participating in KISS were included in the analysis, namely, hip (2 types) and knee prosthesis, breast surgery, hernia repair, C-section, cholecystectomy and colon operations. Various multiple logistic regression analyses were performed for each procedure category to predict duration of operation. Patient factors (sex, age, American Society of Anesthesiologists score, wound contamination class) and hospital factors (hospital status, size, annual volume) were considered. The area under the receiver operating characteristic (ROC) curve was used to evaluate predictive power including patient- and hospital-based factors.
RESULTS: A total of 253,454 operations were included in the analysis. In general, the predictive power of the model including all variables for the different procedure types was relatively low (C-index range: 0.57-0.63) and not much higher than that of the models including only patient-based or only hospital-based variables, respectively. The predictive power for the duration of operative time based on the model including only hospital-based variables was as good as or better than that of the model including only patient-based factors.
CONCLUSION: Duration of operation is at least partially determined by hospital factors and, consequently, should be used as a quality indicator to compare SSI infections between hospitals, rather than being used as a patient factor to adjust comparisons between hospitals.

Entities:  

Mesh:

Year:  2011        PMID: 21509426     DOI: 10.1007/s15010-011-0112-x

Source DB:  PubMed          Journal:  Infection        ISSN: 0300-8126            Impact factor:   3.553


  9 in total

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2.  Finding a method for optimizing risk adjustment when comparing surgical-site infection rates.

Authors:  Christian Brandt; Sonja Hansen; Dorit Sohr; Franz Daschner; Henning Rüden; Petra Gastmeier
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3.  Ten years of KISS: the most important requirements for success.

Authors:  Petra Gastmeier; Dorit Sohr; Frank Schwab; Michael Behnke; Irina Zuschneid; Christian Brandt; Markus Dettenkofer; Iris F Chaberny; Henning Rüden; Christine Geffers
Journal:  J Hosp Infect       Date:  2008-10       Impact factor: 3.926

4.  Improved risk adjustment for comparison of surgical site infection rates.

Authors:  Eveline L P E Geubbels; Diederick E Grobbee; Christina M J E Vandenbroucke-Grauls; Jan C Wille; Annette S de Boer
Journal:  Infect Control Hosp Epidemiol       Date:  2006-11-17       Impact factor: 3.254

5.  Identifying patients at high risk of surgical wound infection. A simple multivariate index of patient susceptibility and wound contamination.

Authors:  R W Haley; D H Culver; W M Morgan; J W White; T G Emori; T M Hooton
Journal:  Am J Epidemiol       Date:  1985-02       Impact factor: 4.897

6.  Surgical site infection prevention: the importance of operative duration and blood transfusion--results of the first American College of Surgeons-National Surgical Quality Improvement Program Best Practices Initiative.

Authors:  Darrell A Campbell; William G Henderson; Michael J Englesbe; Bruce L Hall; Michael O'Reilly; Dale Bratzler; E Patchen Dellinger; Leigh Neumayer; Barbara L Bass; Matthew M Hutter; James Schwartz; Clifford Ko; Kamal Itani; Steven M Steinberg; Allan Siperstein; Robert G Sawyer; Douglas J Turner; Shukri F Khuri
Journal:  J Am Coll Surg       Date:  2008-10-10       Impact factor: 6.113

7.  Surgical wound infection rates by wound class, operative procedure, and patient risk index. National Nosocomial Infections Surveillance System.

Authors:  D H Culver; T C Horan; R P Gaynes; W J Martone; W R Jarvis; T G Emori; S N Banerjee; J R Edwards; J S Tolson; T S Henderson
Journal:  Am J Med       Date:  1991-09-16       Impact factor: 4.965

8.  A user evaluation of the Nosocomial Infection National Surveillance System: surgical site infection module.

Authors:  J A Wilson; V P Ward; R Coello; A Charlett; A Pearson
Journal:  J Hosp Infect       Date:  2002-10       Impact factor: 3.926

9.  Does stratifying surgical site infection rates by the National Nosocomial Infection Surveillance risk index influence the rank order of the hospitals in a surveillance system?

Authors:  S Brümmer; C Brandt; D Sohr; P Gastmeier
Journal:  J Hosp Infect       Date:  2008-06-16       Impact factor: 3.926

  9 in total
  4 in total

1.  Prolonged duration of surgery: a new look at the causes.

Authors:  C Ruef
Journal:  Infection       Date:  2011-06       Impact factor: 3.553

2.  Teaching surgery takes time: the impact of surgical education on time in the operating room.

Authors:  Christopher Vinden; Richard Malthaner; Jacob McGee; J Andrew McClure; Jennifer Winick-Ng; Kuan Liu; Danielle M Nash; Blayne Welk; Luc Dubois
Journal:  Can J Surg       Date:  2016-04       Impact factor: 2.089

3.  Association of Robotic-Assisted vs Laparoscopic Radical Nephrectomy With Perioperative Outcomes and Health Care Costs, 2003 to 2015.

Authors:  In Gab Jeong; Yash S Khandwala; Jae Heon Kim; Deok Hyun Han; Shufeng Li; Ye Wang; Steven L Chang; Benjamin I Chung
Journal:  JAMA       Date:  2017-10-24       Impact factor: 56.272

4.  Short Term Survival after Admission for Heart Failure in Sweden: Applying Multilevel Analyses of Discriminatory Accuracy to Evaluate Institutional Performance.

Authors:  Nermin Ghith; Philippe Wagner; Anne Frølich; Juan Merlo
Journal:  PLoS One       Date:  2016-02-03       Impact factor: 3.240

  4 in total

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