World Journal of Surgery

, Volume 42, Issue 10, pp 3125–3133 | Cite as

Time Attributable to Obesity in Surgery: A Multi-specialty Report on Day-of-Surgery Resource Utilization from 189,264 Cases

  • Dominykas Burneikis
  • Gareth Morris-Stiff
  • Sricharan Chalikonda
Original Scientific Report



Obesity presents a unique challenge in caring for surgical patients and has been shown to adversely affect outcomes for several operative procedures. However, quantitative data on surgical resource utilization attributable to obesity are scarce. The aim of this study was to quantify day-of-surgery resource utilization by degree of obesity.


Patients undergoing one of 14 common surgical procedures at our multicenter institution between 2008 and 2017 were identified from our operating room management databank. Multiple-variable regression analysis (MVRA) was performed to quantify the independent effect of body mass index (BMI) category on day-of-surgery resource utilization variables including procedure time, non-operative OR time, PACU time, number of unique staff and number of supplies used. Trends in mean BMI were examined for each procedure studied.


MVRA of the 189,264 cases in the database revealed consistently significant (p < 0.05) stepwise increase in procedure time by BMI category for all procedures studied. Non-operative OR time was also significantly prolonged, though to a lesser degree. There was no significant impact on number of unique staff, supplies utilized or PACU time by BMI category. Procedures most impacted by BMI category in terms of resource utilization were ventral hernia repair, laminectomy and hysterectomy.


Our study quantified day-of-surgery resource utilization for 14 major surgical procedures by BMI category. The need for additional resources to accommodate patients in higher BMI groups was consistent across all procedures studied and was primarily reflected by lengthened operative times.


  1. 1.
    Flegal KM, Carroll MD, Kit BK et al (2012) Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA 307:491CrossRefPubMedGoogle Scholar
  2. 2.
    Abarca-Gómez L, Abdeen ZA, Hamid ZA et al (2017) Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128 9 million children, adolescents, and adults. Lancet. CrossRefGoogle Scholar
  3. 3.
    Haslam DW, James WPT. Obesity. In: Lancet. 2005. Epub ahead of print 2005.
  4. 4.
    Hubert HB, Mcnamara PM, Castelli WP (1983) Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the framingham heart study. Circulation 67:968–977CrossRefPubMedGoogle Scholar
  5. 5.
    Schauer DP, Feigelson HS, Koebnick C et al (2017) Bariatric surgery and the risk of cancer in a large multisite cohort. Ann Surg. CrossRefPubMedGoogle Scholar
  6. 6.
    Finkelstein EA, Trogdon JG, Cohen JW et al (2009) Annual medical spending attributable to obesity: payer-and service-specific estimates. Health Aff 28:w822–w831CrossRefGoogle Scholar
  7. 7.
    Hirose K, Shore AD, Wick EC et al (2011) Pay for obesity? Pay-for-performance metrics neglect increased complication rates and cost for obese patients. J Gastrointest Surg 15:1128–1135CrossRefPubMedGoogle Scholar
  8. 8.
    Sood A, Firas Abdollah B, Jesse Sammon BD et al (2015) The effect of body mass index on perioperative outcomes after major surgery: results from the national surgical quality improvement program (ACS-NSQIP) 2005–2011. World J Surg 39:2376–2385. CrossRefPubMedGoogle Scholar
  9. 9.
    Hawn MT, Bian J, Leeth RR et al (2005) Impact of obesity on resource utilization for general surgical procedures. Ann Surg. 241:821-6-8CrossRefGoogle Scholar
  10. 10.
    HCUP-US tools and software page CCS-services and procedures. Accessed 16 Oct 2017
  11. 11.
    World Health Organization (2000) Obesity: preventing and managing the global epidemic: report of a WHO consultation. World Health OrganizationGoogle Scholar
  12. 12.
    Hamlin RJ, Sprung J, Hofer RE et al (2013) Obesity trends in the surgical population at a large academic center: a comparison between 1989–1991 to 2006–2008 epochs. Acta Chir Belg 113:397–400PubMedGoogle Scholar
  13. 13.
    Camhi SM, Bray GA, Bouchard C et al (2011) The relationship of waist circumference and BMI to visceral, subcutaneous, and total body fat: sex and race differences. Obesity 19:402–408CrossRefPubMedGoogle Scholar
  14. 14.
    Gallagher D, Visser M, Sepúlveda D et al (1996) How useful is body mass index for comparison of body fatness across age, sex, and ethnic groups? Am J Epidemiol 143:228–239CrossRefPubMedGoogle Scholar
  15. 15.
    Sun SX, Greenleaf EK, Hollenbeak CS et al (2015) Attributable cost of obesity in breast surgery: a matched cohort analysis. Am J Surg 210(668–677):e1Google Scholar
  16. 16.
    Brooks RA, Blansit K, Young-Lin N et al (2016) The economic impact of surgical care for morbidly obese endometrial cancer patients: a nationwide study. Am J Obstet Gynecol 214:498.e1–498.e6CrossRefGoogle Scholar
  17. 17.
    Mason RJ, Moroney JR, Berne TV (2013) The cost of obesity for nonbariatric inpatient operative procedures in the United States: national cost estimates obese versus nonobese patients. Ann Surg. 258:541–553PubMedGoogle Scholar

Copyright information

© Société Internationale de Chirurgie 2018

Authors and Affiliations

  • Dominykas Burneikis
    • 1
  • Gareth Morris-Stiff
    • 1
  • Sricharan Chalikonda
    • 1
  1. 1.Digestive Diseases and Surgery InstituteCleveland Clinic FoundationClevelandUSA

Personalised recommendations