Skip to main navigation menu Skip to main content Skip to site footer

Original article

Vol. 152 No. 1112 (2022)

Number of comorbidities and their impact on perioperative outcome and costs – a single centre cohort study

  • Loris Cavalli
  • Luzius Angehrn
  • Christian Schindler
  • Niccolò Orsini
  • Christian Grob
  • Mark Kaufmann
  • Luzius A. Steiner
  • Matthias Schwenkglenks
  • Salome Dell-Kuster
Cite this as:
Swiss Med Wkly. 2022;152:w30135



AIMS OF THE STUDY: Multimorbidity is a growing global health problem, resulting in an increased perioperative risk for surgical patients. Data on both the prevalence of multimorbidity and its impact on perioperative outcome are limited. The American Society of Anesthesiologists (ASA) classification uses only the single most severe systemic disease to define the ASA class and ignores multimorbidity. This study aimed to assess the number and type of all anaesthesia-relevant comorbidities and to analyse their impact on outcome and hospital costs.

METHODS: This cohort study is nested in the ClassIntra® validation study and includes only patients enrolled at the University Hospital of Basel. Approximately 30 patients per surgical discipline undergoing any type of in-hospital surgery were followed up until hospital discharge to record all intra- and postoperative adverse events. In addition, the type and severity of all perioperatively relevant comorbidities were extracted from the electronic medical record according to a predefined list. The primary endpoint was the number of all anaesthesia-relevant comorbidities by ASA class. Using structural equation models, the direct and indirect effects of comorbidities on costs were estimated after adjustment for the ASA class and further relevant confounders and mediators.

RESULTS: Of 320 enrolled patients, 27 were ASA I (8%), 150 ASA II (47%), 116 ASA III (36%) and 27 ASA IV (8%). The median number of comorbidities per patient was 5 (range 0–18), this number significantly increasing with higher ASA class: 1 comorbidity (95% CI 0.0–2.0) in ASA I, 4 comorbidities (3.8–4.2) in ASA II, 9 (8.1–9.9) in ASA III and 12 (10–14) in ASA IV patients. Independent of ASA class, each additional comorbidity increased hospital costs by EUR 1,198 (95% CI 288–2108) with almost identical proportions of direct and indirect effects. The number of anaesthesia-relevant comorbidities also increased postoperative complications and postoperative length of hospital stay.

CONCLUSIONS: Multimorbidity in perioperative patients is highly prevalent and has a relevant impact on hospital costs, independent of the ASA class. Incorporating multimorbidity into the ASA classification might be warranted to improve its predictive ability and support adequate reimbursement.

The ClassIntra® validation study had been registered on (NCT03009929).


  1. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012 Jul;380(9836):37–43.
  2. Bainbridge D, Martin J, Arango M, Cheng D ; Evidence-based Peri-operative Clinical Outcomes Research (EPiCOR) Group. Perioperative and anaesthetic-related mortality in developed and developing countries: a systematic review and meta-analysis. Lancet. 2012 Sep;380(9847):1075–81.
  3. CIHI. Care in Canadian ICUs Ottawa: CIHI 2016 [Available from: accessed January 2018.
  4. WHO. Global spending on health: a world in transition Geneva: WHO 2019 [Available from: accessed March 9 2021.
  5. ASA Physical Status Classification System. 2014 [Available from: accessed April 2021.
  6. Lagasse RS. Anesthesia safety: model or myth? A review of the published literature and analysis of current original data. Anesthesiology. 2002 Dec;97(6):1609–17.
  7. Visser A, Geboers B, Gouma DJ, Goslings JC, Ubbink DT. Predictors of surgical complications: A systematic review. Surgery. 2015 Jul;158(1):58–65.
  8. Menke H, Klein A, John KD, Junginger T. Predictive value of ASA classification for the assessment of the perioperative risk. Int Surg. 1993 Jul-Sep;78(3):266–70.
  9. Hemmila MR, Jakubus JL, Maggio PM, Wahl WL, Dimick JB, Campbell DA Jr, et al. Real money: complications and hospital costs in trauma patients. Surgery. 2008 Aug;144(2):307–16.
  10. Staiger RD, Cimino M, Javed A, Biondo S, Fondevila C, Périnel J, et al. The Comprehensive Complication Index (CCI®) is a Novel Cost Assessment Tool for Surgical Procedures. Ann Surg. 2018 Nov;268(5):784–91.
  11. Ramly EP, Larentzakis A, Bohnen JD, Mavros M, Chang Y, Lee J, et al. The financial impact of intraoperative adverse events in abdominal surgery. Surgery. 2015 Nov;158(5):1382–8.
  12. Abouleish AE, Cohen NH. ASA provides exam- ples to each ASA Physical Status Class [ASA Provides Examples to Each ASA Physical Status Class.]. ASA Newsl. 2015;79(6):38–9.
  13. Dell-Kuster S, Gomes NV, Gawria L, Aghlmandi S, Aduse-Poku M, Bissett I, et al. Prospective validation of classification of intraoperative adverse events (ClassIntra): international, multicentre cohort study. BMJ. 2020 Aug;370:m2917.
  14. Boes S, Napierala C. Assessment of the introduction of DRG-based reimbursement in Switzerland: evidence on the short-term effects on length of stay compliance in university hospitals [published Online First: 2021/04/30]. Health Policy. 2021 Jun;125(6):739–50.
  15. Swiss DR. [Available from: accessed Oktober 7 2021.
  16. Acock AC. Discovering Structural Equation Modeling Using Stata. Revised ed. College Station, TX: Stata Press 2013.
  17. Kline RB. Principles and Practice of Structural Equation Modeling. 4th ed. New York: Guilford Press 2016.
  18. BUPA. (British United Provident Association) [Available from: accessed August 17th 2015.
  19. BUPA (British United Provident Association). Schedule of Procedures 1999 [Available from: accessed August 17th 2015.
  20. Sutton R, Bann S, Brooks M, Sarin S. The Surgical Risk Scale as an improved tool for risk-adjusted analysis in comparative surgical audit. Br J Surg. 2002 Jun;89(6):763–8.
  21. Slankamenac K, Graf R, Barkun J, Puhan MA, Clavien PA. The comprehensive complication index: a novel continuous scale to measure surgical morbidity. Ann Surg. 2013 Jul;258(1):1–7.
  22. Cullen DJ, Apolone G, Greenfield S, Guadagnoli E, Cleary P. ASA Physical Status and age predict morbidity after three surgical procedures. Ann Surg. 1994 Jul;220(1):3–9.
  23. Kay HF, Sathiyakumar V, Yoneda ZT, Lee YM, Jahangir AA, Ehrenfeld JM, et al. The effects of American Society of Anesthesiologists physical status on length of stay and inpatient cost in the surgical treatment of isolated orthopaedic fractures. J Orthop Trauma. 2014 Jul;28(7):e153–9.
  24. Schupper AJ, Shuman WH, Baron RB, Neifert SN, Chapman EK, Gilligan J, et al. Utilization of the American Society of Anesthesiologists (ASA) classification system in evaluating outcomes and costs following deformity spine procedures. Spine Deform. 2021 Jan;9(1):185–90.
  25. Bronheim RS, Caridi JM, Steinberger J, Hunter S, Neifert SN, Deutsch BC, et al. American Society of Anesthesiologists’ Status Association With Cost and Length of Stay in Lumbar Laminectomy and Fusion: Results From an Institutional Database. Spine. 2020 Mar;45(5):333–8.
  26. Lee DK, Frye A, Louis M, Koshy AN, Tosif S, Yii M, et al. Postoperative complications and hospital costs following small bowel resection surgery. PLoS One. 2020 Oct;15(10):e0241020.
  27. Khechen B, Haws BE, Bawa MS, Patel DV, Cardinal KL, Guntin JA, et al. The Impact of Comorbidity Burden on Complications, Length of Stay, and Direct Hospital Costs After Minimally Invasive Transforaminal Lumbar Interbody Fusion. Spine. 2019 Mar;44(5):363–8.
  28. Milne S, Parmar J, Ong TK. Adult Comorbidity Evaluation-27 as a predictor of postoperative complications, two-year mortality, duration of hospital stay, and readmission within 30 days in patients with squamous cell carcinoma of the head and neck. Br J Oral Maxillofac Surg. 2019 Apr;57(3):214–8.
  29. Shen Y, Silverstein JC, Roth S. In-hospital complications and mortality after elective spinal fusion surgery in the united states: a study of the nationwide inpatient sample from 2001 to 2005. J Neurosurg Anesthesiol. 2009 Jan;21(1):21–30.
  30. Fukuse T, Satoda N, Hijiya K, Fujinaga T. Importance of a comprehensive geriatric assessment in prediction of complications following thoracic surgery in elderly patients. Chest. 2005 Mar;127(3):886–91.
  31. Whitmore RG, Stephen JH, Vernick C, Campbell PG, Yadla S, Ghobrial GM, et al. ASA grade and Charlson Comorbidity Index of spinal surgery patients: correlation with complications and societal costs. Spine J. 2014 Jan;14(1):31–8.
  32. American College of Surgeons NSQIP Surgical Risk Calculator [Available from: accessed 21. Decemeber 2021.
  33. Mir WA, Fiumara F, Shrestha DB, Gaire S, Verda L. Utilizing the Most Accurate Preoperative Risk Calculator [published Online First: 20210810]. Cureus. 2021 Aug;13(8):e17054.
  34. Vaziri S, Abbatematteo JM, Fleisher MS, Dru AB, Lockney DT, Kubilis PS, et al. Correlation of perioperative risk scores with hospital costs in neurosurgical patients [published Online First: 20190215]. J Neurosurg. 2019 Feb;132(3):818–24. Crossref reports the DOI should be "10.3171/2018.10.JNS182041", not "10.3171/2018.10.Jns182041". Edifix has used the Crossref-supplied DOI. (Ref. 34 "Vaziri, Abbatematteo, Fleisher, Dru, Lockney, Kubilis, et al., 2019")
  35. Eappen S, Lane BH, Rosenberg B, Lipsitz SA, Sadoff D, Matheson D, et al. Relationship between occurrence of surgical complications and hospital finances. JAMA. 2013 Apr;309(15):1599–606.
  36. de la Plaza Llamas R, Hidalgo Vega Á, Latorre Fragua RA, López Marcano AJ, Medina Velasco AA, Díaz Candelas DA, et al. The Cost of Postoperative Complications and Economic Validation of the Comprehensive Complication Index: prospective Study. Ann Surg. 2021 Jan;273(1):112–20.
  37. Khan NA, Quan H, Bugar JM, Lemaire JB, Brant R, Ghali WA. Association of postoperative complications with hospital costs and length of stay in a tertiary care center. J Gen Intern Med. 2006 Feb;21(2):177–80.
  38. Dimick JB, Weeks WB, Karia RJ, Das S, Campbell DA Jr. Who pays for poor surgical quality? Building a business case for quality improvement. J Am Coll Surg. 2006 Jun;202(6):933–7.
  39. Mehra T, Müller CT, Volbracht J, Seifert B, Moos R. Predictors of High Profit and High Deficit Outliers under SwissDRG of a Tertiary Care Center. PLoS One. 2015 Oct;10(10):e0140874.
  40. Grosflam JM, Wright EA, Cleary PD, Katz JN. Predictors of blood loss during total hip replacement surgery. Arthritis Care Res. 1995 Sep;8(3):167–73.

Most read articles by the same author(s)

1 2 3 > >>