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Postoperative Critical Care: Findings from SNAP-2

In this article, Dr Danny Wong, anaesthetist and health services researcher at the NIAA HSRC, explores why we use critical care in the postoperative period and explains the results of the SNAP 2: EPICCS study. This multicentre observational cohort study looked at the availability of postoperative critical care beds, and which patients are being admitted to them.

Although intended for benefit, surgery exposes patients to potential risks and some patients may develop complications. Critical care is thought to protect against the development of these complications, and is recommended for patients at higher risk. Critical care is a broad umbrella term for higher-intensity care that is delivered in specific areas of the hospital, typically the intensive care unit (ICU) or high-dependency unit (HDU). These hospital areas are usually able to provide more nurses and doctors, looking after fewer patients, while also being able to provide some specific interventions which are not available elsewhere in the hospital (Table 1).

Table 1: Some features of critical care as described using a Structure-Process-Outcome [1] framework

SNAP 2: EPICCS

Although expert bodies such as the Royal College of Surgeons, National Confidential Enquiry into Patient Outcomes and Death (NCEPOD) and the National Institute of Clinical Excellence (NICE) have recommended that high-risk patients should be admitted automatically to critical care after their surgery [2], [3], [4], previous literature suggests that this does not consistently happen [5], [6], [7].

Therefore, in 2017, the Royal College of Anaesthetists’ Health Services Research Centre, in conjunction with the Surgical Outcomes Research Centre at UCL conducted a multicentre observational cohort study, The 2nd Sprint National Anaesthesia Project: EPIdemiology of Critical Care provision after Surgery (SNAP-2: EPICCS) [8], to investigate this supposed misallocation of critical care resources, seeking to answer the following research questions:

  1. What is the availability of postoperative critical care?
  2. How do clinicians estimate perioperative risk?
  3. How accurate are current available risk prediction tools?
  4. How do clinicians decide which patients to admit for postoperative critical care?
  5. What factors influence their admission?
  6. Is there a benefit to postoperative critical care admission?

The study consisted of 2 parts: an organisational survey of critical care resources and availability, and a patient cohort study collecting data about patient risks and outcomes.

Organisational Survey

A survey of postoperative critical care availability was conducted in 309 hospitals across the United Kingdom, Australia and New Zealand (NZ)[9].

Postoperative critical care availability was found to differ between countries. UK hospitals reported fewer critical care beds per 100 hospital beds (median = 2.7) compared with Australia (median = 3.7) and NZ (median = 3.5). Enhanced care/high-acuity beds used to manage some high-risk patients were identified in around 31% of hospitals. These bed areas did not quite meet the definitions of critical care, but were typically able to deliver a subset of critical care interventions, and were thought to have evolved to overcome shortages in ICU and HDU beds.

The estimated numbers of critical care beds per 100,000 population were 9.3, 14.1, and 9.1 in the UK, Australia, and NZ, respectively (Table 2). The estimated per capita high-acuity bed capacities per 100,000 population were 1.2, 3.8, and 6.4 in the UK, Australia, and NZ, respectively.

Table 2: Critical care and high-acuity care beds per capita. The sum of the number of critical care beds was divided by the sum of all hospital beds within each country, and multiplied by 100, to obtain the average ratio of critical care beds to hospital beds in each country. This ratio was then multiplied by OECD data on hospital beds per capita to obtain the per capita critical care bed numbers, rescaled to per 100,000 population.

Patient Cohort Study

In a subset of 274 of the hospitals that participated in the Organisation Survey, a cohort study enrolling 26,502 patients undergoing inpatient surgery was undertaken. In this cohort, less than 40% of predicted high-risk patients (defined as having a 5% or higher predicted 30-day mortality) were admitted to critical care directly after surgery. Predictions in risk can vary depending on which type of risk model is used, but in this study, 3 models - the Portsmouth Physiological and Operative Severity Score for the enumeration of Mortality (P-POSSUM)[10], the Surgical Risk Scale (SRS)[11] and the Surgical Outcome Risk Tool (SORT)[12], [13] - were used to assess predicted risk and the low admission to critical care was true regardless of the model (Figure 1). We cover these risk assessment tools in much great detail next week; you can always skip ahead using this link if you would like to learn more about them before carrying on.

Figure 1: Critical care admissions (blue) in patients of high- and low-predicted mortality risks in the overall cohort (A), and in each country (B). Mortality risks were computed using P-POSSUM, SORT and SRS. Although guidelines recommend that patients with predicted mortality of ≥5% should be admitted to critical care immediately after surgery, only approximately one-third were in this cohort. A substantial proportion of those admitted to critical care postoperatively were low-risk patients with <5% predicted mortality.

Compared with objective risk tools, subjective clinical assessment performed similarly in terms of discrimination, but consistently overpredicted risk. However, a model combining information from both objective tools and subjective assessment improved the accuracy and clinical applicability of risk predictions (paper accepted, in press).

Associations were identified between patient risk factors (e.g. increased comorbidities, more complex surgery, higher surgical urgency) and the likelihood of being recommended postoperative critical care admission. Increased critical care bed availability had a small but significant association with critical care recommendation (adjusted odds ratio [OR] = 1.05 per empty critical care bed at the time of surgery), suggesting a subtle effect of exogenous influences on clinical decision-making.

Conclusions

The results of SNAP-2: EPICCS have shown that critical care resources vary between countries, and in some places, the development of Enhanced Care/High-Acuity Care areas has occurred. High-risk patients are still not being admitted to critical care consistently despite guidelines. This may be due to the availability of resources at the time of surgery. More patients should have their predicted mortality risks assessed prior to surgery to identify who is appropriate for critical care admission, and in the future, this may involve the use of models that combine subjective clinical assessment with objective measurements.

Further work is still underway with data from SNAP-2: EPICCS to examine whether critical care helps to improve patient outcomes.

What is critical care bed availability like in your place of work? How do you decide who should be admitted to critical care postoperatively? Based on the last two articles: do you think we should change the way we provide high acuity care for high risk patients? Do you have a separate Enhanced Area or PACU area? Please do use the discussion to discuss your experiences with your fellow learners’.

References

  1. Donabedian A. Evaluating the quality of medical care. Milbank Mem Fund Q. 1966 Jul;44(3):Suppl:166-206.
  2. Lees NP, Peden CJ, Dhesi JK, Quiney N, Lockwood S, Symons NRA, et al. The High-Risk General Surgical Patient: Raising the Standard [Internet]. The Royal College of Surgeons of England; 2018 [cited 2019 Apr 9]
  3. Findlay GP, Goodwin APL, Protopapa K, Smith NCE, Mason M. Knowing the Risk: A review of the peri-operative care of surgical patients [Internet]. National Confidential Enquiry into Patient Outcome and Death (NCEPOD); 2011.
  4. National Institute for Health and Care Excellence (NICE). NICE Guideline 180: Perioperative care in adults [Internet]. NICE; 2020 [cited 2020 Aug 25].
  5. Pearse RM, Harrison DA, James P, Watson D, Hinds C, Rhodes A, et al. Identification and characterisation of the high-risk surgical population in the United Kingdom. Crit Care. 2006;10(3):R81.
  6. Pearse RM, Moreno RP, Bauer P, Pelosi P, Metnitz P, Spies C, et al. Mortality after surgery in Europe: a 7 day cohort study. The Lancet. 2012;380(9847):1059–1065.
  7. The International Surgical Outcomes Study group. Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries. Br J Anaesth. 2016 Nov 1;117(5):601–9.
  8. Moonesinghe SR, Wong DJN, Farmer L, Shawyer R, Myles PS, Harris SK. SNAP-2 EPICCS: the second Sprint National Anaesthesia Project—EPIdemiology of Critical Care after Surgery: protocol for an international observational cohort study. BMJ Open. 2017 Sep 1;7(9):e017690.
  9. Wong DJN, Popham S, Wilson AM, Barneto LM, Lindsay HA, Farmer L, et al. Postoperative critical care and high-acuity care provision in the United Kingdom, Australia, and New Zealand. Br J Anaesth. 2019 Apr 1;122(4):460–9.
  10. Prytherch DR, Whiteley MS, Higgins B, Weaver PC, Prout WG, Powell SJ. POSSUM and Portsmouth POSSUM for predicting mortality. Br J Surg. 1998 Sep 1;85(9):1217–20.
  11. 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 1;89(6):763–8.
  12. Protopapa KL, Simpson JC, Smith NCE, Moonesinghe SR. Development and validation of the Surgical Outcome Risk Tool (SORT). Br J Surg. 2014 Dec;101(13):1774–83.
  13. NCEPOD, SOuRCe. Surgical Outcome Risk Tool (SORT) [Internet]. 2015 [cited 2016 Jun 3]

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Perioperative Medicine in Action

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