Fast, evidence-based triage of surgical lists 

Applying a proven approach to prioritizing surgical elective lists

Clearing the elective surgical lists using an evidence-based approach, risk-adjusted for individual patients, their comorbilities and severity of operation
COVID-19 has had a huge impact on hospital services, particularly critical care. Some countries may be seeing lower bed occupancy than expected, but the impact on nursing resource is still heavy and there will be future waves.  Health service managers globally are mobilising everything to manage the current crisis but are also cancelling services they consider “non-urgent” without considering the short and medium consequences.
PROBLEM

Many patients who do not have COVID-19 still need urgent care but are not getting that at present.  They will be back with more severe symptoms and there will also be a huge backlog when elective services restart.  Tens of thousands of patients waiting for elective surgery, with a massive backlog to clear when we switch elective services back on after COVID:

  • Who should get their operation on first?
  • How can we automate that triage process? because otherwise, we’ll have to set up months of outpatients clinics for the surgeons to reassess them all face to face.
SOLUTION
  • Our COMPASS Surgical List Triage system runs a bulk assessment of patients on elective surgical waiting lists. It carries out an individualised risk assessment for each patient, deriving risk of mortality, risk of complications and the list of the most probably complications (with associated probability) in both the short and longer term. 
  • Can apply set criteria (not just based on overall risk, but the value added of who has what risk of what complication) to triage and prioritise. System can say which patients are better off being optimised first (with the double benefit of better outcomes for them, and alleviated pressure on the immediate operating lists, as they can be deferred).
  • Clinicians/physicians can review the long list and click through to the one-page full predictive menu for any patient to support their decision making.
  • Patients that may benefit from optimization before surgery are suggested for individual review and decision making. 
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