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Objectives This study aimed to determine which method to triage intensive care patients using chronic comorbidity in a pandemic was perceived to be the fairest by the general public. Secondary objectives were to determine whether the public perceived it fair to provide preferential intensive care triage to vulnerable or disadvantaged people, and frontline healthcare workers. Methods A postal survey of 2000 registered voters randomly selected from the Australian Electoral Commission electoral roll was performed. The main outcome measures were respondents' fairness rating of four hypothetical intensive care triage methods that assess comorbidity (chronic medical conditions, long-term survival, function and frailty); and respondents' fairness rating of providing preferential triage to vulnerable or disadvantaged people, and frontline healthcare workers. Results The proportion of respondents who considered it fair to triage based on chronic medical conditions, long-term survival, function and frailty, was 52.1, 56.1, 65.0 and 62.4%, respectively. The proportion of respondents who considered it unfair to triage based on these four comorbidities was 31.9, 30.9, 23.8 and 23.2%, respectively. More respondents considered it unfair to preferentially triage vulnerable or disadvantaged people, than fair (41.8% versus 21.2%). More respondents considered it fair to preferentially triage frontline healthcare workers, than unfair (44.2% versus 30.0%). Conclusion Respondents in this survey perceived all four hypothetical methods to triage intensive care patients based on comorbidity in a pandemic disaster to be fair. However, the sizable minority who consider this to be unfair indicates that these triage methods could encounter significant opposition if they were to be enacted in health policy.

Background and Objective: An influenza pandemic has the potential to overwhelm intensive care resources, but the views of the general public on how resources should be allocated in such a scenario were unknown. We aimed to determine Australian and New Zealand public opinion on how intensive care unit beds should be allocated during an influenza pandemic., Design, Setting, and Participants: A postal questionnaire was sent to 4000 randomly selected registered voters; 2000 people each from the Australian Electoral Commission and New Zealand Electoral Commission rolls., Main Outcome Measure: The respondents' preferred method to triage ICU patients in an influenza pandemic. Respondents chose from six methods: use a "first in, first served" approach; allow a senior doctor to decide; use pre-determined health department criteria; use random selection; use the patient's ability to pay; use the importance of the patient to decide. Respondents also rated each of the triage methods for fairness., Results: Australian respondents preferred that patients be triaged to the ICU either by a senior doctor (43.2%) or by pre-determined health department criteria (38.7%). New Zealand respondents preferred that triage be performed by a senior doctor (45.9%). Respondents from both countries perceived triage by a senior doctor and by pre-determined health department criteria to be fair, and the other four methods of triage to be unfair., Conclusion: In an influenza pandemic, when ICU resources would be overwhelmed, survey respondents preferred that ICU triage be performed by a senior doctor, but also perceived the use of pre-determined triage criteria to be fair.

Objectives: To develop an influenza pandemic ICU triage (iPIT) protocol that excludes patients with the highest and lowest predicted mortality rates, and to determine the increase in ICU bed availability that would result., Design and Setting: Post-hoc analysis of a study evaluating two triage protocols, designed to determine which patients should be excluded from access to ICU resources during an influenza pandemic. ICU mortality rates were determined for the individual triage criteria in the protocols and included criteria based on the Sequential Organ Failure Assessment (SOFA) score. Criteria resulting in mortality rates outside the 25th and 75th percentiles were used as exclusion criteria in a new iPIT-1 protocol. The SOFA threshold component was modified further and reported as iPIT-2 and iPIT-3., Main Outcome Measure: Increase in ICU bed availability., Results: The 25th and 75th percentiles for ICU mortality were 8.3% and 35.2%, respectively. Applying the iPIT-1 protocol resulted in an increase in ICU bed availability at admission of 71.7% ± 0.6%. Decreasing the lower SOFA score exclusion criteria to ≤6 (iPIT-2) and ≤4 (iPIT-3) resulted in an increase in ICU bed availability at admission of 66.9% ± 0.6% and 59.4 ± 0.7%, respectively (P < 0.001)., Conclusion: The iPIT protocol excludes patients with the lowest and highest ICU mortality, and provides increases in ICU bed availability. Adjusting the lower SOFA score exclusion limit provides a method of escalation or de- escalation to cope with demand.

Objective: To determine the increase in intensive care unit (ICU) bed availability that would result from the use of the New South Wales and Ontario Health Plan for an Influenza Pandemic (OHPIP) triage protocols., Design, Setting and Patients: Prospective evaluation study conducted in eight Australian, adult, general ICUs, between September 2009 and May 2010. All patients who were admitted to the ICU, excluding those who had elective surgery, were prospectively evaluated using the two triage protocols, simulating a pandemic situation. Both protocols were originally developed to determine which patients should be excluded from accessing ICU resources during an influenza pandemic., Main Outcome Measure: Increase in ICU bed availability., Results: At admission, the increases in ICU bed availability using Tiers 1, 2 and 3 of the NSW triage protocol were 3.5%, 14.7% and 22.7%, respectively, and 52.8% using the OHPIP triage protocol (P < 0.001). Re-evaluation of patients at 12 hours after admission using Tiers 1, 2 and 3 of the NSW triage protocol incrementally increased ICU bed availability by 19.2%, 16.1% and 14.1%, respectively (P < 0.001). The maximal cumulative increases in ICU bed availability using Tiers 1, 2 and 3 of the NSW triage protocol were 23.7%, 31.6% and 37.5%, respectively, at 72 hours (P < 0.001), and 65.0% using the OHPIP triage protocol, at 120 hours (P < 0.001)., Conclusion: Both triage protocols resulted in increases in ICU bed availability, but the OHPIP protocol provided the greatest increase overall. With the NSW triage protocol, ICU bed availability increased as the protocol was escalated.