· Tele-ICU services are provided either by existing staff within the network to smaller centers, or outsourced to larger networks or independent firms
· The impact of tele-ICU adoption can result in a decrease in ICU mortality as large as 32%
· The impact of tele-ICU adoption of length of stay is mixed, with some studies reporting a significant decrease, while others report a small, but statistically insignificant decrease
· The degree of impact of tele-ICU adoption is linked to several factors such as yearly admission rates, location (urban vs. rural) and level of authority given to the tele-ICU team leading to increased positive impacts.
Badea, A; Groot, G; Reeder, B; Young, C; Ellsworth, C; Howell-Spooner, B. How to deliver remote ICU care for COVID-19 patients to avoid/prevent transfer from smaller communities to tertiary care hospitals. 2021 Apr 6; Document no.: CC210301 RR. In: COVID-19 Rapid Evidence Reviews [Internet]. SK: SK COVID Evidence Support Team, c2020. 13p. (CEST rapid review report)
There is limited research examining COVID-19 ICU patients undergoing prolonged (>14 days) mechanical ventilation
Rates of prolonged mechanical ventilation, defined as > 14 days, among COVID-19 ICU patients ranged from 16.7% to 33.3%.
Overall, studies suggest that length of ICU stay range from 11 to 31 days and length of hospital stay range from 25 to 51 days among COVID-19 patients who have undergone prolonged mechanical ventilation.
Following ICU discharge, patients are admitted to general wards, subacute nursing facilities, pneumological sub-intensive units, rehabilitation wards or long-term acute care.
Groot, G; McLean, M; Fox, L; Mueller, M. What is the final disposition of post-COVID patients who require chronic ventilation in the ICU? 2021 Feb 27; Document no.: CC011101 RR. In: COVID-19 Rapid Evidence Reviews [Internet]. SK: SK COVID Evidence Support Team, c2020. 37 p. (CEST rapid review report)
· There is little literature on the performance of triage frameworks. However, critiques of frameworks can help to inform the development of future protocols.
· It is ethically problematic to include age as a triage factor rather than the more nuanced factors of frailty and chronic comorbidities.
· The public should be included when creating triage protocols to create transparency and trust in the health system.
· Healthcare providers should be familiar with the ethical decisions that have been made in establishing the protocols. However, using a triage team to make decisions about resource allocation would alleviate moral burden from clinicians.
· Regular review of current guidelines, such as the use of SOFA scores, is recommended as knowledge about COVID-19 changes.
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· Patients should be regularly reassessed to allow for timely redistribution of critical resources.
Fick, F; Valiani, S; Miller, L; Howell-Spooner, B. Does data exist on the performance of triage or resource allocation frameworks for COVID-19 and other pandemics? 2020 Dec 17; Document no.: CC120401 RR. In: COVID-19 Rapid Evidence Reviews [Internet]. SK: SK COVID Evidence Support Team, c2020. 91 p. (CEST rapid review report)
No studies directly evaluated the association between level of surge capacity and quality of care indicators for COVID-19 patients. However, in more broad studies, the findings suggest that mortality and other adverse events increase when the strain on the intensive care capacity increases.
A tiered staffing strategy is recommended to meet surge capacity needs in the ICU: High critical care nurse to patient ratios (1:1 or 1:2) are recommended to provide high quality patient care.
There is a lack of high-quality evidence to support ICU triage protocols tailored for patients with COVID-19. Nevertheless, the protocols must be flexible, adaptable according to the availability of local resources, and effective for inter-hospital patient transfer.
While the Crisis Standards of Care (CSC) guidelines (e.g., Saskatchewan’s Critical Care Resource Allocation Framework, published on September 2020) can be used to triage newly admitted COVID-19 patients requiring critical care, there is contradicting evidence about using the Sequential Organ Failure Assessment (SOFA) score for ICU triage of patients with COVID-19.
The literature suggests the use of mathematical modeling to support capacity planning (e.g., very low, low, medium, and high intensity patient surge response)
To relieve pressure from ICUs, other types of units (e.g., Step Down Unit [SDU] or Surge Clinic) can be implemented.
Azizian, A; Valiani, S; Groot, G; Badea, A; Miller, L; Howell-Spooner, B. At what level of surge capacity do quality of care indicators suffer? 2020 Dec 10; Document no.: CC120301 RR. In: COVID-19 Rapid Evidence Reviews [Internet]. SK: SK COVID Evidence Support Team, c2020. 17 p. (CEST rapid review report)
Azizian, A; Valiani, S; Groot, G; Badea, A; Miller, L; Howell-Spooner, B. At what level of surge capacity do quality of care indicators suffer? 2020 Dec 10; Document no.: CC120301 RR Table. In: COVID-19 Rapid Evidence Reviews [Internet]. SK: SK COVID Evidence Support Team, c2020. 17 p. (CEST table)
· A burgeoning body of research exists about factors associated with in-hospital mortality among COVID-19 patients; however, focus on intensive care settings remains limited.
· The most frequent predictors of critical care mortality integrate age, physiologic markers and laboratory parameters in the most parsimonious models or prognostic scoring systems.
· Commonly used prognostic scoring systems such as MEWS, APACHE and SOFA provide crude mortality risk prediction that may be improved with machine learning algorithms that potentially offer more clinically relevant windows and opportunities for mortality risk prediction prior to deterioration.
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· Between centre variation is potentially an important determinant of critical care mortality that needs to be explored.
Williams-Roberts, H; Valiani, S; McLean, M; Miller, L; Howell-Spooner, B. What are the predictors of mortality in hospitalized COVID-19 patients? 2020 Dec 9; Document no.: CC120402 RR. In: COVID-19 Rapid Evidence Reviews [Internet]. SK: SK COVID Evidence Support Team, c2020. 33 p. (CEST rapid review report)