Practices in Triage and Transfer of Critically Ill Patients: A Qualitative Systematic Review of Selection Criteria

In-Hospital Triage

The intensive care unit (ICU) is a finite and expensive resource with demand not infrequently exceeding capacity. Understanding ICU capacity strain is essential to gain situational awareness. Increased capacity strain can influence ICU triage decisions, which rely heavily on clinical judgment. Having an admission and triage protocol with which clinicians are very familiar can mitigate difficult, inappropriate admissions. This article reviews these concepts and methods of in-hospital triage.

Physicians' perceptions of intensive care patients' 1-year prognoses compared to realistic prognoses

BACKGROUND

It is unknown whether physicians treating critically ill patients have realistic perceptions of their patients' prognoses.

METHODS

We sent a survey by email to Finnish anesthesiologists to investigate their ability to estimate the probability of 1-year survival of intensive care unit (ICU) patients based on data available at the beginning of intensive care. We presented 12 fictional but real-life-based patient cases and asked the respondent to estimate the probability of 1-year survival in each case by choosing one of the alternatives 5%, 10%-90% in 10% intervals and 95%. We compared the physicians' estimates to registry data-based realistic prognoses of comparable patients treated in the ICU. Based on the difference between the estimate and the realistic prognosis, we categorized the estimates into three groups: (1) difference less than 10 percentage points, (2) difference between 10 and 20 percentage points, and (3) difference over 20 percentage points.

RESULTS

We received 210 responses (totally 2520 estimates). Of the respondents, 43 (20.5%) were specialists working mainly in the ICU, 81 (38.6%) were specialists working occasionally in the ICU, 47 (22.4%) were specialists not working in the ICU, and 39 (18.6%) were doctors in training. The difference between the estimate and the realistic prognosis was less than 10 percentage points for 1083 (43.0%) estimates, between 10 and 20 percentage points for 645 (25.6%) estimates, and over 20 percentage points for 792 (31.4%) estimates, out of which 612 (24.3% of all estimates) underestimated and 180 (7.1%) overestimated the likelihood of survival. The median error (the median of the differences between the estimate and the realistic prognosis) for all estimates was -8.8 [interquartile range (IQR), -20.0 to -0.2], which means that the most typical response underestimated the likelihood of survival by 9 percentage points. Based on the 12 estimates, we calculated the median error for each respondent. The median (IQR) of these median errors was -8.6 (-12.6 to -5.0) for specialists working mainly in the ICU, -8.1 (-13.0 to -5.2) for specialists working occasionally in the ICU, -9.7 (-17.7 to -6.3) for specialists not working in the ICU, and -9.1 (-14.5 to -5.1) for doctors in training (p = .29).

CONCLUSION

Finnish anesthesiologists commonly misestimate the long-term prognoses of ICU patients, more often underestimating than overestimating the likelihood of 1-year survival. More education about critically ill patients' prognoses and better prediction tools are needed.

Early Recognition of Low-Risk SARS-CoV-2 Pneumonia

Background

A shortage of beds in ICUs and conventional wards during the COVID-19 pandemic led to a collapse of health care resources.

Research Question

Can admission data and minor criteria by the Infectious Diseases Society of America (IDSA) and the American Thoracic Society (ATS) help identify patients with low-risk SARS-CoV-2 pneumonia?

Study Design and Methods

This multicenter cohort study included 1,274 patients in a derivation cohort and 830 (first wave) and 754 (second wave) patients in two validation cohorts. A multinomial regression analysis was performed on the derivation cohort to compare the following patients: those admitted to the ward (assessed as low risk); those admitted to the ICU directly; those transferred to the ICU after general ward admission; and those who died. A regression analysis identified independent factors for low-risk pneumonia. The model was subsequently validated.

Results

In the derivation cohort, similarities existed among those either directly admitted or transferred to the ICU and those who died. These patients could, therefore, be merged into one group. Five independently associated factors were identified as being predictors of low risk (not dying and/or requiring ICU admission) (ORs, with 95% CIs): peripheral blood oxygen saturation/Fio₂ > 450 (0.233; 0.149-0.364); < 3 IDSA/ATS minor criteria (0.231; 0.146-0.365); lymphocyte count > 723 cells/mL (0.539; 0.360-0.806); urea level < 40 mg/dL (0.651; 0.426-0.996); and C-reactive protein level < 60 mg/L (0.454; 0.285-0.724). The areas under the curve were 0.802 (0.769-0.835) in the derivation cohort, and 0.779 (0.742-0.816) and 0.801 (0.757-0.845) for the validation cohorts (first and second waves, respectively).

Interpretation

Initial biochemical findings and the application of < 3 IDSA/ATS minor criteria make early identification of low-risk SARS-CoV-2 pneumonia (approximately 80% of hospitalized patients) feasible. This scenario could facilitate and streamline health care resource allocation for patients with COVID-19.

Associations of Government-issued ICU Admission Criteria with Clinical Practices, Outcomes, and ICU Bed Occupancy

RATIONALE

In Japan, the government officially issued intensive care unit (ICU) admission criteria that require ICU units to admit patients who need a certain level of monitoring and procedures to ensure their reimbursement for ICU costs from April 2014.

OBJECTIVE

To assess whether the newly issued health policy on ICU admission criteria based on financial incentives for monitoring and procedures had any impact on clinical practices, outcomes, and ICU bed occupancy.

METHODS

Using a nationwide inpatient health claims database in Japan, we identified patients who were admitted to the ICU from April 2012 to March 2018. Outcomes were monitoring and procedures in the ICU, clinical outcomes, and ICU bed occupancy. The outcomes of monitoring and procedures and clinical outcomes were adjusted for patient characteristics. Interrupted time-series analyses were used to compare the trends in outcomes for two separate periods before and after the issue of the new health policy on ICU admission criteria in April 2014.

RESULTS

A total of 1,660,601 patients in 259 ICU-equipped hospitals were eligible. There were significant upward slope changes between the pre- and post-issue periods for all monitoring and procedures in the ICU, including invasive arterial pressure monitoring (5.62% change in trend per year; 95% CI, 4.75%-6.49%) and central venous pressure monitoring (1.22% change in trend per year; 95% CI, 0.78%-1.67%). There was no significant slope change between the pre- and post-issue periods for in-hospital mortality, but there were significant upward slope changes for complications of pneumonia (0.27% change in trend per year; 95% CI, 0.14%-0.39%) and catheter-related bloodstream infection (0.02% change in trend per year; 95% CI, 0.00%-0.14%). There were also significant upward slope changes in length of hospital stay, length of ICU stay, and hospitalization costs between the pre- and post-issue periods. There was no significant slope change between the pre- and post-issue periods for ICU bed occupancy.

CONCLUSIONS

The health policy on ICU admission criteria based on financial incentives for actions taken by providers was associated with increased monitoring and procedures, complications, lengths of hospital and ICU stay, and hospitalization costs without decreasing ICU bed occupancy.

Physicians' Acceptance of Triage Guidelines in the Context of the COVID-19 Pandemic: A Qualitative Study

Aims: One of the major ethical challenges posed by the Covid-19 pandemic comes in the form of fair triage decisions for critically ill patients in situations where life-saving resources are limited. In Spring 2020, the Swiss Academy of Medical Sciences (SAMS) issued specific guidelines on triage for intensive-care treatment in the context of the Covid-19 pandemic. While evidence has shown that the capacities of intensive care medicine throughout Switzerland were sufficient to take care of all critically ill patients during the first wave of the outbreak, no evidence is available regarding the acceptance of these guidelines by ICU staff. The aim of this qualitative study was to explore the acceptance and perceived implementation of the SAMS guidelines among a sample of senior physicians involved in the care of Covid-19 patients in the Canton of Ticino. Specific objectives included capturing and describing physicians' attitudes toward the guidelines, any challenges experienced in their application, and any perceived factors that facilitated or would facilitate their application.

Methods: We conducted face-to-face and telephone interviews with a purposive sample of nine senior physicians employed as either head of unity, deputy-head of unit, or medical director in either one of the two Covid-19 hospitals in the Canton of Ticino during the peak of the outbreak. Interviews were transcribed verbatim and thematically analyzed using an inductive approach.

Results: We found that participants held different views regarding the nature of the guidelines, saw decisions on admission as a matter of collective responsibility, argued that decisions should be based on a medical futility principle rather than an age criterion, and found that difficulties to address end-of-life issues led to a comeback of paternalism.

Conclusions: Results highlight the importance of clarifying the nature of the guidelines, establishing authority, and responsibility during triaging decisions, recognizing and addressing sources of interference with patients' autonomy, and the need of a cultural shift in timely and efficiently addressing end-of-life issues.

Predicting mortality of individual patients with COVID-19: a multicentre Dutch cohort

OBJECTIVE

Develop and validate models that predict mortality of patients diagnosed with COVID-19 admitted to the hospital.

DESIGN

Retrospective cohort study.

SETTING

A multicentre cohort across 10 Dutch hospitals including patients from 27 February to 8 June 2020.

PARTICIPANTS

SARS-CoV-2 positive patients (age ≥18) admitted to the hospital.

MAIN OUTCOME MEASURES

21-day all-cause mortality evaluated by the area under the receiver operator curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. The predictive value of age was explored by comparison with age-based rules used in practice and by excluding age from the analysis.

RESULTS

2273 patients were included, of whom 516 had died or discharged to palliative care within 21 days after admission. Five feature sets, including premorbid, clinical presentation and laboratory and radiology values, were derived from 80 features. Additionally, an Analysis of Variance (ANOVA)-based data-driven feature selection selected the 10 features with the highest F values: age, number of home medications, urea nitrogen, lactate dehydrogenase, albumin, oxygen saturation (%), oxygen saturation is measured on room air, oxygen saturation is measured on oxygen therapy, blood gas pH and history of chronic cardiac disease. A linear logistic regression and non-linear tree-based gradient boosting algorithm fitted the data with an AUC of 0.81 (95% CI 0.77 to 0.85) and 0.82 (0.79 to 0.85), respectively, using the 10 selected features. Both models outperformed age-based decision rules used in practice (AUC of 0.69, 0.65 to 0.74 for age >70). Furthermore, performance remained stable when excluding age as predictor (AUC of 0.78, 0.75 to 0.81).

CONCLUSION

Both models showed good performance and had better test characteristics than age-based decision rules, using 10 admission features readily available in Dutch hospitals. The models hold promise to aid decision-making during a hospital bed shortage.

Physicians' perspective on potentially non-beneficial treatment when assessing patients with advanced disease for ICU admission: a qualitative study

OBJECTIVE

The use of intensive care at the end of life can be high, leading to inappropriate healthcare utilisation, and prolonged suffering for patients and families. The objective of the study was to determine which factors influence physicians' admission decisions in situations of potentially non-beneficial intensive care.

DESIGN

This is a secondary analysis of a qualitative study exploring the triage process. In-depth interviews were analysed using an inductive approach to thematic content analysis.

SETTING

Data were collected in a Swiss tertiary care centre between March and June 2013.

PARTICIPANTS

12 intensive care unit (ICU) physicians and 12 internists routinely involved in ICU admission decisions.

RESULTS

Physicians struggled to understand the request for intensive care for patients with advanced disease and full code status. Physicians considered patients' long-term vital and functional prognosis, but they also resorted to shortcuts, that is, a priori consensus about reasons for admitting a patient. Family pressure and unexpected critical events were determinants of admission to the ICU. Patient preferences, ICU physician's expertise and collaborative decision making facilitated refusal. Physicians were willing to admit a patient with advanced disease for a limited amount of time to fulfil a personal need.

CONCLUSIONS

In situations of potentially non-beneficial intensive care, the influence of shortcuts or context-related factors suggests that practice variations and inappropriate admission decisions are likely to occur. Institutional guidelines and timely goals of care discussions with patients with advanced disease and their families could contribute to ensuring appropriate levels of care.

Level of Medical Intervention in Geriatric Settings: Decision Factors and Correlation With Mortality

OBJECTIVES

Level of medical intervention (LMI) has to be adapted to each patient in geriatric care. LMI scales intend to help nonintensive care (NIC) decisions, giving priority to patient choice and collegial discussion. In the present study, we aimed to assess the parameters associated with the NIC decision and whether these parameters differ from those associated with in-hospital mortality.

DESIGN

Prospective observational study.

SETTING AND PARTICIPANTS

All consecutive patients from a French 62-bed acute geriatric unit over 1 year.

METHODS

Factors from the geriatric assessment associated with the decision of NIC were compared with those associated with in-hospital and 1-year mortality, in univariate and multivariate analyses.

RESULTS

In total, 1654 consecutive patients (median age 87 years) were included. Collegial reflection led to NIC decision for 532 patients (32%). In-hospital and 1-year mortality were 22% and 54% in the NIC group vs 2% and 27% in the rest of the cohort (P < .001 for both). In multivariable analysis, high Charlson Comorbidity Index [odds ratio (OR) 1.15, 95% confidence interval (CI) 1.06-1.23, per point], severe neurocognitive disorders (OR 2.78, 95% CI 1.67-4.55), dependence (OR 1.92, 95% CI 1.45-2.59), and nursing home residence (OR 2.38, 95% CI 1.85-3.13) were highly associated with NIC decision but not with in-hospital mortality. Conversely, acute diseases had little impact on LMI despite their high short-term prognostic burden.

CONCLUSIONS AND IMPLICATIONS

Neurocognitive disorders and dependence were strongly associated with NIC decision, even though they were not significantly associated with in-hospital mortality. The decision-making process of LMI therefore seems to go beyond the notion of short-term survival.

Allocation of intensive care resources during an infectious disease outbreak: a rapid review to inform practice

BACKGROUND

The COVID-19 pandemic has placed sustained demand on health systems globally, and the capacity to provide critical care has been overwhelmed in some jurisdictions. It is unknown which triage criteria for allocation of resources perform best to inform health system decision-making. We sought to summarize and describe existing triage tools and ethical frameworks to aid healthcare decision-making during infectious disease outbreaks.

METHODS

We conducted a rapid review of triage criteria and ethical frameworks for the allocation of critical care resources during epidemics and pandemics. We searched Medline, EMBASE, and SCOPUS from inception to November 3, 2020. Full-text screening and data abstraction were conducted independently and in duplicate by three reviewers. Articles were included if they were primary research, an adult critical care setting, and the framework described was related to an infectious disease outbreak. We summarized each triage tool and ethical guidelines or framework including their elements and operating characteristics using descriptive statistics. We assessed the quality of each article with applicable checklists tailored to each study design.

RESULTS

From 11,539 unique citations, 697 full-text articles were reviewed and 83 articles were included. Fifty-nine described critical care triage protocols and 25 described ethical frameworks. Of these, four articles described both a protocol and ethical framework. Sixty articles described 52 unique triage criteria (29 algorithm-based, 23 point-based). Few algorithmic- or point-based triage protocols were good predictors of mortality with AUCs ranging from 0.51 (PMEWS) to 0.85 (admitting SOFA > 11). Most published triage protocols included the substantive values of duty to provide care, equity, stewardship and trust, and the procedural value of reason.

CONCLUSIONS

This review summarizes available triage protocols and ethical guidelines to provide decision-makers with data to help select and tailor triage tools. Given the uncertainty about how the COVID-19 pandemic will progress and any future pandemics, jurisdictions should prepare by selecting and adapting a triage tool that works best for their circumstances.