Assessment of Disparities Associated With a Crisis Standards of Care Resource Allocation Algorithm for Patients in 2 US Hospitals During the COVID-19 Pandemic

SOFA score performs worse than age for predicting mortality in patients with COVID-19

The use of the Sequential Organ Failure Assessment (SOFA) score, originally developed to describe disease morbidity, is commonly used to predict in-hospital mortality. During the COVID-19 pandemic, many protocols for crisis standards of care used the SOFA score to select patients to be deprioritized due to a low likelihood of survival. A prior study found that age outperformed the SOFA score for mortality prediction in patients with COVID-19, but was limited to a small cohort of intensive care unit (ICU) patients and did not address whether their findings were unique to patients with COVID-19. Moreover, it is not known how well these measures perform across races. In this retrospective study, we compare the performance of age and SOFA score in predicting in-hospital mortality across two cohorts: a cohort of 2,648 consecutive adult patients diagnosed with COVID-19 who were admitted to a large academic health system in the northeastern United States over a 4-month period in 2020 and a cohort of 75,601 patients admitted to one of 335 ICUs in the eICU database between 2014 and 2015. We used age and the maximum SOFA score as predictor variables in separate univariate logistic regression models for in-hospital mortality and calculated area under the receiver operator characteristic curves (AU-ROCs) and area under precision-recall curves (AU-PRCs) for each predictor in both cohorts. Among the COVID-19 cohort, age (AU-ROC 0.795, 95% CI 0.762, 0.828) had a significantly better discrimination than SOFA score (AU-ROC 0.679, 95% CI 0.638, 0.721) for mortality prediction. Conversely, age (AU-ROC 0.628 95% CI 0.608, 0.628) underperformed compared to SOFA score (AU-ROC 0.735, 95% CI 0.726, 0.745) in non-COVID-19 ICU patients in the eICU database. There was no difference between Black and White COVID-19 patients in performance of either age or SOFA Score. Our findings bring into question the utility of SOFA score-based resource allocation in COVID-19 crisis standards of care.

Evaluating Prognostic Bias of Critical Illness Severity Scores Based on Age, Sex, and Primary Language in the United States: A Retrospective Multicenter Study

OBJECTIVES

Although illness severity scoring systems are widely used to support clinical decision-making and assess ICU performance, their potential bias across different age, sex, and primary language groups has not been well-studied.

DESIGN SETTING AND PATIENTS

We aimed to identify potential bias of Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation (APACHE) IVa scores via large ICU databases.

SETTING/PATIENTS

This multicenter, retrospective study was conducted using data from the Medical Information Mart for Intensive Care (MIMIC) and eICU Collaborative Research Database. SOFA and APACHE IVa scores were obtained from ICU admission. Hospital mortality was the primary outcome. Discrimination (area under receiver operating characteristic [AUROC] curve) and calibration (standardized mortality ratio [SMR]) were assessed for all subgroups.

INTERVENTIONS

Not applicable.

MEASUREMENTS AND MAIN RESULTS

A total of 196,310 patient encounters were studied. Discrimination for both scores was worse in older patients compared with younger patients and female patients rather than male patients. In MIMIC, discrimination of SOFA in non-English primary language speakers patients was worse than that of English speakers (AUROC 0.726 vs. 0.783, p < 0.0001). Evaluating calibration via SMR showed statistically significant underestimations of mortality when compared with overall cohort in the oldest patients for both SOFA and APACHE IVa, female patients (1.09) for SOFA, and non-English primary language patients (1.38) for SOFA in MIMIC.

CONCLUSIONS

Differences in discrimination and calibration of two scores across varying age, sex, and primary language groups suggest illness severity scores are prone to bias in mortality predictions. Caution must be taken when using them for quality benchmarking and decision-making among diverse real-world populations.

Simulation of New York City's Ventilator Allocation Guideline During the Spring 2020 COVID-19 Surge

Importance

The spring 2020 surge of COVID-19 unprecedentedly strained ventilator supply in New York City, with many hospitals nearly exhausting available ventilators and subsequently seriously considering enacting crisis standards of care and implementing New York State Ventilator Allocation Guidelines (NYVAG). However, there is little evidence as to how NYVAG would perform if implemented.

Objectives

To evaluate the performance and potential improvement of NYVAG during a surge of patients with respect to the length of rationing, overall mortality, and worsening health disparities.

Design, Setting, and Participants

This cohort study included intubated patients in a single health system in New York City from March through July 2020. A total of 20 000 simulations were conducted of ventilator triage (10 000 following NYVAG and 10 000 following a proposed improved NYVAG) during a crisis period, defined as the point at which the prepandemic ventilator supply was 95% utilized.

Exposures

The NYVAG protocol for triage ventilators.

Main Outcomes and Measures

Comparison of observed survival rates with simulations of scenarios requiring NYVAG ventilator rationing.

Results

The total cohort included 1671 patients; of these, 674 intubated patients (mean [SD] age, 63.7 [13.8] years; 465 male [69.9%]) were included in the crisis period, with 571 (84.7%) testing positive for COVID-19. Simulated ventilator rationing occurred for 163.9 patients over 15.0 days, 44.4% (95% CI, 38.3%-50.0%) of whom would have survived if provided a ventilator while only 34.8% (95% CI, 28.5%-40.0%) of those newly intubated patients receiving a reallocated ventilator survived. While triage categorization at the time of intubation exhibited partial prognostic differentiation, 94.8% of all ventilator rationing occurred after a time trial. Within this subset, 43.1% were intubated for 7 or more days with a favorable SOFA score that had not improved. An estimated 60.6% of these patients would have survived if sustained on a ventilator. Revising triage subcategorization, proposed improved NYVAG, would have improved this alarming ventilator allocation inefficiency (25.3% [95% CI, 22.1%-28.4%] of those selected for ventilator rationing would have survived if provided a ventilator). NYVAG ventilator rationing did not exacerbate existing health disparities.

Conclusions and Relevance

In this cohort study of intubated patients experiencing simulated ventilator rationing during the apex of the New York City COVID-19 2020 surge, NYVAG diverted ventilators from patients with a higher chance of survival to those with a lower chance of survival. Future efforts should be focused on triage subcategorization, which improved this triage inefficiency, and ventilator rationing after a time trial, when most ventilator rationing occurred.

Influence of social deprivation index on in-hospital outcomes of COVID-19

While it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient's residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70-0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71-0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79-0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79-0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important.

The Disproportionate Impact of Coronavirus Disease 2019 (COVID-19) Pandemic on Healthcare-Associated Infections in Community Hospitals: Need for Expanding the Infectious Disease Workforce

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic had a considerable impact on US healthcare systems, straining hospital resources, staff, and operations. However, a comprehensive assessment of the impact on healthcare-associated infections (HAIs) across different hospitals with varying level of infectious disease (ID) physician expertise, resources, and infrastructure is lacking.

METHODS

This retrospective longitudinal multicenter cohort study included central-line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), Clostridioides difficile infections (CDIs), and ventilator-associated events (VAEs) from 53 hospitals (academic and community) in Southeastern United States from 1 January 2018 to 31 March 2021. Segmented negative binomial regression generalized estimating equations models estimated changes in monthly incidence rates in the baseline (01/2018-02/2020) compared to the pandemic period (03/2020-03/2021, further divided into three pandemic phases).

RESULTS

CLABSIs and VAEs increased by 24% and 34%, respectively, during the pandemic period. VAEs increased in all phases of the pandemic, while CLABSIs increased in later phases of the pandemic. CDI trend increased by 4.2% per month in the pandemic period. On stratifying the analysis by hospital characteristics, the impact of the pandemic on healthcare-associated infections was more significant in smaller sized and community hospitals. CAUTIs did not change significantly during the pandemic across all hospital types.

CONCLUSIONS

CLABSIs, VAEs, and CDIs increased significantly during the pandemic, especially in smaller community hospitals, most of which lack ID physician expertise. Future efforts should focus on better understanding challenges faced by community hospitals, strengthening the infection prevention infrastructure, and expanding the ID workforce, particularly to community hospitals.

How Common SOFA and Ventilator Time Trial Criteria Would Have Performed During the COVID-19 Pandemic: An Observational Simulated Cohort Study

OBJECTIVES

To evaluate how key aspects of New York State Ventilator Allocation Guidelines (NYSVAG)-Sequential Organ Failure Assessment score criteria and ventilator time trials -might perform with respect to the frequency of ventilator reallocation and survival to hospital discharge in a simulated cohort of coronavirus disease (COVID-19) patients.

METHODS

Single center retrospective observational and simulation cohort study of 884 critically ill COVID-19 patients undergoing ventilator allocation per NYSVAG.

RESULTS

In total, 742 patients (83.9%) would have had their ventilator reallocated during the 11-day observation period, 280 (37.7%) of whom would have otherwise survived to hospital discharge if provided with a ventilator. Only 65 (18.1%) of the observed surviving patients would have survived by NYSVAG. Extending ventilator time trials from 2 to 5 days resulted in a 49.2% increase in simulated survival to discharge.

CONCLUSIONS

In the setting of a protracted respiratory pandemic, implementation of NYSVAG or similar protocols could lead to a high degree of ventilator reallocation, including withdrawal from patients who might otherwise survive. Longer ventilator time trials might lead to improved survival for COVID-19 patients given their protracted respiratory failure. Further studies are needed to understand the survival of patients receiving reallocated ventilators to determine whether implementation of NYSVAG would improve overall survival.

Assessment of a Crisis Standards of Care Scoring System for Resource Prioritization and Estimated Excess Mortality by Race, Ethnicity, and Socially Vulnerable Area During a Regional Surge in COVID-19

IMPORTANCE

Crisis standards of care (CSOC) scores designed to allocate scarce resources during the COVID-19 pandemic could exacerbate racial disparities in health care.

OBJECTIVE

To analyze the association of a CSOC scoring system with resource prioritization and estimated excess mortality by race, ethnicity, and residence in a socially vulnerable area.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort analysis included adult patients in the intensive care unit during a regional COVID-19 surge from April 13 to May 22, 2020, at 6 hospitals in a health care network in greater Boston, Massachusetts. Participants were scored by acute severity of illness using the Sequential Organ Failure Assessment score and chronic severity of illness using comorbidity and life expectancy scores, and only participants with complete scores were included. The score was ordinal, with cutoff points suggested by the Massachusetts guidelines.

EXPOSURES

Race, ethnicity, Social Vulnerability Index.

MAIN OUTCOMES AND MEASURES

The primary outcome was proportion of patients in the lowest priority score category stratified by self-reported race. Secondary outcomes were discrimination and calibration of the score overall and by race, ethnicity, and neighborhood Social Vulnerability Index. Projected excess deaths were modeled by race, using the priority scoring system and a random lottery.

RESULTS

Of 608 patients in the intensive care unit during the study period, 498 had complete data and were included in the analysis; this population had a median (IQR) age of 67 (56-75) years, 191 (38.4%) female participants, 79 (15.9%) Black participants, and 225 patients (45.7%) with COVID-19. The area under the receiver operating characteristic curve for the priority score was 0.79 and was similar across racial groups. Black patients were more likely than others to be in the lowest priority group (12 [15.2%] vs 34 [8.1%]; P = .046). In an exploratory simulation model using the score for ventilator allocation, with only those in the highest priority group receiving ventilators, there were 43.9% excess deaths among Black patients (18 of 41 patients) and 28.6% (58 of 203 patients among all others (P = .05); when the highest and intermediate priority groups received ventilators, there were 4.9% (2 of 41 patients) excess deaths among Black patients and 3.0% (6 of 203) among all others (P = .53). A random lottery resulted in more excess deaths than the score.

CONCLUSIONS AND RELEVANCE

In this study, a CSOC priority score resulted in lower prioritization of Black patients to receive scarce resources. A model using a random lottery resulted in more estimated excess deaths overall without improving equity by race. CSOC policies must be evaluated for their potential association with racial disparities in health care.

Promoting equity with a multi-principle framework to allocate scarce ICU resources

We wholeheartedly agree with Schmidt and colleagues' efforts to promote equity in intensive care unit (ICU) triage. We also take issue with their characterisation of the New Jersey (NJ) allocation framework for ICU beds and ventilators, which is modelled after the multi-principle allocation framework we developed early in the pandemic. They characterise it as a two-criterion allocation framework and claim-without evidence-that it will 'compound disadvantage for black patients'. However, the NJ triage framework-like the model allocation policy we developed-actually contains four allocation criteria: the two criteria that the authors mentioned (chances for survival and near-term prognosis) and two criteria that they failed to mention which we included to promote equity: giving priority to frontline essential workers and giving priority to younger patients. These omissions are problematic both for reasons of factual accuracy and because the two criteria they failed to acknowledge would likely mitigate rather than exacerbate racial disparities during triage.

Sequential organ failure assessment, ventilator rationing and evolving triage guidance: new evidence underlines the need to recognise and revise, unjust allocation frameworks

We respond to recent comments on our proposal to improve justice in ventilator triage, in which we used as an example New Jersey's (NJ) publicly available and legally binding Directive Number 2020-03. We agree with Bernard Lo and Doug White that equity implications of triage frameworks should be continually reassessed, which is why we offered six concrete options for improvement, and called for monitoring the consequences of adopted triage models. We disagree with their assessment that we mis-characterised their Model Guidance, as included in the NJ Directive, in ways that undermine our conclusions. They suggest we erroneously described their model as a two-criterion allocation framework; that recognising other operant criterion reveals it 'likely mitigate[s] rather than exacerbate[s] racial disparities during triage', and allege that concerns about inequitable outcomes are 'without evidence'. We highlight two major studies robustly demonstrating why concerns about disparate outcomes are justified. We also show that White and Lo seek to retrospectively-and counterfactually-correct the version of the Model Guideline included in the NJ Directive. However, as our facsimile reproductions show, neither the alleged four-criteria form, nor other key changes, such as dropping the Sequential Organ Failure Assessment score, are found in the Directive. These points matter because (1) our conclusions hence stand, (2) because the public version of the Model Guidance had not been updated to reduce the risk of inequitable outcomes until June 2021 and (3) NJ's Directive still does not reflect these revisions, and, hence, represents a less equitable version, as acknowledged by its authors. We comment on broader policy implications and call for ways of ensuring accurate, transparent and timely updates for users of high-stakes guidelines.

Ethics of Extracorporeal Membrane Oxygenation under Conventional and Crisis Standards of Care

Extracorporeal membrane oxygenation (ECMO) is a form of life support for cardiac and/or pulmonary failure with unique ethical challenges compared to other forms of life support. Ethical challenges with ECMO exist when conventional standards of care apply, and are exacerbated during periods of absolute ECMO scarcity when "crisis standards of care" are instituted. When conventional standards of care apply, we propose that it is ethically permissible to withhold placing patients on ECMO for reasons of technical futility or when patients have terminal, short-term prognoses that are untreatable by ECMO. Under crisis standards of care, it is ethically permissible to broaden exclusionary criteria to also withhold ECMO from patients who have a low likelihood of recovery, to maximize the overall number of lives saved. Unilateral withdrawal of ECMO against a patient's preferences is unethical under conventional standards of care, but is ethical under crisis standards of care to increase access to ECMO to others in society. ECMO should only be rationed when true scarcity exists, and allocation protocols should be transparent to the public. When rationing must occur under crisis standards of care, it is imperative that oversight bodies assess for inequities in the allocation of ECMO and make frequent changes to improve any inequities.

Access to Palliative Care Consultation for Hospitalized Adults with COVID-19 in an Urban Health System: Were There Disparities at the Peak of the Pandemic?

Background: Palliative care (PC) services expanded rapidly to meet the needs of coronavirus disease 2019 (COVID-19) patients, yet little is known about which patients were referred for PC consultation during the pandemic. Objective: Examine factors predictive of PC consultation for COVID-19 patients. Design: Retrospective cohort study of COVID-19 patients discharged from four hospitals (March 1-June 30, 2020). Exposures: Patient demographic, socioeconomic, and clinical factors and hospital-level characteristics. Outcome Measurement: Inpatient PC consultation. Results: Of 4319 hospitalized COVID-19 patients, 581 (14%) received PC consultation. Increasing age, serious illness (cancer, chronic obstructive pulmonary disease, and dementia), greater illness severity, and admission to the quaternary hospital were associated with receipt of PC consultation. There was no association between PC consultation and race/ethnicity, household crowding, insurance status, or hospital-factors, including inpatient, emergency department, and intensive care unit census. Conclusions: Although site variation existed, the highest acuity patients were most likely to receive PC consultation without racial/ethnic or socioeconomic disparities.

Protocol to assess performance of crisis standards of care guidelines for clinical triage

During the COVID-19 pandemic, US states developed Crisis Standards of Care (CSC) algorithms to triage allocation of scarce resources to maximize population-wide benefit. While CSC algorithms were developed by ethical debate, this protocol guides their quantitative assessment. For CSC algorithms, this protocol addresses (1) adapting algorithms for empirical study, (2) quantifying predictive accuracy, and (3) simulating clinical decision-making. This protocol provides a framework for healthcare systems and governments to test the performance of CSC algorithms to ensure they meet their stated ethical goals.

For complete details on the use and execution of this protocol, please refer to Jezmir et al. (2021).

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Scoring with Crisis Standards of Care (CSC) triage algorithms

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Assessing the predictive accuracy of triage algorithms

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Simulating clinical decision-making by triage algorithms

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Troubleshooting disease severity, comorbidity scoring, and ties

Predictive Value of Sequential Organ Failure Assessment Score across Patients with and without COVID-19 Infection

Rationale

Sequential organ failure assessment (SOFA) scores are commonly used in crisis standards of care policies to assist in resource allocation. The relative predictive value of SOFA by coronavirus disease (COVID-19) infection status and among racial and ethnic subgroups within patients infected with COVID-19 is unknown.

Objectives

To evaluate the accuracy and calibration of SOFA in predicting hospital mortality by COVID-19 infection status and across racial and ethnic subgroups.

Methods

We performed a retrospective cohort study of adult admissions to the University of Miami Hospital and Clinics inpatient wards (July 1, 2020–April 1, 2021). We primarily considered maximum SOFA within 48 hours of hospitalization. We assessed accuracy using the area under the receiver operating characteristic curve (AUROC) and created calibration belts. Considered subgroups were defined by COVID-19 infection status (by severe acute respiratory syndrome coronavirus 2 polymerase chain reaction testing) and prevalent racial and ethnic minorities. Comparisons across subgroups were made with DeLong testing for discriminative accuracy and visualization of calibration belts.

Results

Our primary cohort consisted of 20,045 hospitalizations, of which 1,894 (9.5%) were COVID-19 positive. SOFA was similarly accurate for COVID-19–positive (AUROC, 0.835) and COVID-19–negative (AUROC, 0.810; P = 0.15) admissions but was slightly better calibrated in patients who were positive for COVID-19. For those with critical illness, maximum SOFA score accuracy at critical illness onset also did not differ by COVID-19 status (AUROC, COVID-19 positive vs. negative: intensive care unit admissions, 0.751 vs. 0.775; P = 0.46; mechanically ventilated, 0.713 vs. 0.792, P = 0.13), and calibration was again better for patients positive for COVID-19. Among patients with COVID-19, SOFA accuracy was similar between the non-Hispanic White population (AUROC, 0.894) and racial and ethnic minorities (Hispanic White population: AUROC, 0.824 [P vs. non-Hispanic White = 0.05]; non-Hispanic Black population: AUROC, 0.800 [P = 0.12]; Hispanic Black population: AUROC, 0.948 [P = 0.31]). This similar accuracy was also found for those without COVID-19 (non-Hispanic White population: AUROC, 0.829; Hispanic White population: AUROC, 0.811 [P = 0.37]; Hispanic Black population: AUROC, 0.828 [P = 0.97]; non-Hispanic Black population: AUROC, 0.867 [P = 0.46]). SOFA was well calibrated for all racial and ethnic groups with COVID-19 but estimated mortality more variably and performed less well across races and ethnicities without COVID-19.

Conclusions

SOFA accuracy does not differ by COVID-19 status and is similar among racial and ethnic groups both with and without COVID-19. Calibration is better for COVID-19–infected patients and, among those without COVID-19, varies by race and ethnicity.

Variation in COVID-19 Resource Allocation Protocols and Potential Implementation in the Chicago Metropolitan Area

BACKGROUND

Scarce resource allocation policies vary across the United States. Little is known about regional variation in resource allocation protocols and variation in their application. We sought to evaluate how Covid-19 scarce resource allocation policies vary throughout the Chicago metropolitan area and whether there are differences in policy application within hospitals when prioritizing hypothetical patients who need critical care resources.

METHODS

Two cross-sectional surveys were distributed to Chicago metropolitan area hospital representatives and triage officers. Survey responses and categorical variables are described by frequency of occurrence. Intra- and interhospital variation in ranking of hypothetical patients was assessed using Fleiss's Kappa coefficients.

RESULTS

Eight Chicago-area hospitals responded to the survey assessing scarce resource allocation protocols (N = 8/18, response rate 44%). For hospitals willing to describe their ventilator allocation protocol (N = 7), most used the sequential organ failure assessment (SOFA) score (N = 6/7, 86%) and medical comorbidities (N = 4/7, 57%) for initial scoring of patients. A majority gave priority in initial scoring to pre-defined groups (N = 5/7, 71%), all discussed withdrawal of mechanical ventilation for adult patients (N = 7/7, 100%), and a minority had exclusion criteria (N = 3/7, 43%). Forty-nine triage officers from nine hospitals responded to the second survey (N = 9/10 hospitals, response rate 90%). Their rankings of hypothetical patients showed only slight agreement amongst all hospitals (Kappa 0.158) and fair agreement within two hospitals with the most respondents (Kappa 0.21 and 0.25). Almost half used tiebreakers to rank patients (N = 23/49, 47%).

CONCLUSIONS

Although most respondents from Chicago-area hospitals described policies for resource allocation during the COVID-19 pandemic, the substance and application of these protocols varied. There was little agreement when prioritizing hypothetical patients to receive scarce resources, even among people from the same hospital. Variations in resource allocation protocols and their application could lead to inequitable distribution of resources, further exacerbating community distrust and disparities in health.

Supplemental data for this article is available online at https://doi.org/10.1080/23294515.2021.1983667.

Ventilator Allocation Protocols: Sophisticated Bioethics for an Unworkable Strategy

I was a member of the Massachusetts advisory working group that wrote the Commonwealth's crisis standards of care guidance for the Covid‐19 pandemic, and I was proud of the work we did, thinking carefully about whether age should matter and whether priority should be given to essential workers if there was a scarcity of medical resources, about whether protocols should address issues of structural racism, and so forth. But as a critical care physician, I have concluded that, no matter how sophisticated the ethical analysis, the fundamental approach we proposed was flawed and virtually impossible to implement. All the existing allocation protocols that states developed are based on the assumption that clinicians will be faced with the task of selecting which patients will be offered a ventilator from among a population of patients who are each in need of one. The protocols then assign patients a priority category, and the protocols specify “tie‐breaking” criteria to be used when necessary. The problem with this approach for ventilator allocation is that it has no relationship whatsoever to what happens in the real world.

Structural Inequities, Fair Opportunity, and the Allocation of Scarce ICU Resources

The September-October 2021 issue of the Hastings Center Report highlights the important topic of allocating scarce critical care resources during the Covid-19 pandemic. The article by Alex Rajczi and colleagues urges that policy-makers use public reasoning, not private reasoning, when developing triage policies. We completely agree. We show how the allocation framework we developed as private scholars, the "Pittsburgh framework," has been supported by public reasoning. The article by MaryKatherine Gaurke and colleagues criticizes rationing based on maximizing life-years saved and mistakenly claims that our framework recommended this approach. We explain that our framework never contained such a criterion but instead included a more limited consideration of near-term prognosis. In December 2020, in response to emerging data and important criticisms, we modified our framework to further strengthen equity. We are committed to improving allocation guidelines during crisis standards of care through reflective discussions and debates.

Accuracy of the Sequential Organ Failure Assessment Score for In-Hospital Mortality by Race and Relevance to Crisis Standards of Care

IMPORTANCE

Crisis Standards of Care (CSC) are guidelines for rationing health care resources during public health emergencies. The CSC adopted by US states ration intensive care unit (ICU) admission using the Sequential Organ Failure Assessment (SOFA) score, which is used to compare expected in-hospital mortality among eligible patients. However, it is unknown if Black and White patients with equivalent SOFA scores have equivalent in-hospital mortality.

OBJECTIVE

To investigate whether reliance on SOFA is associated with bias against Black patients in CSC.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted using data from the eICU Collaborative Research Database of patients admitted to 233 US ICUs in 2014 to 2015. Included individuals were Black and White adult patients in the ICU, who were followed up to hospital discharge. Data were analyzed from May 2020 through April 2021.

EXPOSURE

SOFA scores at ICU admission.

MAIN OUTCOMES AND MEASURES

Hierarchical logistic regression with hospital fixed effects was used to measure the interaction between race and SOFA as a factor associated with in-hospital mortality, as well as the odds of death among Black and White patients with equivalent priority for resource allocation according to the SOFA-based ranking rules of 3 statewide CSC (denoted A, B, and C) under shortage conditions that were severe (ie, only patients with the highest priority would be eligible for allocation), intermediate (ie, patients in the highest 2 tiers would be eligible for allocation), or low (ie, only patients with the lowest priority would be at risk of exclusion).

RESULTS

Among 111 885 ICU encounters representing 95 549 patients, there were 16 688 encounters with Black patients (14.9%) and 51 464 (46.0%) encounters with women and the mean (SD) age was 63.3 (16.9) years. The median (interquartile range) SOFA score was not statistically significantly different between Black and White patients (4 [2-6] for both groups; P = .19), but mortality was lower among Black individuals compared with White individuals with equivalent SOFA scores (odds ratio [OR], 0.98; 95% CI, 0.97-0.99; P < .001). This was associated with lower mortality among Black patients compared with White patients prioritized for resource allocation in 3 CSC under shortage conditions that were severe (system A: OR, 0.65; 95% CI, 0.58-0.74; P < .001; system B: OR, 0.70; 95% CI, 0.64-0.78; P < .001; system C: OR, 0.73; 95% CI, 0.67-0.80; P < .001), intermediate (system A: OR, 0.73; 95% CI, 0.67-0.80; P < .001; system B: OR, 0.83; 95% CI, 0.77-0.89; P < .001; system C: OR, 0.82; 95% CI, 0.77-0.89; P < .001), and low (system A: OR, 0.83; 95% CI, 0.77-0.89; P < .001; system C: OR, 0.86; 95% CI, 0.81-0.92; P < .001; not applicable for system B, which had fewer tiers). When SOFA-based ranking rules were adjusted for Black patients to simulate equitable allocation based on observed mortality, the proportion upgraded to higher priority ranged from 379 Black patient encounters (2.3%) in low shortage conditions to 2601 Black patient encounters (15.6%) in severe shortage conditions.

CONCLUSIONS AND RELEVANCE

This study found that SOFA scores were associated with overestimated mortality among Black patients compared with White patients, and this was associated with a structural disadvantage for Black patients in CSC allocation systems. These findings suggest that guidelines should be revised to correct this inequity and alternative methods should be developed for more equitable triage.