Dataset Information

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

ABSTRACT:

Importance

Significant concern has been raised that crisis standards of care policies aimed at guiding resource allocation may be biased against people based on race/ethnicity.

Objective

To evaluate whether unanticipated disparities by race or ethnicity arise from a single institution's resource allocation policy.

Design, setting, and participants

This cohort study included adults (aged ≥18 years) who were cared for on a coronavirus disease 2019 (COVID-19) ward or in a monitored unit requiring invasive or noninvasive ventilation or high-flow nasal cannula between May 26 and July 14, 2020, at 2 academic hospitals in Miami, Florida.

Exposures

Race (ie, White, Black, Asian, multiracial) and ethnicity (ie, non-Hispanic, Hispanic).

Main outcomes and measures

The primary outcome was based on a resource allocation priority score (range, 1-8, with 1 indicating highest and 8 indicating lowest priority) that was assigned daily based on both estimated short-term (using Sequential Organ Failure Assessment score) and longer-term (using comorbidities) mortality. There were 2 coprimary outcomes: maximum and minimum score for each patient over all eligible patient-days. Standard summary statistics were used to describe the cohort, and multivariable Poisson regression was used to identify associations of race and ethnicity with each outcome.

Results

The cohort consisted of 5613 patient-days of data from 1127 patients (median [interquartile range {IQR}] age, 62.7 [51.7-73.7]; 607 [53.9%] men). Of these, 711 (63.1%) were White patients, 323 (28.7%) were Black patients, 8 (0.7%) were Asian patients, and 31 (2.8%) were multiracial patients; 480 (42.6%) were non-Hispanic patients, and 611 (54.2%) were Hispanic patients. The median (IQR) maximum priority score for the cohort was 3 (1-4); the median (IQR) minimum score was 2 (1-3). After adjustment, there was no association of race with maximum priority score using White patients as the reference group (Black patients: incidence rate ratio [IRR], 1.00; 95% CI, 0.89-1.12; Asian patients: IRR, 0.95; 95% CI. 0.62-1.45; multiracial patients: IRR, 0.93; 95% CI, 0.72-1.19) or of ethnicity using non-Hispanic patients as the reference group (Hispanic patients: IRR, 0.98; 95% CI, 0.88-1.10); similarly, no association was found with minimum score for race, again with White patients as the reference group (Black patients: IRR, 1.01; 95% CI, 0.90-1.14; Asian patients: IRR, 0.96; 95% CI, 0.62-1.49; multiracial patients: IRR, 0.81; 95% CI, 0.61-1.07) or ethnicity, again with non-Hispanic patients as the reference group (Hispanic patients: IRR, 1.00; 95% CI, 0.89-1.13).

Conclusions and relevance

In this cohort study of adult patients admitted to a COVID-19 unit at 2 US hospitals, there was no association of race or ethnicity with the priority score underpinning the resource allocation policy. Despite this finding, any policy to guide altered standards of care during a crisis should be monitored to ensure equitable distribution of resources.

SUBMITTER: Gershengorn HB

PROVIDER: S-EPMC7980099 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:To establish the feasibility of empirically testing crisis standards of care guidelines.DesignRetrospective single-center study.SettingICUs at a large academic medical center in the United States.SubjectsAdult, critically ill patients admitted to ICU, with 27 patients admitted for acute respiratory failure due to coronavirus disease 2019 and 37 patients admitted for diagnoses other than coronavirus disease 2019.InterventionsReview of electronic health record.Measurements and main resultsMany U.S. states released crisis standards of care guidelines with algorithms to allocate scarce healthcare resources during the coronavirus disease 2019 pandemic. We compared state guidelines that represent different approaches to incorporating disease severity and comorbidities: New York, Maryland, Pennsylvania, and Colorado. Following each algorithm, we calculated priority scores at the time of ICU admission for a cohort of patients with primary diagnoses of coronavirus disease 2019 and diseases other than coronavirus disease 2019 (n = 64). We assessed discrimination of 28-day mortality by area under the receiver operating characteristic curve. We simulated real-time decision-making by applying the triage algorithms to groups of two, five, or 10 patients. For prediction of 28-day mortality by priority scores, area under the receiver operating characteristic curve was 0.56, 0.49, 0.53, 0.66, and 0.69 for New York, Maryland, Pennsylvania, Colorado, and raw Sequential Organ Failure Assessment score algorithms, respectively. For groups of five patients, the percentage of decisions made without deferring to a lottery were 1%, 57%, 80%, 88%, and 95% for New York, Maryland, Pennsylvania, Colorado, and raw Sequential Organ Failure Assessment score algorithms, respectively. The percentage of decisions made without lottery was higher in the subcohort without coronavirus disease 2019, compared with the subcohort with coronavirus disease 2019.ConclusionsInclusion of comorbidities does not consistently improve an algorithm's performance in predicting 28-day mortality. Crisis standards of care algorithms result in a substantial percentage of tied priority scores. Crisis standards of care algorithms operate differently in cohorts with and without coronavirus disease 2019. This proof-of-principle study demonstrates the feasibility and importance of empirical testing of crisis standards of care guidelines to understand whether they meet their goals.

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