Dataset Information

Empirical Assessment of COVID-19 Crisis Standards of Care Guidelines.

ABSTRACT:

Background

Several states have released Crisis Standards of Care (CSC) guidelines for the allocation of scarce critical care resources. Most guidelines rely on Sequential Organ Failure Assessment (SOFA) scores to maximize lives saved, but states have adopted different stances on whether to maximize long-term outcomes (life-years saved) by accounting for patient comorbidities.

Methods

We compared 4 representative state guidelines with varying approaches to comorbidities and analyzed how CSC prioritization correlates with clinical outcomes. We included 27 laboratory-confirmed COVID-19 patients admitted to ICUs at Brigham and Women's Hospital from March 12 to April 3, 2020. We compared prioritization algorithms from New York, which assigns priority based on SOFA alone; Maryland, which uses SOFA plus severe comorbidities; Pennsylvania, which uses SOFA plus major and severe comorbidities; and Colorado, which uses SOFA plus a modified Charlson comorbidity index.

Results

In pairwise comparisons across all possible pairs, we found that state guidelines frequently resulted in tie-breakers based on age or lottery: New York 100% of the time (100% resolved by lottery), Pennsylvania 86% of the time (18% by lottery), Maryland 93% of the time (35% by lottery), and Colorado: 32% of the time (10% by lottery). The prioritization algorithm with the strongest correlation with 14-day outcomes was Colorado (r_s = -0.483. p = 0.011) followed by Maryland (r_s = -0.394, p =0.042), Pennsylvania (r_s = -0.382, p = 0.049), and New York (r_s = 0). An alternative model using raw SOFA scores alone was moderately correlated with outcomes (r_s = -0.448, p = 0.019).

Conclusions

State guidelines for scarce resource allocation frequently resulted in identical priority scores, requiring tie-breakers based on age or lottery. These findings suggest that state CSC guidelines should be further assessed empirically to understand whether they meet their goals.

SUBMITTER: Jezmir JL

PROVIDER: S-EPMC7273246 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

Empirical Assessment of COVID-19 Crisis Standards of Care Guidelines.

Jezmir Julia L JL Bharadwaj Maheetha M Kishore Sandeep P SP Winkler Marisa M Diephuis Bradford B Kim Edy Y EY Feldman William B WB

medRxiv : the preprint server for health sciences 20200519

<h4>Background</h4>Several states have released Crisis Standards of Care (CSC) guidelines for the allocation of scarce critical care resources. Most guidelines rely on Sequential Organ Failure Assessment (SOFA) scores to maximize lives saved, but states have adopted different stances on whether to maximize long-term outcomes (life-years saved) by accounting for patient comorbidities.<h4>Methods</h4>We compared 4 representative state guidelines with varying approaches to comorbidities and analyze ...[more]

PMID: 32511478

Similar Datasets

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.

Project description:ImportanceState crisis standards of care (CSC) guidelines in the US allocate scarce health care resources among patients. Anecdotal reports suggest that guidelines may disproportionately allocate resources away from patients with cancer, but no comprehensive evaluation has been performed.ObjectiveTo examine the implications of US state CSC guidelines for patients with cancer, including allocation methods, cancer-related categorical exclusions and deprioritizations, and provisions for blood products and palliative care.Design, setting, and participantsThis cross-sectional population-based analysis examined state-endorsed CSC guidelines published before May 20, 2020, that included health care resource allocation recommendations.Main outcomes and measuresGuideline publication before or within 120 days after the first documented US case of coronavirus disease 2019 (COVID-19), inclusion of cancer-related categorical exclusions and/or deprioritizations, provisions for blood products and/or palliative care, and associations between these outcomes and state-based cancer demographics.ResultsThirty-one states had health care resource allocation guidelines that met inclusion criteria, of which 17 had been published or updated since the first US case of COVID-19. States whose available hospital bed capacity was predicted to exceed 100% at 6 months (χ2 = 3.82; P = .05) or that had a National Cancer Institute-designated Comprehensive Cancer Center (CCC; χ2 = 6.21; P = .01) were more likely to have publicly available guidelines. The most frequent primary methods of prioritization were the Sequential Organ Failure Assessment score (27 states [87%]) and deprioritizing persons with worse long-term prognoses (22 states [71%]). Seventeen states' (55%) allocation methods included cancer-related deprioritizations, and 8 states (26%) included cancer-related categorical exclusions. The presence of an in-state CCC was associated with lower likelihood of cancer-related categorical exclusions (multivariable odds ratio, 0.06 [95% CI, 0.004-0.87]). Guidelines with disability rights statements were associated with specific provisions to allocate blood products (multivariable odds ratio, 7.44 [95% CI, 1.28-43.24). Both the presence of an in-state CCC and having an oncologist and/or palliative care specialist on the state CSC task force were associated with the inclusion of palliative care provisions.Conclusions and relevanceAmong states with CSC guidelines, most deprioritized some patients with cancer during resource allocation, and one-fourth categorically excluded them. The presence of an in-state CCC was associated with guideline availability, palliative care provisions, and lower odds of cancer-related exclusions. These data suggest that equitable state-level CSC considerations for patients with cancer benefit from the input of oncology stakeholders.

Project description:ImportanceSignificant concern has been raised that crisis standards of care policies aimed at guiding resource allocation may be biased against people based on race/ethnicity.ObjectiveTo evaluate whether unanticipated disparities by race or ethnicity arise from a single institution's resource allocation policy.Design, setting, and participantsThis 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.ExposuresRace (ie, White, Black, Asian, multiracial) and ethnicity (ie, non-Hispanic, Hispanic).Main outcomes and measuresThe 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.ResultsThe 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 relevanceIn 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.

Dataset Information

Empirical Assessment of COVID-19 Crisis Standards of Care Guidelines.

Background

Methods

Results

Conclusions

Publications

Empirical Assessment of COVID-19 Crisis Standards of Care Guidelines.

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