This New England Journal of Medicine article argues that “color-blind” crisis standards of care (CSC) plans fail to account for disproportionate burdens on communities of color and risk exacerbating existing health inequities.

Existing state CSC plans often explicitly reject consideration of race or ethnicity, but “color-blind” processes can result in discrimination and exacerbation of existing inequities by denying the experience of people of color in a highly racialized society. Most CSC plans emphasize saving the most lives or life-years by applying prioritization criteria that rely on factors such as SOFA score, comorbid conditions, and predicted near-term mortality. However, due to existing health inequities, the authors argue that communities of color may be systematically deprioritized by such systems, despite the appearance of fairness.

Communities of color appear to be suffering disproportionate impacts from COVID-19 based on limited existing data, which the authors note has so far failed to adequately capture demographic information. This disparate impact is the result of existing inequalities and inequities that place some populations, notably Black and Latinx Americans, at greater risk of contracting COVID-19 and of suffering worse disease outcomes. Communities of color are more likely to have comorbidities due to a legacy of structural racism and inequality that has resulted in unequal health care access and inequities in social determinants of health such as housing, education, and employment. The impact of these factors on baseline health status and life expectancy would result in disadvantages under common prioritization criteria.

The authors recommend that CSC plans be modified to address problematic criteria. They suggest that existing predictive scoring systems such as SOFA score may fail to accurately predict short-term survival and misrepresent quality of life and that CSC plans should therefore apply limitations on the use of such systems and explore alternative systems that integrate concepts of equity. They also suggest that triage officers and appeals committee members should be required to have expertise in equity and come from diverse backgrounds or, at a minimum, that facility-level training be designed with input from clinicians well versed in equity issues.

This Health Affairs article further explores the potential for “fair” systems of allocating scarce resources to allow unconscious bias and existing disparities to penalize persons of color and persons with disabilities. The article offers several principles to ensure unbiased allocation based on lessons from health care prioritization managed by Oregon’s Health Evidence Review Commission (HERC).

Existing guidelines to support fair decision making in scarce resource allocation typically specify objective triage criteria and scoring systems, as well as explicitly rejecting consideration of “social value” or personal characteristics such as race/ethnicity or disability status. These guidelines generally prioritize allocations on the basis of maximizing the utility of limited resources to save the most lives, which the authors argue typically results in favoring patients in better health and therefore penalizing groups with higher illness burden, including racial/ethnic minorities and persons with disabilities. The authors also note that much research supports the influence of unconscious bias on judgment, which may result in unconscious devaluation of a person negatively influencing judgment of prognosis. Existing health care disparities may also result in distrust of the health care system among disadvantaged groups, resulting in delay in seeking care and placing them at higher risk.

The article offers principles based on lessons from health prioritization in Oregon as managed by the HERC to outline an approach to instilling trust and protecting against bias and the perception of bias in rationing care. Specifically, the article recommends:

• Establishing a scarce resource allocation committee for each health care institution or system that uses set policies based on clear principles and evidence to avoid ad hoc, subjective judgments.
• Explicitly considering the potential for even objective criteria to exacerbate existing inequities when developing allocation guidelines and incorporating effects on vulnerable populations into decision-making. For example, this may include using only acute physiologic parameters, rather than chronic comorbidities or functional limitations in assigning priority scores.
• Incorporating public values into resource allocation guidelines with input from diverse constituencies.
• Using explicit and transparent resource allocation criteria to increase accountability and reduce likelihood that decision will be perceived as unfair or arbitrary.
• Carrying out resource allocation guidelines through triage officers or teams not involved in front-line care of individual patients.
• Making resource allocation committee members visible and accessible.
• Stratifying COVID-19 tracking data by demographic characteristics and creating dashboards to determine, in real time, if disparities are occurring.

The principles are consistent with most existing guidance, but offer additional insights and strategies for preventing the influence of both conscious and unconscious bias on resource allocation decision-making.