Disparities in Unilateral Do Not Resuscitate Order Use During the COVID-19 Pandemic

A unilateral do-not-resuscitate (UDNR) order is a do-not-resuscitate order placed using clinician judgment which does not require consent from a patient or surrogate. This study assessed how UDNR orders were used during the COVID-19 pandemic.

We analyzed a retrospective cross-sectional study of UDNR use at two academic medical centers between April 2020 and April 2021.

Two academic medical centers in the Chicago metropolitan area.

Patients admitted to an ICU between April 2020 and April 2021 who received vasopressor or inotropic medications to select for patients with high severity of illness.

None.

The 1,473 patients meeting inclusion criteria were 53% male, median age 64 (interquartile range, 54-73), and 38% died during admission or were discharged to hospice. Clinicians placed do not resuscitate orders for 41% of patients ( n = 604/1,473) and UDNR orders for 3% of patients ( n = 51/1,473). The absolute rate of UDNR orders was higher for patients who were primary Spanish speaking (10% Spanish vs 3% English; p ≤ 0.0001), were Hispanic or Latinx (7% Hispanic/Latinx vs 3% Black vs 2% White; p = 0.003), positive for COVID-19 (9% vs 3%; p ≤ 0.0001), or were intubated (5% vs 1%; p = 0.001). In the base multivariable logistic regression model including age, race/ethnicity, primary language spoken, and hospital location, Black race (adjusted odds ratio [aOR], 2.5; 95% CI, 1.3-4.9) and primary Spanish language (aOR, 4.4; 95% CI, 2.1-9.4) had higher odds of UDNR. After adjusting the base model for severity of illness, primary Spanish language remained associated with higher odds of UDNR order (aOR, 2.8; 95% CI, 1.7-4.7).

In this multihospital study, UDNR orders were used more often for primary Spanish-speaking patients during the COVID-19 pandemic, which may be related to communication barriers Spanish-speaking patients and families experience. Further study is needed to assess UDNR use across hospitals and enact interventions to improve potential disparities.