Validation of a Crisis Standards of Care Model for Prioritization of Limited Resources During the Coronavirus Disease 2019 Crisis in an Urban, Safety-Net, Academic Medical Center

Albert Nadjarian, MD, MPH; Jessica LeClair, BS; Taylor F. Mahoney, MA; Eric H. Awtry, MD, FACC; Jasvinder S. Bhatia, MD; Lisa B. Caruso, MD, MPH; Alexis Clay, MD; David Greer, MD, MA; Karan S. Hingorani, MD, PhD; L. F. B. Horta, MD; Michel Ibrahim, MD; Michael H. Ieong, MD; Thea James, MD; Matthew H. Kulke, MD; Remington Lim, BA; Robert C. Lowe, MD; James M. Moses, MD; Jaime Murphy, MD; Ala Nozari, MD; Anuj D. Patel, MD; Brent Silver, MD; Arthur C. Theodore, MD; Ryan Shufei Wang, MD; Ellen Weinstein, JD; Stephen A. Wilson, MD, MPH, FAAFP; Anna M. Cervantes-Arslanian, MD

Disclosures

Crit Care Med. 2021;49(10):1739-1748. 

In This Article

Methods

Ethics

The study protocol was approved by the Boston University Medical Campus Institutional Review Board, Approval Number H-40336.

Setting

BMC is a 514-bed urban academic medical center and the largest safety-net hospital in New England. Over 75% of visits are from underserved populations such as low income, homeless, and the elderly, who rely on government payors such as Medicaid, the Health Safety Net, and Medicare for insurance coverage.[7] These patients tend to have complex medical and social histories, and approximately one-third of patient encounters are conducted in a language other than English.

Patient Identification

Adult (18 yr and older) patients were identified through BMC's electronic medical record system for the first 15 days of both April 2015 and April 2019. The study period was chosen to reflect the peak of new COVID cases in the state of Massachusetts (April 2020). All patients admitted to the medical, surgical, neurologic, or cardiac ICUs were included.

Data Collection and Variables

Variables collected included age, sex, race, length of stay, admission diagnosis, as well as date and cause of death when applicable. Triage scoring was performed via chart review by study physicians and verified by subspecialty physicians for complex scoring categories (e.g., neurodegenerative conditions, congestive heart failure [CHF], chronic lung disease [CLD]). Points were scored for chronic comorbid conditions at the time of ICU admission using the CSC point allocation framework (Table 1). These conditions included end-stage renal disease (ESRD) in patients older than 75 years, CHF, cirrhosis—ineligible for liver transplant—metastatic cancer, CLD, and neurodegenerative conditions (Supplemental Table 1, http://links.lww.com/CCM/G513). Any patient with ESRD on renal replacement therapy and greater than 75 years old scored 2 points. Patients with cirrhosis and concurrent laboratory values or clinical features suggestive of severe disease scored 2 points, and those with a Model for End-Stage Liver Disease (MELD) score greater than 20 scored 4 points. Patients with metastatic cancer scored 2 or 4 points, depending on the prognostication of cancer type as well as hospice eligibility. Patients with CHF scored 2 or 4 points depending on New York Heart Association class and concurrent clinical symptoms suggestive of decompensation. Patients with neurodegenerative conditions scored 2 points based on deteriorating cognitive impairment with extensive functional decline, and 4 points if such conditions were associated with complete functional dependence and signs of end-stage dementia. Criteria for those with CLD were most extensive and were subdivided based on type of condition, with criteria for each condition derived from prior literature and other clinical features suggestive of severe decompensation.

Data Analysis/Statistical Methods

Descriptive statistics of demographic and clinical variables were generated separately for patients with and without underlying conditions. Bivariate associations were calculated between these variables and whether or not the patient had an underlying condition. chi-square or Fisher Exact tests were used to compare categorical variables, and two-sample t tests were used to compare continuous variables. SAS 9.4 (SAS Institute Inc., Cary, NC) was used to perform all statistical analyses.

The date of admission and date of death were used to compute 1- and 5-year mortality. Patients who were admitted in 2019 were excluded from the 5-year mortality calculation. We defined any patients as lost to follow-up if they did not have 1- or 5-year follow-up encounters (depending on date of ICU admission). If a patient was lost to follow-up, they were classified as alive. For deceased patients with a missing year of death, the discharge date was used. Similarly, if a patient was discharged to hospice, they were classified as deceased with the date of death considered the date of hospital discharge when not otherwise available.

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