Objective: Rationing critical care beds occurs daily in the hospital setting. The objective of this systematic review was to examine the impact of rationing intensive care unit beds on the process and outcomes of care.
Data Source: We searched MEDLINE (1966–2003), CINAHL (1982–2003), Ovid Healthstar (1975–2003), EMBASE (1980–2003), Scisearch (1980–2003), the Cochrane Library, PUBMED related articles, personal files, abstract proceedings, and reference lists.
Study Selection: We included studies of seriously ill patients considered for admission to an intensive care unit bed during periods of reduced availability. We had no restriction on study design. Studies were excluded if rationing was performed using a scoring system or protocol and if cost-effectiveness was the only outcome.
Data Extraction: In duplicate and independently, we performed data abstraction and quality assessment.
Data Synthesis: We included ten observational studies. Hospital mortality rate was increased in patients refused intensive care unit admission vs. those admitted (odds ratio, 3.04; 95% confidence interval, 1.49–6.17). Factors associated with both intensive care unit bed refusal and increased mortality rate were increased age, severity of illness, and medical diagnosis. When intensive care unit beds were reduced, admitted patients were sicker, were less often admitted primarily for monitoring, and had a shorter intensive care unit length of stay, without other observed adverse effects.
Conclusions: These studies suggest that patients who are perceived not to benefit from critical care are more often refused intensive care unit admission; refusal is associated with an increased risk of hospital death. During times of decreased critical bed availability, several factors, including age, illness severity, and medical diagnosis, are used to triage patients, although their relative importance is uncertain. Critical care bed rationing requires further investigation.
From the Departments of Medicine (TS, DJC), Surgery (KK), and Clinical Epidemiology & Biostatistics (DJC), McMaster University, Hamilton, Ontario, Canada; Department of Medicine (JML), University of California, San Francisco, CA; and Department of Medicine (MML), Brown Medical School, Providence, RI.
Supported, in part, by the Canadian Institutes for Health Research (TS, DJC).