Outcomes Among Patients Discharged From Busy Intensive Care Units

William Penn University, Filadelfia, Pennsylvania, United States
Annals of internal medicine (Impact Factor: 17.81). 10/2013; 159(7):447-455. DOI: 10.7326/0003-4819-159-7-201310010-00004
Source: PubMed


Chinese translation BACKGROUND: Strains on the capacities of intensive care units (ICUs) may influence the quality of ICU-to-floor transitions.
To determine how 3 metrics of ICU capacity strain (ICU census, new admissions, and average acuity) measured on days of patient discharges influence ICU length of stay (LOS) and post-ICU discharge outcomes.
Retrospective cohort study from 2001 to 2008.
155 ICUs in the United States.
200 730 adults discharged from ICUs to hospital floors.
Associations between ICU capacity strain metrics and discharged patient ICU LOS, 72-hour ICU readmissions, subsequent in-hospital death, post-ICU discharge LOS, and hospital discharge destination.
Increases in the 3 strain variables on the days of ICU discharge were associated with shorter preceding ICU LOS (all P < 0.001) and increased odds of ICU readmissions (all P < 0.050). Going from the 5th to 95th percentiles of strain was associated with a 6.3-hour reduction in ICU LOS (95% CI, 5.3 to 7.3 hours) and a 1.0% increase in the odds of ICU readmission (CI, 0.6% to 1.5%). No strain variable was associated with increased odds of subsequent death, reduced odds of being discharged home from the hospital, or longer total hospital LOS.
Long-term outcomes could not be measured.
When ICUs are strained, triage decisions seem to be affected such that patients are discharged from the ICU more quickly and, perhaps consequentially, have slightly greater odds of being readmitted to the ICU. However, short-term patient outcomes are unaffected. These results suggest that bed availability pressures may encourage physicians to discharge patients from the ICU more efficiently and that ICU readmissions are unlikely to be causally related to patient outcomes.
Agency for Healthcare Research and Quality; National Heart, Lung, and Blood Institute; and Society of Critical Care Medicine.

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    • "When ICUs are strained, triage decisions seem to be affected such that patients are discharged or transferred from the ICU more quickly and, perhaps consequently, have slightly greater odds of being readmitted to the ICU. However, short-term patient outcomes are unaffected, suggesting that bed availability pressures may encourage intensivists to discharge patients from ICU more efficiently [27]. Our readmission rate of 3.1% falls into rates reported previously, which ranged from 0.9% to 19% [28, 29]. "
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    ABSTRACT: Background The demand for specialized medical services such as critical care often exceeds availability, thus rationing of intensive care unit (ICU) beds commonly leads to difficult triage decisions. Many factors can play a role in the decision to admit a patient to the ICU, including severity of illness and the need for specific treatments limited to these units. Although triage decisions would be based solely on patient and institutional level factors, it is likely that intensivists make different decisions when there are fewer ICU beds available. The objective of this study is to evaluate the characteristics of patients referred for ICU admission during times of limited beds availability. Methods A single center, prospective, observational study was conducted among consecutive patients in whom an evaluation for ICU admission was requested during times of ICU overcrowding, which comprised the months of April and May 2014. Results A total of 95 patients were evaluated for possible ICU admission during the study period. Their mean APACHE-II score was 16.8 (median 16, range 3 - 36). Sixty-four patients (67.4%) were accepted to ICU, 18 patients (18.9%) were triaged to SDU, and 13 patients (13.7%) were admitted to hospital wards. ICU had no beds available 24 times (39.3%) during the study period, and in 39 opportunities (63.9%) only one bed was available. Twenty-four patients (25.3%) were evaluated when there were no available beds, and eight of those patients (33%) were admitted to ICU. A total of 17 patients (17.9%) died in the hospital, and 15 (23.4%) expired in ICU. Conclusion ICU beds are a scarce resource for which demand periodically exceeds supply, raising concerns about mechanisms for resource allocation during times of limited beds availability. At our institution, triage decisions were not related to the number of available beds in ICU, age, or gender. A linear correlation was observed between severity of illness, expressed by APACHE-II scores, and the likelihood of being admitted to ICU. Alternative locations outside the ICU in which care for critically ill patients could be delivered should be considered during times of extreme ICU-bed shortage.
    Journal of Clinical Medicine Research 12/2014; 6(6):463-8. DOI:10.14740/jocmr1939w
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    • "Unfortunately, there are no valid tools systematically used to determine the ideal timing for ICU discharge or for predicting ICU readmission [9]. In fact, recent data suggest that the timing of transfer from the ICU to a less intensively monitored setting may be strongly influenced by metrics of ICU capacity strain such as ICU census, bed occupancy, or staff workload [10] [11] [12]. Therefore, unplanned ICU readmission has increasingly been regarded as an indicator of quality of ICU care [13]. "
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    ABSTRACT: Purpose Intensive care unit (ICU) readmission negatively impacts patients’ outcomes. We aimed to characterize and determine risk factors for ICU readmission within the initial hospital stay after liver transplant (LT). Materials and Methods The reference cohort included 369 LT recipients from a Canadian center between 2005 and 2012. One control was randomly selected per each case of ICU readmission within the initial hospital stay following LT. Survival analysis used the Kaplan-Meier method. Associations were studied by conditional logistic regression. Results Fifty-two (14%) LT recipients were readmitted to the ICU within the initial hospital stay after LT; they had longer first hospital stay (P < 0.001) and lower 1-month to 2-year cumulative survival (P < 0.001). Respiratory failure was the major cause of ICU readmission (61%). Respiratory rate at discharge from the first ICU stay following LT was an independent risk factor for ICU readmission (OR = 1.24). The cutoff point > 20 breaths/min prognosticated ICU readmission with a specificity of 90% and a positive predictive value of 80%. Conclusions ICU readmission within the initial hospital stay following LT negatively impacts LT recipients’ outcomes. Monitoring respiratory rate at discharge from the first ICU stay after LT is important to prevent readmission.
    Journal of Critical Care 10/2014; 29(5). DOI:10.1016/j.jcrc.2014.03.038 · 2.00 Impact Factor
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    ABSTRACT: Rationale: The aging population may strain intensive care unit (ICU) capacity and adversely affect patient outcomes. Existing fluctuations in demand for ICU care offer an opportunity to explore such relationships. Objectives: To determine whether transient increases in ICU strain influence patient mortality, and identify characteristics of ICUs that are resilient to surges in capacity strain. Methods: Retrospective cohort study of 264,401 patients admitted to 155 U.S. ICUs from 2001-2008. We used logistic regression to examine relationships of measures of ICU strain (census, average acuity, and proportion of new admissions) near the time of ICU admission with mortality. Measurements and Main Results: 36,465 (14%) patients died in the hospital. ICU census on the day of a patient's admission was associated with increased mortality (OR: 1.02 per SD-unit increase (95% CI: 1.00, 1.03)). This effect was greater among ICUs employing closed (OR: 1.07 (95% CI: 1.02, 1.12)) versus open (OR: 1.01 (95% CI: 0.99, 1.03)) physician staffing models (interaction p-value=0.02). The relationship between census and mortality was stronger when the census was comprised of higher acuity patients (interaction p-value<0.01). Averaging strain over the first three days of patients' ICU stays yielded similar results except that the proportion of new admissions was now also associated with mortality (OR: 1.04 for each 10% increase (95% CI: 1.02, 1.06)). Conclusions: Several sources of ICU strain are associated with small but potentially important increases in patient mortality, particularly in ICUs employing closed staffing models. Although closed ICUs may promote favorable outcomes under static conditions, they are susceptible to being overwhelmed by patient influxes.
    American Journal of Respiratory and Critical Care Medicine 08/2013; 188(7). DOI:10.1164/rccm.201304-0622OC · 13.00 Impact Factor
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