Outcomes Among Patients Discharged From Busy Intensive Care Units
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Chinese translation Background: Strains on the capacities of intensive care units (ICUs) may influence the quality of ICU-to-floor transitions. Objective: 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. Design: Retrospective cohort study from 2001 to 2008. Setting: 155 ICUs in the United States. Patients: 200 730 adults discharged from ICUs to hospital floors. Measurements: 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. Results: 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. Limitation: Long-term outcomes could not be measured. Conclusion: 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. Primary Funding Source: Agency for Healthcare Research and Quality; National Heart, Lung, and Blood Institute; and Society of Critical Care Medicine.Keywords:
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In Brief Rationale: Life and death triage decisions are made daily by intensive care unit physicians. Admission to an intensive care unit is denied when intensive care unit resources are constrained, especially for the elderly. Objective: To determine the effect of intensive care unit triage decisions on mortality and intensive care unit benefit, specifically for elderly patients. Design: Prospective, observational study of triage decisions from September 2003 until March 2005. Setting: Eleven intensive care units in seven European countries. Patients: All patients >18 yrs with an explicit request for intensive care unit admission. Interventions: Admission or rejection to intensive care unit. Measurements and Main Results: Demographic, clinical, hospital, physiologic variables, and 28-day mortality were obtained on consecutive patients. There were 8,472 triages in 6,796 patients, 5,602 (82%) were accepted to the intensive care unit, 1,194 (18%) rejected; 3,795 (49%) were ≥65 yrs. Refusal rate increased with increasing patient age (18–44: 11%; 45–64: 15%; 65–74: 18%; 75–84: 23%; >84: 36%). Mortality was higher for older patients (18–44: 11%; 45–64: 21%; 65–74: 29%; 75–84: 37%; >84: 48%). Differences between mortalities of accepted vs. rejected patients, however, were greatest for older patients (18–44: 10.2% vs. 12.5%; 45–64: 21.2% vs. 22.3%; 65–74: 27.9% vs. 34.6%; 75–84: 35.5% vs. 40.4%; >84: 41.5% vs. 58.5%). Logistic regression showed a greater mortality reduction for accepted vs. rejected patients corrected for disease severity for elderly patients (age >65 [odds ratio 0.65, 95% confidence interval 0.55–0.78, p < .0001]) than younger patients (age <65 [odds ratio 0.74, 95% confidence interval 0.57–0.97, p = .01]). Conclusions: Despite the fact that elderly patients have more intensive care unit rejections than younger patients and have a higher mortality when admitted, the mortality benefit appears greater for the elderly. Physicians should consider changing their intensive care unit triage practices for the elderly. (Crit Care Med 2012; 40:132–138) Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's web site (www.ccmjournal.com).
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Summary We assessed the impact of a United Kingdom government‐recommended triage process, designed to guide the decision to admit patients to intensive care during an influenza pandemic, on patients in a teaching hospital intensive care unit. We found that applying the triage criteria to a current case‐mix would result in 116 of the 255 patients (46%) admitted during the study period being denied intensive care treatment they would have otherwise received, of which 45 (39%) survived to hospital discharge. In turn, 69% of those categorised as too ill to warrant admission according to the criteria survived. The sensitivity and specificity of the triage category at ICU admission predicting mortality was 0.29 and 0.84, respectively. If the need for intensive care beds is estimated to be 275 patients per week, the triage criteria would not exclude enough patients to prevent the need for further rationing. We conclude that the proposed triage tool failed adequately to prioritise patients who would benefit from intensive care.
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Background Intensive care treat critically ill patients. When intensive care is not considered beneficial for the patient, decisions to withdraw or withhold treatments are made. We aimed to identify independent patient variables that increase the odds for receiving a decision to withdraw or withhold intensive care. Methods Registry study using data from the Swedish Intensive Care Registry (SIR) 2014‐2016. Age, condition at admission, including co‐morbidities (Simplified Acute Physiology Score version 3, SAPS 3), diagnosis, sex, and decisions on treatment limitations were extracted. Patient data were divided into a full care (FC) group, and a withhold or withdraw (WW) treatment group. Results Of all 97 095 cases, 47.1% were 61‐80 years old, 41.9% were women and 58.1% men. 14 996 (15.4%) were allocated to the WW group and 82 149 (84.6%) to the FC group. The WW group, compared with the FC group, was older ( P < 0.001), had higher SAPS 3 ( P < 0.001) and were predominantly female ( P < 0.001). Compared to patients 16‐20 years old, patients >81 years old had 11 times higher odds of being allocated to the WW group. Higher SAPS 3 (continuous) increased the odds of being allocated to the WW group by odds ratio [OR] 1.085, (CI 1.084‐1.087). Female sex increased the odds of being allocated to the WW group by 18% (1.18; CI 1.13‐ 1.23). Conclusion Older age, higher SAPS 3 at admission and female sex were found to be independent variables that increased the odds to receive a decision to withdraw or withhold intensive care.
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To assess physician decision-making in triage for intensive care and how judgments impact on patient survival.Prospective, descriptive study.General intensive care unit, university medical center.All patients triaged for admission to a general intensive care unit were studied. Information was collected for the patient's age, diagnoses, surgical status, admission purpose, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and mortality. The number of available beds at the time of triage and reasons for refused admission were obtained.Of 382 patients, 290 were admitted, 92 (24%) were refused admission, and 31 were admitted at a later time. Differences between admission diagnoses were found between patients admitted or not admitted (p < .001). Patients refused admission had higher APACHE II scores (15.6+/-1.5 admitted later and 15.8+/-1.4 never admitted) than did admitted patients (12.1+/-.4; p < .001). The frequency of admitting patients decreased when the intensive care unit was full (p < .001). Multivariate analysis revealed that triage to intensive care correlated with age, a full unit, surgical status, and diagnoses. Hospital mortality was lower in admitted (14%) than in refused patients (36% admitted later and 46% never admitted; p < .01) and in admitted patients with APACHE II scores of 11 to 20 (p = .02). The 28-day survival of patients was greater for admitted patients compared with patients never admitted (p = .01).Physicians triage patients to intensive care based on the number of beds available, the admission diagnosis, severity of disease, age, and operative status. Admitting patients to intensive care is associated with a lower mortality rate, especially in patients with APACHE scores of 11 to 20.
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Intensive care units (ICUs) are not always able to admit all patients who would benefit from intensive care. Pressure on ICU beds is likely to be particularly high during times of epidemics such as might arise in the case of swine influenza. In making choices as to which patients to admit, the key US guidelines state that significant priority should be given to the interests of patients who are already in the ICU over the interests of patients who would benefit from intensive care but who have not been admitted. We examine four reasons that in principle might justify such a prioritization rule and conclude that none is convincing. We argue that the current location of patients should not, in principle, affect their priority for intensive care. We show, however, that under some but not all circumstances, maximizing lives saved by intensive care might require continuing to treat in the ICU a patient already admitted rather than transferring that patient out of the unit in order to admit a sicker patient who would also benefit more from intensive care. We conclude that further modelling is required in order to clarify what practical policies would maximize lives saved by intensive care.
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The objectives of this study were to identify factors associated with decisions concerning triage and admission to the intensive care unit and to describe the outcome of patients referred to intensive care unit for admission. The study was a single-centre, prospective, observational study. It was performed in the general intensive care unit of a tertiary regional hospital, over the period of February to June 2009. The patients were non-elective, acute medical in-patients. For 100 patients referred, only 36 were admitted to the intensive care unit. The remaining 64 were declined admission: nine were declined admission because they were assessed as too sick to benefit, 41 were declined admission because they were assessed as too well to benefit and 14 were deemed to potentially benefit from intensive care unit admission but were not admitted (‘triage’). Patients most likely to receive triage decisions were medical in-patients who had expressed wishes about end-of-life care, who were functionally limited with co-morbid conditions affecting their performance status. Patients referred by Resident Medical Officers were also more likely to receive a triage decision. Age, gender, Aboriginal and Torres Strait Islander status, diagnostic category and reason for referral did not impact on admission or triage decisions. Bed status in intensive care unit at the time of referral affected neither admission nor triage decisions. Hospital mortality in patients deemed too well to benefit from intensive care unit was 7.3%, suggesting that all patients referred for consideration of admission to intensive care unit should be classified as ‘high risk’.
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Background: Hospital bed capacity is one of problems in intensive care unit during at the time of crisis, emergencies and disasters. At this regard, it seems reverse triage can resolve this issue by using predictive score systems. This study was purposed to develop a reverse triage system in intensive care unit using APACHE II scoring system for crisis, emergencies and disasters situations. Methods: This study was performed by a prospective longitudinal design that lasted from March 2016 to February 2017. Research population were 420 internal patients that were admitted in intensive care units of Imam Reza Hospital in Mashhad, Iran. Data were collected and documented for each patient by demographic questionnaire and APACHE II scoring system daily until discharging time from intensive care units. The patient’s status after discharge from the intensive care unit was used as a criterion for statistical tests. Results: APACHE II mean score in first day of admission was 18.9±16.20. Risk ratio of patients’ discharging from intensive care unit was 1.034. The patients were placed in four levels of inverse triage according to mortality rate and risk ratio. The scores of four levels were including: 0-10 (first level and green color), 11-16 (second level and yellow color), 27-71 (third level and black color) and 17-26 (fourth level and red color). Conclusion: The Apache II system can be used as a tool for reverse triage in intensive care units during at the time of crisis, emergencies and disasters. When using this system for reverse triage, patients at the first to third levels can be discharged from intensive care unit. However, patients on the fourth level should not be discharged from intensive care units under any circumstances. © 2018, Tehran University of Medical Sciences. All rights reserved.
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Objective: To develop a predictive model to triage patients for discharge from intensive care units to reduce mortality after discharge. Design: Logistic regression analyses and modelling of data from patients who were discharged from intensive care units. Setting: Guy9s hospital intensive care unit and 19 other UK intensive care units from 1989 to 1998. Participants: 5475 patients for the development of the model and 8449 for validation. Main outcome measures: Mortality after discharge and power of triage model. Results: Mortality after discharge from intensive care was up to 12.4%. The triage model identified patients at risk from death on the ward with a sensitivity of 65.5% and specificity of 87.6%, and an area under the receiver operating curve of 0.86. Variables in the model were age, end stage disease, length of stay in unit, cardiothoracic surgery, and physiology. In the validation dataset the 34% of the patients identified as at risk had a discharge mortality of 25% compared with a 4% mortality among those not at risk. Conclusions: The discharge mortality of at risk patients may be reduced by 39% if they remain in intensive care units for another 48 hours. The discharge triage model to identify patients at risk from too early and inappropriate discharge from intensive care may help doctors to make the difficult clinical decision of whom to discharge to make room for a patient requiring urgent admission to the unit. If confirmed, this study has implications on the provision of resources.What is already known on this topic
In the United Kingdom, the mortality of patients who die on the ward after discharge from intensive care is unacceptably high (9% to 27%) Indirect evidence has shown that this is due to too early and inappropriate discharge from intensive care that has increased over the past 10 yearsWhat this study adds
A triage model identifies patients at risk from inappropriate discharge from intensive care Mortality after discharge from intensive care may be reduced by 39% if these patients were to stay in intensive care for another 48 hours An estimated 16% more beds are required if mortality after discharge from intensive care is to be reducedTriage
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