scholarly journals Initiating palliative care consultation for acute critically ill patients in the emergency department intensive care unit

2020 ◽  
Vol 83 (5) ◽  
pp. 500-506
Author(s):  
Che Yang ◽  
Tsu-Te Yang ◽  
Yu-Ju Tsou ◽  
Ming-Hui Lin ◽  
Ju-Sing Fan ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Palliative Care ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Palliative Care Consultation ◽  
Care Consultation

scholarly journals Differences in Characteristics, Hospital Care, and Outcomes between Acute Critically Ill Emergency Department Patients Receiving Palliative Care and Usual Care

2021 ◽  
Vol 18 (23) ◽  
pp. 12546
Author(s):  
Julia Chia-Yu Chang ◽  
Che Yang ◽  
Li-Ling Lai ◽  
Hsien-Hao Huang ◽  
Shih-Hung Tsai ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Palliative Care ◽  
Intensive Care ◽  
Hospital Mortality ◽  
Usual Care ◽  
Critically Ill ◽  
Resource Utilization ◽  
Critically Ill Patients ◽  
Hospital Care

Background: The early integration of palliative care in the emergency department (ED-PC) provides several benefits, including improved quality of life with optimal comfort measures, and symptom control. Whether palliative care could affect the intensive care unit admissions, hospital care and resource utilization requires further investigation. Aim: To determine the differences in inpatient characteristics, hospital care, survival, and resource utilization between patients receiving palliative care (ED-PC) and usual care (UC). Design: Retrospective observational study. Setting/participants: We enrolled consecutive, acute, critically ill patients admitted to the emergency intensive care unit at Taipei Veterans General Hospital from 1 February 2018 to 31 January 2020. Results: A total of 1273 patients were evaluated for unmet palliative care needs; 685 patients received ED-PC and 588 received UC. The palliative care patients were more severely frail (AOR 2.217 (1.295–3.797), p = 0.004), had functional deterioration with three ADLs (AOR 1.348 (1.040–1.748), p = 0.024), biopsychosocial discomfort (AOR 1.696 (1.315–2.187), p < 0.001), higher Taiwan Triage and Acuity Scale 1 (p = 0.024), higher in-hospital mortality (AOR 1.983 (1.540–2.555), p < 0.001), were four times more likely to sign an DNR (AOR 4.536 (2.522–8.158), p < 0.001), and were twice as likely to sign an DNR at admission (AOR 2.1331.619–2.811), p < 0.001). Palliative care patients received less epinephrine (AOR 0.424 (0.265–0.678), p < 0.001), more frequent withdrawal of an endotracheal tube (AOR 8.780 (1.122–68.720), p = 0.038), and more narcotics (AOR1.675 (1.132–2.477), p = 0.010). Palliative care patients exhibited lower 7-day, 30-day, and 90-day survival rates (p < 0.001). There was no significant difference in the hospital length of stay (LOS) (21.2 ± 26.6 vs. 21.7 ± 20.6, p = 0.709) nor total hospital expenses (293,169 ± 350,043 vs. 294,161 ± 315,275, p = 0.958). Conclusion: Acute critically ill patients receiving palliative care were more frail, more critical, and had higher in-hospital mortality. Palliative care patients received less epinephrine, more endotracheal extubation, and more narcotics. There was no difference in the hospital LOS or hospital costs between the palliative and usual care groups. The synthesis of ED-PC is new but achievable with potential benefits to align care with patient goals.

Feasibility and Acceptability of a Palliative Approach Screening Tool in the Intensive Care Unit

2020 ◽  
Vol 29 (3) ◽  
pp. 214-220
Author(s):  
Jane Venis ◽  
Peter Dodek
Keyword(s):  
Intensive Care Unit ◽  
Palliative Care ◽  
Intensive Care ◽  
Focus Group ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Screening Tool ◽  
Unmet Needs ◽  
Pilot Testing ◽  
Palliative Approach

Background Identifying critically ill patients who have unmet needs for palliative care is the first step in integrating the palliative approach for patients and their families into intensive care units. Objective To explore how palliative care is addressed in an intensive care unit and to develop and test a screening tool for unmet needs that may be met through the palliative approach. Methods A mixed-methods study was conducted in the intensive care unit of a tertiary care hospital to explore the palliative approach. Focus groups and a survey were used to identify items for the screening tool. After pilot testing of the tool, interviews were conducted to refine the content. Results The first focus group (14 participants) revealed participants’ frustration with unclear communication and a desire for better collaboration among health care team members regarding patients with serious life-limiting illnesses and their families. The survey (response rate: 20%; 30 of 150) showed clinicians’ preference for items that identify specific needs rather than diagnoses. The second focus group (8 participants) yielded strategies to operationalize the tool for all patients in the intensive care unit. After 2 separate pilot testing cycles, bedside nurses noted that use of the screening tool prompted earlier discussions and broader assessments of what is meaningful to patients and their families. Conclusion Development of a screening tool for unmet palliative care needs among intensive care unit patients is feasible and acceptable and may help to systematically integrate the palliative approach into routine care for critically ill patients.

scholarly journals Using machine learning tools to predict outcomes for emergency department intensive care unit patients

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qiangrong Zhai ◽  
Zi Lin ◽  
Hongxia Ge ◽  
Yang Liang ◽  
Nan Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Predictive Accuracy ◽  
Medical Center ◽  
Learning Tools ◽  
Critical Patients

AbstractThe number of critically ill patients has increased globally along with the rise in emergency visits. Mortality prediction for critical patients is vital for emergency care, which affects the distribution of emergency resources. Traditional scoring systems are designed for all emergency patients using a classic mathematical method, but risk factors in critically ill patients have complex interactions, so traditional scoring cannot as readily apply to them. As an accurate model for predicting the mortality of emergency department critically ill patients is lacking, this study’s objective was to develop a scoring system using machine learning optimized for the unique case of critical patients in emergency departments. We conducted a retrospective cohort study in a tertiary medical center in Beijing, China. Patients over 16 years old were included if they were alive when they entered the emergency department intensive care unit system from February 2015 and December 2015. Mortality up to 7 days after admission into the emergency department was considered as the primary outcome, and 1624 cases were included to derive the models. Prospective factors included previous diseases, physiologic parameters, and laboratory results. Several machine learning tools were built for 7-day mortality using these factors, for which their predictive accuracy (sensitivity and specificity) was evaluated by area under the curve (AUC). The AUCs were 0.794, 0.840, 0.849 and 0.822 respectively, for the SVM, GBDT, XGBoost and logistic regression model. In comparison with the SAPS 3 model (AUC = 0.826), the discriminatory capability of the newer machine learning methods, XGBoost in particular, is demonstrated to be more reliable for predicting outcomes for emergency department intensive care unit patients.

scholarly journals Factors contributing to delay intensive care unit admission of critically ill patients from the adult emergency Department in Tikur Anbessa Specialized Hospital

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Helen Teklie ◽  
Hywet Engida ◽  
Birhanu Melaku ◽  
Abdata Workina
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Intensive Care Unit Admission ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Transfer Time ◽  
Multivariate Logistic Regression ◽  
Icu Admission ◽  
Specialized Hospital

Abstract Background The transfer time for critically ill patients from the emergency department (ED) to the Intensive care unit (ICU) must be minimal; however, some factors prolong the transfer time, which may delay intensive care treatment and adversely affect the patient’s outcome. Purpose To identify factors affecting intensive care unit admission of critically ill patients from the emergency department. Patients and methods A cross-sectional study design was conducted from January 13 to April 12, 2020, at the emergency department of Tikur Anbesa Specialized Hospital. All critically ill patients who need intensive care unit admission during the study period were included in the study. A pretested structured questionnaire was adapted from similar studies. The data were collected by chart review and observation. Then checked data were entered into Epi-data version 4.1 and cleaned data was exported to SPSS Version 25 for analysis. Descriptive statistics, bivariate and multivariate logistic regression were used to analyze the data. Result From the total of 102 critically ill patients who need ICU admission 84.3% of them had prolonged lengths of ED stay. The median length of ED stay was 13.5 h with an IQR of 7–25.5 h. The most common reasons for delayed ICU admission were shortage of ICU beds 56 (65.1%) and delays in radiological examination results 13(15.1%). On multivariate logistic regression p < 0.05 male gender (AOR = 0.175, 95% CI: (0.044, 0.693)) and shortage of ICU bed (AOR = 0.022, 95% CI: (0.002, 0.201)) were found to have a significant association with delayed intensive care unit admission. Conclusion there was a delay in ICU admission of critically ill patients from the ED. Shortage of ICU bed and delay in radiological investigation results were the reasons for the prolonged ED stay.

scholarly journals Intensive care unit admission protocol controlled by intensivists can reduce transfer delays from the emergency department in critically ill patients

2018 ◽  
Vol 26 (2) ◽  
pp. 84-90 ◽  
Author(s):  
Ji Eun Kim ◽  
Seul Lee ◽  
Jinwoo Jeong ◽  
Dong Hyun Lee ◽  
Jin-Heon Jeong
Keyword(s):  
Intensive Care Unit ◽  
Emergency Department ◽  
Intensive Care ◽  
Length Of Stay ◽  
Intensive Care Unit Admission ◽  
Critically Ill ◽  
Critically Ill Patients ◽  
Unit Length ◽  
Intensive Care Unit Length ◽  
Before And After

Background: Delayed transfer of patients from the emergency department to the intensive care unit is associated with adverse clinical outcomes. Critically ill patients with delayed admission to the intensive care unit had higher in-hospital mortality and increased hospital length of stay. Objectives: We investigated the effects of an intensive care unit admission protocol controlled by intensivists on the emergency department length of stay among critically ill patients. Methods: We designed the intensive care unit admission protocol to reduce the emergency department length of stay in critically ill patients. Full-time intensivists determined intensive care unit admission priorities based on the severity of illness. Data were gathered from patients who were admitted from the emergency department to the intensive care unit between 1 April 2016 and 30 November 2016. We retrospectively analyzed the clinical data and compared the emergency department length of stay between patients admitted from the emergency department to the intensive care unit before and after intervention. Results: We included 292 patients, 120 and 172 were admitted before and after application of the intensive care unit admission protocol, respectively. The demographic characteristics did not differ significantly between the groups. After intervention, the overall emergency department length of stay decreased significantly from 1045.5 (425.3–1665.3) min to 392.0 (279.3–686.8) min (p < 0.001). Intensive care unit length of stay also significantly decreased from 6.0 (4.0–11.8) days to 5.0 (3.0–10.0) days (p = 0.015). Conclusion: Our findings suggest that introduction of the intensive care unit admission protocol controlled by intensivists successfully decreased the emergency department length of stay and intensive care unit length of stay among critically ill patients at our institution.

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