Impact of delayed admission to intensive care units on mortality of critically ill patients: a cohort study

Measurement of Cost of Boarding in the Emergency Department Using Time-Driven Activity-Based Costing

STUDY OBJECTIVE

Boarding admitted patients in emergency departments (EDs) is a national crisis that is worsening despite potential financial disadvantages. The objective of this study was to assess costs associated with boarding.

METHODS

We conducted a prospective, observational investigation of patients admitted through an ED for management of acute stroke at a large, urban, academic, comprehensive stroke center hospital. We employed time-driven activity-based costing methodology to estimate cost for patient care activities during admission and aggregated results to estimate the total cost of boarding versus inpatient care. Primary outcomes were total daily costs per patient for medical-surgical (med/surg) boarding, med/surg inpatient care, ICU boarding, and ICU inpatient care.

RESULTS

The total daily cost per patient with acute stroke was US$1856, for med/surg boarding versus US$993 for med/surg inpatient care and US$2267, for ICU boarding versus US$2165, for ICU inpatient care. These differences were even greater when accounting for costs associated with traveler nurses. ED nurses spent 293 min/d (mean) caring for each med/surg boarder; inpatient nurses spent 313 min/d for each med/surg inpatient. ED nurses spent 419 min/d caring for each ICU boarder; inpatient nurses spent 787 min/d for each ICU inpatient. Neurology attendings and residents spent 25 and 52 min/d caring for each med/surg boarder versus 62 minutes and 90 minutes for each med/surg inpatient, respectively.

CONCLUSION

Using advanced cost-accounting methods, our investigation provides novel evidence that boarding of admitted patients is financially costly, adding greater urgency for elimination of this practice.

Adverse Events in Patients Transitioning From the Emergency Department to the Inpatient Setting

OBJECTIVES

The objective of this study was to determine the incidence and types of adverse events (AEs), including preventable and ameliorable AEs, in patients transitioning from the emergency department (ED) to the inpatient setting. A second objective was to examine the risk factors for patients with AEs.

METHODS

This was a prospective cohort study of patients at risk for AEs in 2 urban academic hospitals from August 2020 to January 2022. Eighty-one eligible patients who were being admitted to any internal medicine or hospitalist service were recruited from the ED of these hospitals by a trained nurse. The nurse conducted a structured interview during admission and referred possible AEs for adjudication. Two blinded trained physicians using a previously established methodology adjudicated AEs.

RESULTS

Over 22% of 81 patients experienced AEs from the ED to the inpatient setting. The most common AEs were adverse drug events (42%), followed by management (38%), and diagnostic errors (21%). Of these AEs, 75% were considered preventable. Patients who stayed in the ED longer were more likely to experience an AE (adjusted odds ratio = 1.99, 95% confidence interval = 1.19-3.32, P = 0.01).

CONCLUSIONS

AEs were common for patients transitioning from the ED to the inpatient setting. Further research is needed to understand the underlying causes of AEs that occur when patients transition from the ED to the inpatient setting. Understanding the contribution of factors such as length of stay in the ED will significantly help efforts to develop targeted interventions to improve this crucial transition of care.

Rapid response system and mortality in intensive care unit: a nationwide cohort study in South Korea

The beneficial effects of a rapid response system (RRS) on clinical outcomes in patients admitted to a ward have been established. However, the relationship between RRS implementation and clinical outcomes in patients in the intensive care unit (ICU) has not yet been established. Therefore, we aimed to investigate whether the RRS affects clinical outcomes in critically ill patients admitted to the ICU. As a nationwide, population-based cohort study, all adult patients who were admitted to the ICU from 1 January 2019 to 31 December 2021 in South Korea were included. Patients in hospitals with an RRS formed the RRS group; those in hospitals lacking an RRS constituted the non-RRS group. In total, 900,606 patients admitted to the ICU were included in the final analysis. Among them, 365,305 (40.6%) were assigned to the RRS group, and 535,301 (59.4%) were assigned to the non-RRS group. After propensity score (PS) matching, a total of 454,748 patients (227,374 in each group) were included in the final analysis. In the PS-matched cohort, the RRS group showed 8% (odds ratio [OR]: 0.92, 95% confidence interval [CI]: 0.91, 0.94; P < 0.001) and 11% (hazard ratio: 0.89, 95% CI: 0.88, 0.90; P < 0.001) lower in-hospital mortality rates and 1-year all-cause mortality rates than the non-RRS group, respectively. In addition, ICU readmission rates and the occurrence rate for adverse events during hospitalization in the RRS group were 3% (OR: 0.97, 95% CI: 0.95, 0.98; P < 0.001) and 21% (OR: 0.79, 95% CI: 0.78, 0.80; P < 0.001) lower than those in the non-RRS group, respectively. RRS deployment was linked to lower in-hospital and 1-year all-cause mortality rates, ICU readmission rates, and the occurrence of adverse events during hospitalization among ICU patients. The findings indicate that using the RRS could assist not only patients in the ward but also critically ill patients in the ICU.

Implementing Oxygen Therapy in Medical Wards-A Scoping Review to Understand Health Services Protocols and Procedures

Background/Objectives: Conventional oxygen therapy (COT) is the cornerstone of management for hypoxaemia associated with acute respiratory failure (ARF) in wards. COT implementation guidance is provided in local health guidance documents (LHGDs). This study aimed to identify ward-delivered adult COT implementation LHGDs in Australian health services and assess their content and accuracy. Methods: A scoping review was conducted on 1 May 2022 and updated on 19 December 2023 to identify public health services COT LHGDs. Data were extracted and analysed regarding COT initiation, monitoring, maintenance and weaning, and management of clinical deterioration. Results: Thirty-seven included LHGDs, and eleven referenced the Australian COT guidelines. A definition in the LHGDs for hypoxaemia is that any oxygen saturation (SpO2) or arterial blood gas (ABG) is rare. None required ABG prior to COT initiation. Twenty-nine provided target SpO2 aims for initiation and maintenance. Fifteen did not specify the criteria for clinical review. Nine LHGDs provided guidance on weaning. Conclusions: There was considerable variation in the structure and content of COT LHGDs in Australian health services. Variations and limited guideline concordance of LHGDs may impact the quality and safety of health care. Considerations for future research include the development and implementation of standardised core LHGD recommendations for COT, as well as conducting a national oxygen audit to better measure and benchmark the safety and quality of care.

Risk factors predicting the need for intensive care unit admission within forty-eight hours of emergency department presentation: A case-control study

BACKGROUND

Patients admitted from the emergency department to the wards, who progress to a critically unwell state, may require expeditious admission to the intensive care unit. It can be argued that earlier recognition of such patients, to facilitate prompt transfer to intensive care, could be linked to more favourable clinical outcomes. Nevertheless, this can be clinically challenging, and there are currently no established evidence-based methods for predicting the need for intensive care in the future.

OBJECTIVES

We aimed to analyse the emergency department data to describe the characteristics of patients who required an intensive care admission within 48 h of presentation. Secondly, we planned to test the feasibility of using this data to identify the associated risk factors for developing a predictive model.

METHODS

We designed a retrospective case-control study. Cases were patients admitted to intensive care within 48 h of their emergency department presentation. Controls were patients who did not need an intensive care admission. Groups were matched based on age, gender, admission calendar month, and diagnosis. To identify the associated variables, we used a conditional logistic regression model.

RESULTS

Compared to controls, cases were more likely to be obese, and smokers and had a higher prevalence of cardiovascular (39 [35.1%] vs 20 [18%], p = 0.004) and respiratory diagnoses (45 [40.5%] vs 25 [22.5%], p = 0.004). They received more medical emergency team reviews (53 [47.8%] vs 24 [21.6%], p < 0.001), and more patients had an acute resuscitation plan (31 [27.9%] vs 15 [13.5%], p = 0.008). The predictive model showed that having acute resuscitation plans, cardiovascular and respiratory diagnoses, and receiving medical emergency team reviews were strongly associated with having an intensive care admission within 48 h of presentation.

CONCLUSIONS

Our study used emergency department data to provide a detailed description of patients who had an intensive care unit admission within 48 h of their presentation. It demonstrated the feasibility of using such data to identify the associated risk factors to develop a predictive model.

Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions

Return visit admissions (RVA), which are instances where patients discharged from the emergency department (ED) rapidly return and require hospital admission, have been associated with quality issues and adverse outcomes. We developed and validated a machine learning model to predict 72-hour RVA using electronic health records (EHR) data. Study data were extracted from EHR data in 2019 from three urban EDs. The development and independent validation datasets included 62,154 patients from two EDs and 73,453 patients from one ED, respectively. Multiple machine learning algorithms were evaluated, including deep significance clustering (DICE), regularized logistic regression (LR), Gradient Boosting Decision Tree, and XGBoost. These machine learning models were also compared against an existing clinical risk score. To support clinical actionability, clinician investigators conducted manual chart reviews of the cases identified by the model. Chart reviews categorized predicted cases across index ED discharge diagnosis and RVA root cause classifications. The best-performing model achieved an AUC of 0.87 in the development site (test set) and 0.75 in the independent validation set. The model, which combined DICE and LR, boosted predictive performance while providing well-defined features. The model was relatively robust to sensitivity analyses regarding performance across age, race, and by varying predictor availability but less robust across diagnostic groups. Clinician examination demonstrated discrete model performance characteristics within clinical subtypes of RVA. This machine learning model demonstrated a strong predictive performance for 72- RVA. Despite the limited clinical actionability potentially due to model complexity, the rarity of the outcome, and variable relevance, the clinical examination offered guidance on further variable inclusion for enhanced predictive accuracy and actionability.

Plasma-derived extracellular vesicles (EVs) as biomarkers of sepsis in burn patients via label-free Raman spectroscopy

Sepsis following burn trauma is a global complication with high mortality, with ∼60% of burn patient deaths resulting from infectious complications. Diagnosing sepsis is complicated by confounding clinical manifestations of the burn injury, and current biomarkers lack the sensitivity and specificity required for prompt treatment. There is a strong rationale to assess circulating extracellular vesicles (EVs) from patient liquid biopsy as sepsis biomarkers due to their release by pathogens from bacterial biofilms and roles in the subsequent immune response. This study applies Raman spectroscopy to patient plasma-derived EVs for rapid, sensitive, and specific detection of sepsis in burn patients, achieving 97.5% sensitivity and 90.0% specificity. Furthermore, spectral differences between septic and non-septic burn patient EVs could be traced to specific glycoconjugates of bacterial strains associated with sepsis morbidity. This work illustrates the potential application of EVs as biomarkers in clinical burn trauma care and establishes Raman analysis as a fast, label-free method to specifically identify features of bacterial EVs relevant to infection amongst the host background.

Clinical audit of cases and outcomes of patients admitted to the intensive care unit at Kamuzu Central Hospital, Lilongwe, Malawi

In 2016, a new, improved and modern intensive care unit was constructed at Kamuzu Central Hospital in Lilongwe, Malawi. Having been operational for about 4 years, there has not been a systematic audit to gauge its performance. Therefore, this quantitative retrospective cohort study aimed at investigating the performance of the intensive care unit at Kamuzu Central Hospital in Lilongwe, Malawi. We analysed the patterns of admission through 250 clinical cases and their respective outcomes spanning from 1st January 2019 to 31st December 2019 using STATA. Descriptive and inferential statistics were computed. We also had a follow-up discussion with the Head of the unit to better understand the unit's functioning. Out of the 250 admissions, we evaluated 249 case files. About 30.8% of all patients were referred from the main operating theatre, and 20.7% from the casualty (emergency medicine). Head injury (26.7%) and peritonitis (15.7%) were the commonest causes of admission. The overall mortality was 52.2% with more females (57.5%) dying than males (47.9%). Head injury and peritonitis had the highest contribution to the mortality accounting for 25.3% and 16.9% of all deaths respectively. In conclusion, despite the new unit registering an improved performance compared to the old unit's 2012 mortality of 60.9%, the current mortality rate of 52.2% generally reflects a suboptimal performance. The intensive care unit is still grappling with a number of challenges that need immediate attention including few working beds, shortage of critical care specialists and nursing staff and lack of standard admission criteria.

In-Hospital Triage

The intensive care unit (ICU) is a finite and expensive resource with demand not infrequently exceeding capacity. Understanding ICU capacity strain is essential to gain situational awareness. Increased capacity strain can influence ICU triage decisions, which rely heavily on clinical judgment. Having an admission and triage protocol with which clinicians are very familiar can mitigate difficult, inappropriate admissions. This article reviews these concepts and methods of in-hospital triage.

Tele-Critical Care Support Outside the Intensive Care Unit

Tele-intensive care unit (ICU), or Tele Critical Care (TCC), has been in active use for 25 years and has expanded beyond the original model to support critically ill patients beyond the confines of the ICU. Here, the author reviews the role of TCC in supporting rapid response events, critical care in emergency departments, and disaster and pandemic responses. The ability to rapidly expand critical care services has important capacity and care quality implications. Moreover, as TCC infrastructure becomes less expensive, the opportunities to leverage this care modality also have potentially important financial benefits.

The Role of Intermediate Care in Supporting Critically Ill Patients and Critical Care Infrastructure

Intermediate care (IC) is used for patients who do not require the human and technological support of the intensive care unit (ICU) yet require more care and monitoring than can be provided on general wards. Though prevalent in many countries, there is marked variability in models of organization and staffing, as well as monitoring and interventions provided. In this article, the authors will discuss the historical background of IC, review the impact of IC on ICU and IC patient outcomes, and highlight where future studies can shed light on how to optimize IC organization and outcomes.

A quality improvement study on how a simulation model can help decision making on organization of ICU wards

BACKGROUND

Intensive Care Unit (ICU) capacity management is essential to provide high-quality healthcare for critically ill patients. Yet, consensus on the most favorable ICU design is lacking, especially whether ICUs should deliver dedicated or non-dedicated care. The decision for dedicated or non-dedicated ICU design considers a trade-off in the degree of specialization for individual patient care and efficient use of resources for society. We aim to share insights of a model simulating capacity effects for different ICU designs. Upon request, this simulation model is available for other ICUs.

METHODS

A discrete event simulation model was developed and used, to study the hypothetical performance of a large University Hospital ICU on occupancy, rejection, and rescheduling rates for a dedicated and non-dedicated ICU design in four different scenarios. These scenarios either simulate the base-case situation of the local ICU, varying bed capacity levels, potential effects of reduced length of stay for a dedicated design and unexpected increased inflow of unplanned patients.

RESULTS

The simulation model provided insights to foresee effects of capacity choices that should be made. The non-dedicated ICU design outperformed the dedicated ICU design in terms of efficient use of scarce resources.

CONCLUSIONS

The choice to use dedicated ICUs does not only affect the clinical outcome, but also rejection- rescheduling and occupancy rates. Our analysis of a large university hospital demonstrates how such a model can support decision making on ICU design, in conjunction with other operation characteristics such as staffing and quality management.

A respiratory critical care nurse training program for settings without a registered respiratory therapists: A protocol for a multimethod study

BACKGROUND

The increasing elderly population and prevalence of chronic diseases have raised the need for ICU beds. However, limited bed availability often causes delays in admission, leading to wasted treatment time.

OBJECTIVES

This study aims to create and implement a training program for respiratory critical care nurses (RCCNs) in settings without registered respiratory therapists (RRTs).

RESEARCH

METHODOLOGY/DESIGN

The study will use a multimethod sequential research design, including a scoping review, content analysis, Delphi methods, and a randomized clinical trial. The scoping review will gather extensive information on respiratory care for critically ill patients and the responsibilities of RCCNs. Content analysis and expert interviews will identify opportunities and challenges in RCCNs' provision of respiratory care. The Delphi method will integrate the results to develop a comprehensive training program for RCCNs. Subsequently, five RCCNs will undergo theoretical and practical examinations after completing the three-month training program, and the impact of RCCNs on critically ill patients' outcomes will be evaluated through a clinical trial.

ANTICIPATED FINDINGS

The study aims to provide a comprehensive training program for RCCNs and investigate its impact on the outcomes of critically ill patients through a clinical trial.

CONCLUSION

The training program will equip RCCNs with the necessary skills and knowledge to provide respiratory critical care from the emergency department to hospital discharge. This pioneering study aims to improve patient outcomes in settings without RRTs by offering a unique program for RCCNs.

IMPLICATIONS FOR CLINICAL PRACTICE

The development and implementation of this training program for RCCNs in settings without RRTs will address the gap in respiratory care and potentially improve patient outcomes. By empowering RCCNs with specialized training, healthcare facilities can ensure the provision of high-quality respiratory care throughout a patient's critical illness journey, enhancing the efficiency and effectiveness of healthcare teams, especially in resource-limited settings.

Different but Equal: Outcomes of Prolonged Postanesthesia Care Unit Stay After Trauma Laparotomy

INTRODUCTION

Hospital overcrowding is common and can lead to delays in intensive care unit (ICU) admission, resulting in increased morbidity and mortality in medical and surgical patients. Data on delayed ICU admission are limited in the postsurgical trauma cohort. Damage control laparotomy with temporary abdominal closure (DCL-TAC) for severely injured patients is often followed by an aggressive early resuscitation phase, usually occurring in the ICU. We hypothesized that patients who underwent DCL-TAC with initial postanesthesia care unit (PACU) stay would have worse outcomes than those directly admitted to ICU.

METHODS

A retrospective chart review identified all trauma patients who underwent DCL-TAC at a level 1 trauma center over a 5 y period. Demographics, injuries, and resuscitation markers at 12 and 24 h were collected. Patients were stratified by location after index laparotomy (PACU versus ICU) and compared. Outcomes included composite morbidity and mortality. Multivariable logistic regression was performed.

RESULTS

Of the 561 patients undergoing DCL-TAC, 134 (24%) patients required PACU stay due to ICU bed shortage, and 427 (76%) patients were admitted directly to ICU. There was no difference in demographics, injury severity score, time to resuscitation, complications, or mortality between PACU and ICU groups. Only 46% of patients were resuscitated at 24 h; 76% underwent eventual primary fascial closure. Under-resuscitation at 24 h (adjusted odds ratio [AOR] 0.55; 95% confidence interval [CI] 0.31-0.95, P = 0.03), increased age (AOR 1.04; 95% CI 1.02-10.55, P < 0.0001), and increased injury severity score (AOR 1.04; 95% CI 1.02-1.07, P < 0.0001) were associated with mortality on multivariable logistic regression. The median time in PACU was 3 h.

CONCLUSIONS

PACU hold is not associated with worse outcomes in patients undergoing DCL-TAC. While ICU was designed for the resuscitation of critically ill patients, PACU is an appropriate alternative when an ICU bed is unavailable.

Prolonged time to recovery and its predictors among trauma patients admitted to the intensive care units in comprehensive specialized hospitals in Northwest Ethiopia: a multicenter retrospective follow-up study, 2022

Introduction

A prolonged time to recovery in the intensive care units has adverse effects on both the patients and the healthcare providers. However, there is limited evidence in African countries, including Ethiopia. Therefore, this study aimed to assess the time to recovery and its predictors among trauma patients admitted to intensive care units.

Methods

An institutional-based retrospective follow-up study was conducted on trauma patients hospitalized in intensive care units between 9 January 2019 and 8 January 2022. The charts of 450 patients were chosen using a simple random sampling technique. Data collection was conducted using smartphones and tablets. The data were then exported into STATA version 16 for analysis. The log-rank test and the Kaplan-Meier survival curve were fitted for analysis. An adjusted hazard ratio with 95% confidence intervals was reported to declare the strength of association between time to recovery and predictors in the multivariable Weibull regression analysis.

Results

The overall incidence density rate of recovery was 6.53 per 100 person-day observations, with a median time to recovery of 10 days. Significant predictors of time to recovery included being on mechanical ventilation (AHR = 0.47, 95% CI: 0.34, 0.64), having a Glasgow Coma Scale (GCS) score between 9-12 and 13-15 (AHR = 1.58, 95% CI: 1.01, 2.47, and AHR = 1.66, 95% CI: 1.09, 2.53, respectively), experiencing polytrauma (AHR = 0.55, 95% CI: 0.39, 0.78), and having complications (AHR = 0.43, 95% CI: 0.31, 0.59).

Conclusion and recommendations

The incidence rate of recovery for trauma patients is lower than the national standard, and the median time to recovery is longer. Being on mechanical ventilation, mild and moderate GCS scores, polytrauma, and the presence of complications were significantly associated with prolonged time to recovery. Therefore, special attention has to be given to trauma patients who had polytrauma, complications, received mechanical ventilation, and had a lower GCS score.

Emergency critical care: closing the gap between onset of critical illness and intensive care unit admission

Critical illness is an exquisitely time-sensitive condition and follows a disease continuum, which always starts before admission to the intensive care unit (ICU), in the majority of cases even before hospital admission. Reflecting the common practice in many healthcare systems that critical care is mainly provided in the confined areas of an ICU, any delay in ICU admission of critically ill patients is associated with increased morbidity and mortality. However, if appropriate critical care interventions are provided before ICU admission, this association is not observed. Emergency critical care refers to critical care provided outside of the ICU. It encompasses the delivery of critical care interventions to and monitoring of patients at the place and time closest to the onset of critical illness as well as during transfer to the ICU. Thus, emergency critical care covers the most time-sensitive phase of critical illness and constitutes one missing link in the chain of survival of the critically ill patient. Emergency critical care is delivered whenever and wherever critical illness occurs such as in the pre-hospital setting, before and during inter-hospital transfers of critically ill patients, in the emergency department, in the operating theatres, and on hospital wards. By closing the management gap between onset of critical illness and ICU admission, emergency critical care improves patient safety and can avoid early deaths, reverse mild-to-moderate critical illness, avoid ICU admission, attenuate the severity of organ dysfunction, shorten ICU length of stay, and reduce short- and long-term mortality of critically ill patients. Future research is needed to identify effective models to implement emergency critical care systems in different healthcare systems.

Plasma-derived Extracellular Vesicles (EVs) as Biomarkers of Sepsis in Burn Patients via Label-free Raman Spectroscopy

Sepsis following burn trauma is a global complication with high mortality, with ~60% of burn patient deaths resulting from infectious complications. Sepsis diagnosis is complicated by confounding clinical manifestations of the burn injury, and current biomarkers markers lack the sensitivity and specificity required for prompt treatment. Circulating extracellular vesicles (EVs) from patient liquid biopsy as biomarkers of sepsis due to their release by pathogens from bacterial biofilms and roles in subsequent immune response. This study applies Raman spectroscopy to patient plasma derived EVs for rapid, sensitive, and specific detection of sepsis in burn patients, achieving 97.5% sensitivity and 90.0% specificity. Furthermore, spectral differences between septic and non-septic burn patient EVs could be traced to specific glycoconjugates of bacterial strains associated with sepsis morbidity. This work illustrates the potential application of EVs as biomarkers in clinical burn trauma care, and establishes Raman analysis as a fast, label-free method to specifically identify features of bacterial EVs relevant to infection amongst the host background.

Exploring the Ramifications of Delayed Hospital Discharges: Impacts on Patients, Physicians, and Healthcare Systems

Prolonged hospital stays can significantly impede patients' recovery, negatively affecting anything from physical health via issues like hospital-acquired infections and increased complications due to immobility to psychological health. Several studies investigated the psychosocial impact of prolonged hospital stays, revealing a variety of patient perspectives, such as feeling uncertain and frustrated about their conditions, which can erode their trust in healthcare providers. Delayed discharges not only affect patients but also have multifaceted effects on healthcare providers, potentially reducing physician efficiency and contributing to higher rates of burnout among healthcare professionals. This article investigates the consequences of delayed versus early discharge on physicians, patients, and the overall hospital system. We conducted an extensive search through PubMed and Google Scholar using the keywords "delayed discharge," "hospital discharge," and "bed blocking" to identify all the recent studies highlighting the dynamics of patient discharge. Our results support the hypothesis that reducing delayed discharge rates will not only improve patient outcomes but also have widespread fiscal impacts. This review also outlines measures to reduce delayed discharges, ultimately leading to a significant enhancement in the healthcare system.

Prognostic Factors and Outcomes in Patients With Septic Shock After Allogeneic Hematopoietic Stem Cell Transplantation

Septic shock remains a potentially life-threatening complication among allogeneic hematopoietic stem cell transplant (allo-HSCT) recipients. There is a paucity of information on the clinical characteristics, outcome and prognostic factors of septic shock patients after allo-HSCT. We aimed to describe the clinical characteristics of septic shock after allo-HSCT and its associated health outcomes and to evaluate the role of patient demographics, transplantation-related laboratory and clinical variables associated with the short-term mortality of septic shock after allo-HSCT. We retrospectively studied 242 septic shock patients from 6105 consecutive patients allografted between 2007 and 2021. We assessed 29 risk factors as candidate predictors and used multivariable logistic regression to establish clinical model. The primary outcome was 28-day mortality. The median age of the subjects was 34 (IQR 24 to 45) years. A total of 148 patients (61.2%) had positive blood cultures. Gram-negative bacilli accounted for 61.5% of the positive isolates, gram-positive cocci accounted for 12.2%, and fungi accounted for 6.1%. Coinfections were found in 30 (20.3%) patients. Escherichia coli was the dominant isolated pathogen (31.1%), followed by Pseudomonas spp. (12.8%) and Klebsiella pneumoniae (10.1%). With a median follow-up of 34 (IQR: 2 to 528) days, a total of 142 (58.7%) patients died, of whom 118 (48.8%) died within the first 28 days after septic shock diagnosis, 131 (54.1%) died within 90 days, and 141 (58.3%) died within 1 year. A large majority of deaths (83.1% [118/142]) occurred within 28 days of septic shock diagnosis. Finally, 6 independent predictive variables of 28-day mortality were identified by multivariable logistic regression: time of septic shock, albumin, bilirubin, PaO2/FiO2, lactate, and sepsis-induced coagulopathy. Patients with late onset shock had higher 28-day mortality rates (64.6% versus 25.5%, P < .001) and more ICU admission (32.6% versus 7.1%, P < .001) than those with early onset shock. We highlight the poor survival outcomes in patients who develop septic shock, emphasizing the need for increasing awareness regarding septic shock after allo-HSCT. The information from the current study may help to assist clinicians in identifying high-risk patients.

Measuring Emergency Department Workload Perception Using Electronic Medical Record Measures of Patient Volume and Acuity

BACKGROUND

Workload in the emergency department (ED) fluctuates and there is no established model for measurement of clinician-level ED workload.

OBJECTIVE

The aim of this study was to measure perceived ED workload and assess the relationship between perceived workload and objective measures of workload from the electronic medical record (EMR).

METHODS

This study was conducted at a tertiary care, academic ED from July 1, 2020 through April 13, 2021. Attending workload perceptions were collected using a 5-point scale in three care areas with variable acuity. We collected eight EMR measures thought to correlate with perceived workload. EMR values were compared across areas of the department using ANOVA and correlated with attending workload ratings using linear regression.

RESULTS

We collected 315 unique workload ratings, which were normally distributed. For the entire department, there was a weak positive correlation between reported workload perception and mean percentage of inpatient admissions (r = 0.23; p < 0.001), intensive care unit admissions (r = 0.2; p < 0.001), patient arrivals per shift (r = 0.14; p = 0.017), critical care billed visits (r = 0.22; p < 0.001), cardiopulmonary resuscitation code activations (r = 0.2; p < 0.001), and level 5 visits (r = 0.13; p = 0.02). There was weak negative correlation for ED discharges (r = -0.23; p < 0.001). Several correlations were stronger in individual care areas, including percent admissions in the lowest-acuity area (r = 0.43; p = 0.033) and patient arrivals in the highest-acuity area (r = 0.44; p < .01). No significant correlation was found in any area for observation admissions or trauma activations.

CONCLUSIONS

In this study, EMR measures of workload were not closely correlated with ED attending physician workload perception. Future study should examine additional factors contributing to physician workload outside of the EMR.

Determinants of Mortality of Patients Admitted to the Intensive Care Unit at Debre Berhan Comprehensive Specialized Hospital: A Retrospective Cohort Study

Background

The provision of intensive care services is advancing globally. However, in resource-limited settings, it is lagging far behind and intensive care unit mortality is still higher due to various reasons. This study aimed to assess determinants of mortality among medical patients admitted to the intensive care unit.

Methods

A five-year facility-based retrospective Cohort Study was conducted. A total of 546 medical patients admitted to the intensive care unit from March 2017 to February 2022 were included. Document review using a structured questionnaire was implemented to collect data. Data entered into Epi Data were analyzed by STATA and summarized using frequency tables and graphs. Binary and multivariate logistic regression analyses were performed to identify determinants of mortality.

Results

The overall mortality was 35.9%. Approximately half of the deaths were attributed to septic shock, congestive heart failure, severe community-acquired pneumonia, and stroke. The most common immediate cause of death was cardio-respiratory arrest. Source of admission, GCS level at admission, duration of ICU stay, treatment with inotropes, septic shock, and retroviral infection status were found to have a statistically significant association with ICU mortality.

Conclusion and Recommendations

This study revealed a significantly higher mortality rate among patients admitted to the intensive care unit. Early identification and admission of patients to the intensive care unit are important factors that could decrease mortality. Patient selection is essential since some patients with a high likelihood of mortality might not benefit from intensive care unit admission in an area with high resource limitations.

Impact of emergency department length of stay on in-hospital mortality: a retrospective cohort study

BACKGROUND AND IMPORTANCE

Emergency Department (ED) workload may lead to ED crowding and increased ED length of stay (LOS). ED crowding has been shown to be associated with adverse events and increasing mortality. We hypothesised that ED-LOS is associated with mortality.

OBJECTIVE

To study the relationship between ED-LOS and in-hospital mortality.

DESIGN

Observational retrospective cohort study.

SETTINGS AND PARTICIPANTS

From 1 January 2015 to 30 September 2018, all visits by patients aged 15 or older to one of the two ED at Toulouse University Hospital were screened. Patients admitted to the hospital after ED visits were included. Visits followed by ED discharge, in-ED death or transfer to ICU or another hospital were not included.

OUTCOME MEASURE AND ANALYSIS

The primary outcome was 30-day in-hospital mortality. ED-LOS was defined as time from ED registration to inpatient admission. ED-LOS was categorised according to quartiles [<303 min (Q1), between 303 and 433 minutes (Q2), between 434 and 612 minutes (Q3) and >612 min (Q4)]. A multivariable logistic regression tested the association between ED-LOS and in-hospital mortality.

MAIN RESULTS

A total of 49 913 patients were admitted to our hospital after ED visits and included in the study. ED-LOS was not independently associated with in-hospital mortality. Compared to ED-LOS < 303 min (Q1, reference), odd-ratios (OR) [95% CI] of in-hospital mortality for Q2, Q3, and Q4 were respectively 0.872 [0.747-1.017], 0.906 [0.777-1.056], and 1.137 [0.985-1.312]. Factors associated to in-hospital mortality were: aged over 75 years (OR [95% CI] = 4.3 [3.8-4.9]), Charlson Comorbidity Index score > 1 (OR [95% CI] = 1.3 [1.1-1.5], and 2.2 [1.9-2.5] for scores 2 and ≥ 3 respectively), high acuity at triage (OR [95% CI] = 3.9 [3.5-4.4]), ED visit at Hospital 1 (OR [95% CI] = 1.6 [1.4-1.7]), and illness diagnosis compared to trauma (OR [95% CI] = 2.1 [1.7-2.6]). Night-time arrival was associated with decreased in-hospital mortality (OR [95% CI] = 0.852 [0.767-0.947]).

CONCLUSION

In this retrospective cohort study, there was no independent association between ED-LOS before admission to general non-ICU wards and in-patient mortality.

Outcomes in patients receiving continuous monitoring of vital signs on general wards: A systematic review and meta-analysis of randomised controlled trials

Objective

The timely identification of deterioration on general wards is crucial to patient care with each hour of delay independently associated with increased risk of death. The introduction of continuous monitoring of patient vital signs on general wards, currently not standard care, may improve patient outcomes. Our aim was to investigate whether patients on general wards receiving continuous vital signs monitoring have better outcomes than patients receiving usual care.

Methods

Meta-analysis of randomised controlled trials comparing non-critical care patients receiving continuous monitoring of vital signs to usual care. We searched Medline, Embase, and Web of Science, and assessed risk of bias with version 2 of the Cochrane risk-of-bias tool for randomised trials. In addition to measures related to the early detection of deterioration, we planned to present all patient outcomes reported by the clinical trials included.

Results

We included seven trials involving 1284 participants. There were no statistically significant differences in the four outcomes pooled. Comparing continuously monitored to normal care, the pooled odds for hospital mortality, major event/complication, and HDU/ICU admission was 0.95 (95% CI 0.59-1.53, p = 0.84; 660 participants, 3 studies), 0.71 (95% CI 0.38-1.31, p = 0.27; 948 participants, 4 studies) and 0.82 (95% CI 0.25-2.67, p = 0.74; 655 participants, 4 studies), respectively. The mean difference for length of stay was 2.12 days lower (95% CI -5.56 to 1.32, p = 0.23; 1034 participants, 6 studies).

Conclusion

We found no significant improvements in outcomes for patients continuously monitored compared to usual care. Further research is needed to understand what modalities of continuous monitoring may influence outcomes and investigate the implications of a telepresence service and multi-parameter scoring system.

Registration

PROSPERO CRD42023458656.

Diagnosis and investigation of suspected haemophagocytic lymphohistiocytosis in adults: 2023 Hyperinflammation and HLH Across Speciality Collaboration (HiHASC) consensus guideline

Haemophagocytic lymphohistiocytosis (HLH) is a hyperinflammatory syndrome characterised by persistently activated cytotoxic lymphocytes and macrophages, which, if untreated, leads to multiorgan dysfunction and death. HLH should be considered in any acutely unwell patient not responding to treatment as expected, with prompt assessment to look for what we term the three Fs-fever, falling blood counts, and raised ferritin. Worldwide, awareness of HLH and access to expert management remain inequitable. Terminology is not standardised, classification criteria are validated in specific patient groups only, and some guidelines rely on specialised and somewhat inaccessible tests. The consensus guideline described in this Health Policy was produced by a self-nominated working group from the UK network Hyperinflammation and HLH Across Speciality Collaboration (HiHASC), a multidisciplinary group of clinicians experienced in managing people with HLH. Combining literature review and experience gained from looking after patients with HLH, it provides a practical, structured approach for all health-care teams managing adult (>16 years) patients with possible HLH. The focus is on early recognition and diagnosis of HLH and parallel identification of the underlying cause. To ensure wide applicability, the use of inexpensive, readily available tests is prioritised, but the role of specialist investigations and their interpretation is also addressed.

Effects of Clinical Frailty Scale Score on Adverse Outcomes and Length of Emergency Department Stay Before Intensive Care Unit Admission

BACKGROUND

Older adults living with frailty who require treatment in hospitals are increasingly seen in emergency departments (EDs).

OBJECTIVE

This study investigated the effects of frailty severity according to the Clinical Frailty Scale (CFS) on adverse outcomes and length of stay in the ED before intensive care unit (ICU) admission.

METHODS

We conducted this prospective observational study with patients 65 years or older and admitted to the ICU from March 1, 2021 to December 31, 2022. We divided the patients into four groups according to their CFS scores. We determined the effects of frailty severity on length of ED stay and clinical outcomes using logistic regression analysis.

RESULTS

Of the 920 patients included in the study, 25.4% were nonfrail, 26.2% had mild frailty, 25.9% had moderate frailty, and 22.5% had severe frailty. In the regression analysis, compared with those who were nonfrail, the length of ED stay was significantly longer for those with moderate frailty (odds ratio [OR] 2.13; 95% confidence interval [CI] 1.63-2.90) or severe frailty (OR 3.32; 95% CI 1.92-3.87), but the result was not significant for those with mild frailty (OR 1.65; 95% CI 1.21-2.45). ICU mortality was significantly higher among patients with mild, moderate, or severe frailty than among those who were nonfrail.

CONCLUSIONS

We found CFS score to be a predictor of length of ED stay and adverse outcomes. Accordingly, CFS evaluation can provide an idea of the length of ED stay and the likelihood of adverse outcomes.

Challenging Organizational Factors Associated With Admission Delay to Intensive Care Unit-A Novel Quality Indicator

BACKGROUND

Delays in admitting patients to the intensive care unit (ICU) can defer the timely initiation of life-sustaining therapies and invasive monitoring, jeopardizing the success of the treatment. Nevertheless, the availability of research on interventions that reduce or minimize admission delays is limited.

OBJECTIVES

The current study aimed to assess the factors related to delays in admission times of critically ill patients transferred to the ICU.

METHODS

A software was designed to follow-up, compare and measure the defined intervals of the time to admission, implemented at the ICU for 6 months. Measurements included 5 time intervals, referral department, and work shift at admission. Data from 1004 patients admitted to the ICU between July 2017 and January 2020 were analyzed in a retrospective observational study.

RESULTS

Precisely, 53.9% of total patients were referred from the hospital emergency department, and 44% were admitted during the evening shift. Significant differences were found in time intervals between shifts, showing the morning round had the longer total admission time (median: 67.8 min). Analysis showed that admission time was longer at times of full capacity compared to times of available bed (mean: 56.4 and 40.2 min, respectively; U = 68,722, p < .05). Findings demonstrated a significant shortening of time to admission after implementing a new time monitoring software by the Institutional Quality Control Commission (U  =  5072, p < .001).

CONCLUSIONS

Our study opens doors for potential studies on applying effective initiatives in critical care settings to improve patient care and outcomes. Additionally, it generates new insights regarding how clinicians and nursing teams can jointly develop and promote multidisciplinary interventions in intensive care work environments.

Flow-Sizing Critical Care Resources

OBJECTIVES

To describe the factors affecting critical care capacity and how critical care organizations (CCOs) within academic centers in the U.S. flow-size critical care resources under normal operations, strain, and surge conditions.

DATA SOURCES

PubMed, federal agency and American Hospital Association reports, and previous CCO survey results were reviewed.

STUDY SELECTION

Studies and reports of critical care bed capacity and utilization within CCOs and in the United States were selected.

DATA EXTRACTION

The Academic Leaders in the Critical Care Medicine Task Force established regular conference calls to reach a consensus on the approach of CCOs to "flow-sizing" critical care services.

DATA SYNTHESIS

The approach of CCOs to "flow-sizing" critical care is outlined. The vertical (relation to institutional resources, e.g., space allocation, equipment, personnel redistribution) and horizontal (interdepartmental, e.g., emergency department, operating room, inpatient floors) integration of critical care delivery (ICUs, rapid response) for healthcare organizations and the methods by which CCOs flow-size critical care during normal operations, strain, and surge conditions are described. The advantages, barriers, and recommendations for the rapid and efficient scaling of critical care operations via a CCO structure are explained. Comprehensive guidance and resources for the development of "flow-sizing" capability by a CCO within a healthcare organization are provided.

CONCLUSIONS

We identified and summarized the fundamental principles affecting critical care capacity. The taskforce highlighted the advantages of the CCO governance model to achieve rapid and cost-effective "flow-sizing" of critical care services and provide recommendations and resources to facilitate this capability. The relevance of a comprehensive approach to "flow-sizing" has become particularly relevant in the wake of the latest COVID-19 pandemic. In light of the growing risks of another extreme epidemic, planning for adequate capacity to confront the next critical care crisis is urgent.

Improved performance of an intensive care unit after changing the admission triage model

The aim of this study is to analyze the effect of implementing a prioritization triage model for admission to an intensive care unit on the outcome of critically ill patients. Retrospective longitudinal study of adult patients admitted to the Intensive Care Unit (ICU) carried out from January 2013 to December 2017. The primary outcome considered was vital status at hospital discharge. Patients were divided into period 1 (chronological triage) during the years 2013 and 2014 and period 2 (prioritization triage) during the years 2015-2017. A total of 1227 patients in period 1 and 2056 in period 2 were analyzed. Patients admitted in period 2 were older (59.8 years) compared to period 1 (57.3 years; p < 0.001) with less chronic diseases (13.6% vs. 19.2%; p = 0.001), and higher median APACHE II score (21.0 vs. 18.0; p < 0.001)) and TISS 28 score (28.0 vs. 27.0; p < 0.001). In period 2, patients tended to stay in the ICU for a shorter time (8.5 ± 11.8 days) compared to period 1 (9.6 ± 16.0 days; p = 0.060) and had lower mortality at ICU (32.8% vs. 36.9%; p = 0.016) and hospital discharge (44.2% vs. 47.8%; p = 0.041). The change in the triage model from a chronological model to a prioritization model resulted in improvement in the performance of the ICU and reduction in the hospital mortality rate.

Characteristics and Outcomes of Patients Requiring Repeat Intensive Care Unit Consults

Objective

To better understand the mortality and notable characteristics of patients initially denied intensive care unit (ICU) admission that are later admitted on reconsultation.

Patients and Methods

We collected data regarding all adult inpatients (n=3725) who received one or more ICU consults at an academic tertiary care hospital medical center between January 1, 2018 and October 1, 2021. We compared patients who were initially denied ICU admission and later admitted on reconsultation (C2A1, n=144) with those who were admitted after the first consultation (C1A1, n=2286) and those denied at first consult and never later admitted (C1A0, n=1295).

Results

Ten percent of patients initially rejected by the ICU were later admitted on reconsultation. There was no significant difference in the adjusted hospital death odds ratios between C1A1 and C2A1 (0.67; 95% CI 0.43-1.01; P=.11). Assessing subgroups of the C2A1 population, we found that 8.2% (n=100) of full code patients were later admitted to the ICU on reconsultation vs 23.2% (n=40) of do not attempt resuscitation patients (P<.001); 7.6% (n=77) of patients initially consulted from the emergency department were later admitted to the ICU on reconsultation vs 15.1% (n=52) of patients initially consulted from an inpatient setting (P<.001).

Conclusion

In this cohort, we demonstrated that patients admitted on repeat ICU consultation have no significant difference in mortality compared with equivalent patients admitted after the first consultation. Understanding and further exploring the consequences of these ICU reconsultations is vital to developing optimal critical care triaging practices.

Outbreak of Serratia marcescens in the Neonatal Intensive Care Unit of a Tertiary Care Hospital in Mexico

Introduction

We describe an outbreak of Serratia marcescens (S. marcescens) infection in the neonatal intensive care unit at Women's Hospital in Sinaloa, Mexico.

Methods

In April 2021, an outbreak of S. marcescens infection was identified. A case was identified as any patient who tested positive for S. marcescens and showed signs of an infectious process.

Results

S. marcescens was isolated from the blood cultures of 15 neonates with clinical signs of neonatal sepsis. Statistical analysis showed that all neonates had an invasive medical device. The problem was controlled after hospital hygiene and sanitation measures were strengthened.

Conclusion

The study provides evidence of an outbreak of nosocomial bacteremia due to the cross-transmission of S. marcescens. The findings highlight the need for hospitals to implement strict hygiene measures, especially regarding hand washing, to prevent future outbreaks.

Sepsis mortality and ICU length of stay after the implementation of an intensive care team in the emergency department

Emergency department patient boarding is associated with hospital mortality and increased hospital length of stay. The objective of the present study is to describe the impact of deploying an Intensive Care team in the ED and its association with sepsis mortality and ICU length of stay. Patients admitted to ICU through the ED with an ICD-10 CM diagnosis of sepsis were included. Preintervention and postintervention phases included 4 and 15 months, respectively. Sepsis time zero, SEP-1 compliance, and lag time from time zero to antibiotic administration were compared. Outcomes of interest were mortality and ICU LOS. 1021 septic patients were included. Sixty-six percent fulfilled compliance with 3 h SEP-1 bundle. Lag time from time zero to antibiotic administration was 75 min. Multivariate analysis showed no association between ICU team in the ED and hospital mortality (Log OR 0.94, CI 0.67-1.34; p = 0.73). The ICU team in the ED was associated with prolonged ICU LOS (Log OR 1.21, CI 1.13-1.30; p < 0.01). Septic shock and ED boarding time were associated with prolonged ICU LOS. Compliance with SEP-1 bundle was associated with its reduction. Implementation of an ICU team in the ED for the treatment of septic patients during high volume hospitalizations is not associated with a reduction of mortality or ICU LOS.

Delayed Transfer of Critically Ill Patients from Emergency Department to Intensive Care Unit

Background and aim

Delay in the transfer of critically ill patients from the emergency department (ED) to intensive care units (ICUs) may worsen clinical outcomes. This prospective, observational study was done to find the incidence of delayed transfer.

Materials and methods

After approval from the institute ethics committee and written informed consent, all patients admitted to ICU from ED over 6 months were divided into groups I and II as patients getting transferred to ICU within 30 minutes of the decision or not, respectively. The factors affecting the immediate transfer and clinical outcome of all patients were noted. Monthly feedback was given to the ED team.

Results

Out of 52 ICU admissions from ED, 35 (67.3%) patients were not transferred within 30 minutes, and the most frequent factor preventing immediate transfer was ED-related (54%). A statistically significant difference was found in acute physiology and chronic health evaluation (APACHE II) score, clinical deterioration during transfer, longer duration of mechanical ventilation and length of stay, and higher mortality with patients transferred immediately to ICU. A reduction of 42.6% was noted in transfer time from the first month to the last month of study.

Conclusion

The incidence of delayed transfer of patients from ED to ICU was 67.3% with ED-related factors being the most frequent cause of delay (54.2%).

How to cite this article

Bosco S, Sahni N, Jain A, Arora P, Raj V, Yaddanapudi L. Delayed Transfer of Critically Ill Patients from Emergency Department to Intensive Care Unit. Indian J Crit Care Med 2023;27(8):580-582.

The Association between Emergency Department Length of Stay and In-Hospital Mortality in Older Patients Using Machine Learning: An Observational Cohort Study

The association between emergency department (ED) length of stay (EDLOS) with in-hospital mortality (IHM) in older patients remains unclear. This retrospective study aims to delineate the relationship between EDLOS and IHM in elderly patients. From the ED patients (n = 383,586) who visited an urban academic tertiary care medical center from January 2010 to December 2016, 78,478 older patients (age ≥60 years) were identified and stratified into three age subgroups: 60-74 (early elderly), 75-89 (late elderly), and ≥90 years (longevous elderly). We applied multiple machine learning approaches to identify the risk correlation trends between EDLOS and IHM, as well as boarding time (BT) and IHM. The incidence of IHM increased with age: 60-74 (2.7%), 75-89 (4.5%), and ≥90 years (6.3%). The best area under the receiver operating characteristic curve was obtained by Light Gradient Boosting Machine model for age groups 60-74, 75-89, and ≥90 years, which were 0.892 (95% CI, 0.870-0.916), 0.886 (95% CI, 0.861-0.911), and 0.838 (95% CI, 0.782-0.887), respectively. Our study showed that EDLOS and BT were statistically correlated with IHM (p < 0.001), and a significantly higher risk of IHM was found in low EDLOS and high BT. The flagged rate of quality assurance issues was higher in lower EDLOS ≤1 h (9.96%) vs. higher EDLOS 7 h <t≤ 8 h (1.84%). Special attention should be given to patients admitted after a short stay in the ED and a long BT, and new concepts of ED care processes including specific areas and teams dedicated to older patients care could be proposed to policymakers.

ICU without borders

Critical illness is a continuum, but patient care is often fragmented. Value-based critical care focuses on the overall health of the patient, not on an episode of care. The "ICU without borders" model incorporates a concept where members of the critical care team are involved in the management of patients from the onset of critical illness until recovery and beyond. In this paper, we summarise the potential benefits and challenges to patients, families, staff and the wider healthcare system and list some essential requirements, including a tight governance framework, advanced technologies, investment and trust. We also argue that "ICU without borders" should be viewed as a bi-directional model, allowing extended visiting hours, giving patients and families direct access to experienced critical care staff and offering mutual aid when needed.

The Association Between Time From Emergency Department Visit to ICU Admission and Mortality in Patients With Sepsis

The Surviving Sepsis Campaign Guidelines 2021 recommends that adult patients with sepsis requiring intensive care should be admitted to the ICU within 6 hours of their emergency department (ED) visits. However, there is limited evidence on whether 6 hours is the best target time for compliance with the sepsis bundle. We aimed to investigate the association between time from ED visits to ICU admission (i.e., ED length of stay [ED-LOS]) and mortality and identify the optimal ED-LOS for patients with sepsis.

DESIGN

Retrospective cohort study.

SETTING

The Medical Information Mart for Intensive Care Emergency Department and Medical Information Mart for Intensive Care IV databases.

PATIENTS

Adult patients (≥ 18 yr old) who were transferred from the ED to the ICU and subsequently diagnosed with sepsis based on the Sepsis-3 criteria within 24 hours of ICU admission.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Among 1,849 patients with sepsis, we found a disproportionally higher mortality rate in patients immediately admitted to the ICU (e.g., < 2 hr). When using ED-LOS as a continuous variable, ED-LOS was not significantly associated with 28-day mortality (adjusted odds ratio [OR] per hour increase, 1.04; 95% CI, 0.96-1.13; p = 0.3) after an adjustment for potential confounders (e.g., demographics, triage vital signs, and laboratory results) in the multivariable analysis. However, when we categorized all patients into time quartiles (ED-LOS: < 3.3 hr, 3.3-4.5 hr, 4.6-6.1 hr, and > 6.1 hr), patients in the higher time quartiles (e.g., 3.3-4.5 hr) had higher 28-day mortality compared with those in the lowest time quartile (< 3.3 hr) (e.g., adjusted OR for patients in the second time quartile [3.3-4.5 hr] 1.59; 95% CI, 1.03-2.46; p = 0.04).

CONCLUSIONS

Earlier admission to the ICU (e.g., within 3.3 hr of ED visits) was associated with lower 28-day mortality in patients with sepsis. Our findings suggest patients with sepsis who require intensive care may benefit from a more immediate ICU admission than 6 hours.

Association between the timing of ICU admission and mortality in patients with hospital-onset sepsis: a nationwide prospective cohort study

BACKGROUND

Based on sparse evidence, the current Surviving Sepsis Campaign guideline suggests that critically ill patients with sepsis be admitted to the intensive care unit (ICU) within 6 h. However, limited ICU bed availability often makes immediate transfer difficult, and it is unclear whether all patients will benefit from early admission to the ICU. Therefore, the purpose of this study was to determine the association between the timing of ICU admission and mortality in patients with hospital-onset sepsis.

METHODS

This nationwide prospective cohort study analyzed patients with hospital-onset sepsis admitted to the ICUs of 19 tertiary hospitals between September 2019 and December 2020. ICU admission was classified as either early (within 6 h) or delayed (beyond 6 h). The primary outcome of in-hospital mortality was compared using logistic regression adjusted for key prognostic factors in the unmatched and 1:1 propensity-score-matched cohorts. Subgroup and interaction analyses assessed whether in-hospital mortality varied according to baseline characteristics.

RESULTS

A total of 470 and 286 patients were included in the early and delayed admission groups, respectively. Early admission to the ICU did not significantly result in lower in-hospital mortality in both the unmatched (adjusted odds ratio [aOR], 1.35; 95% confidence interval [CI], 0.99-1.85) and matched cohorts (aOR, 1.38; 95% CI, 0.94-2.02). Subgroup analyses showed that patients with increasing lactate levels (aOR, 2.10; 95% CI, 1.37-3.23; P for interaction = 0.003), septic shock (aOR, 2.06; 95% CI, 1.31-3.22; P for interaction = 0.019), and those who needed mechanical ventilation (aOR, 1.92; 95% CI, 1.24-2.96; P for interaction = 0.027) or vasopressor support (aOR, 1.69; 95% CI, 1.17-2.44; P for interaction = 0.042) on the day of ICU admission had a higher risk of mortality with delayed admission.

CONCLUSIONS

Among patients with hospital-onset sepsis, in-hospital mortality did not differ significantly between those with early and delayed ICU admission. However, as early intensive care may benefit those with increasing lactate levels, septic shock, and those who require vasopressors or ventilatory support, admission to the ICU within 6 h should be considered for these subsets of patients.

The Gap Between Daily Hospital Bed Supply and Demand: Design, Implementation, and Impact of Data-Driven Pre-Noon Discharge Targets

BACKGROUND

Hospitals have sought to increase pre-noon discharges to improve capacity, although evidence is mixed on the impact of these initiatives. Past interventions have not quantified the daily gap between morning bed supply and demand. The authors quantified this gap and applied the pre-noon data to target a pre-noon discharge initiative.

METHODS

The study was conducted at a large hospital and included adult and pediatric medical/surgical wards. The researchers calculated the difference between the average cumulative bed requests and transfers in for each hour of the day in 2018, the year prior to the intervention. In 2019 an intervention on six adult general medical and two surgical wards was implemented. Eight intervention and 14 nonintervention wards were compared to determine the change in average cumulative pre-noon discharges. The change in average hospital length of stay (LOS) and 30-day readmissions was also calculated.

RESULTS

The average daily cumulative gap by noon between bed supply and demand across all general care wards was 32.1 beds (per ward average, 1.3 beds). On intervention wards, mean pre-noon discharges increased from 4.7 to 6.7 (p < 0.0000) compared with the nonintervention wards 14.0 vs. 14.6 (p = 0.19877). On intervention wards, average LOS decreased from 6.9 to 6.4 days (p < 0.001) and readmission rates were 14.3% vs 13.9% (p = 0.3490).

CONCLUSION

The gap between daily hospital bed supply and demand can be quantified and applied to create pre-noon discharge targets. In an intervention using these targets, researchers observed an increase in morning discharges, a decrease in LOS, and no significant change in readmissions.

The Effect of Continuous Versus Periodic Vital Sign Monitoring on Disease Severity of Patients with an Unplanned ICU Transfer

Continuous vital sign monitoring (CM) may detect ward patient's deterioration earlier than periodic monitoring. This could result in timely ICU transfers or in a transfer delay due to misperceived higher level of care on the ward. The primary objective of this study was to compare patient's disease severity upon unplanned ICU transfer, before and after CM implementation. We included a one-year period before and after CM implementation between August 1, 2017 - July 31, 2019. Before implementation, surgical and internal medicine patients' vital signs were periodically monitored, compared to continuous monitoring with wireless linkage to hospital systems after implementation. In both periods the same early warning score (EWS) protocol was in place. Primary outcome was disease severity scores upon ICU transfer. Secondary outcomes were ICU and hospital length of stay, incidence of mechanical ventilation and ICU mortality. In the two one-year periods 93 and 59 unplanned ICU transfer episodes were included, respectively. Median SOFA (3 (2-6) vs 4 (2-7), p = .574), APACHE II (17 (14-20) vs 16 (14-21), p = .824) and APACHE IV (59 (46-67) vs 50 (36-65), p = .187) were comparable between both periods, as were the median ICU LOS (3.0 (1.7-5.8) vs 3.1 (1.6-6.1), p.962), hospital LOS (23.6 (11.5-38.0) vs 19 (13.9-39.2), p = .880), incidence of mechanical ventilation (28 (47%) vs 22 (54%), p.490), and ICU mortality (11 (13%) vs 10 (19%), p.420). This study shows no difference in disease severity upon unplanned ICU transfer after CM implementation for patients who have deteriorated on the ward.

Sepsis in Brazilian emergency departments: a prospective multicenter observational study

We aimed to assess the prevalence, patient allocation adequacy, and mortality of adults with sepsis in Brazilian emergency departments (ED) in a point-prevalence 3-day investigation of patients with sepsis who presented to the ED and those who remained there due to inadequate allocation. Allocation was considered adequate if the patient was transferred to the intensive care unit (ICU), ward, or remained in the ED without ICU admission requests. Prevalence was estimated using the total ED visit number. Prognostic factors were assessed with logistic regression. Of 33,902 ED visits in 74 institutions, 183 were acute admissions (prevalence: 5.4 sepsis per 1000 visits [95% confidence interval (CI): 4.6-6.2)], and 148 were already in the ED; totaling 331 patients. Hospital mortality was 32% (103/322, 95% CI 23.0-51.0). Age (odds ratio (OR) 1.22 [95% CI 1.10-1.37]), Sequential Organ Failure Assessment (SOFA) score (OR 1.41 [95% CI 1.28-1.57]), healthcare-associated infections (OR 2.59 [95% CI 1.24-5.50]) and low-resource institution admission (OR 2.65 [95% CI 1.07-6.90]) were associated with higher mortality. Accredited institutions (OR 0.42 [95% CI 0.21-0.86]) had lower mortality rates. Allocation within 24 h was adequate in only 52.8% of patients (public hospitals: 42.4% (81/190) vs. private institutions: 67.4% (89/132, p < 0.001) with 39.2% (74/189) of public hospital patients remaining in the ED until discharge, of whom 55.4% (41/74) died. Sepsis exerts high burden and mortality in Brazilian EDs with frequent inadequate allocation. Modifiable factors, such as resources and quality of care, are associated with reduced mortality.

Frontline Nurses' clinical judgment in recognizing, understanding, and responding to patient deterioration: A qualitative study

BACKGROUND

Early warning systems and rapid response teams have been widely implemented in hospitals worldwide to facilitate early recognition and response to patient deterioration. Unfortunately, evidence suggests that these interventions have made little impact on unexpected cardiac or respiratory arrest, hospital mortality, unplanned admission to intensive care units, or hospital length of stay. These programs depend on nurses recognizing at risk patients and initiating a timely response. Although physiologic abnormalities commonly precede serious adverse events, nurses often fail to recognize or respond effectively. Clinical judgment is a critical component in the effective response to deterioration, yet little is known about factors that influence nurses' clinical judgment in these situations. Noticing, interpreting, and responding are aspects of clinical judgment and are essential to preventing further patient deterioration and serious adverse events.

OBJECTIVE

To describe medical-surgical nurses' perceptions of factors that influenced their clinical judgment in situations of patient deterioration.

DESIGN

A qualitative descriptive design using individual, semi-structured interviews. Tanner's Clinical Judgment Model served as the framework for interview questions and data analysis.

PARTICIPANTS

A purposive sample of 20 medical-surgical registered nurses were recruited from 10 adult medical-surgical units at an academic medical center hospital in the United States.

METHODS

Telephone interviews occurred between March and July 2018. A directed approach to content analysis was used to code the transcribed data and identify themes.

RESULTS

Eight themes related to each aspect of clinical judgment emerged from the analysis: Knowing the patient, Experience matters, Lots of small points where the system can fail, Making sense of the data, Something doesn't go together, Caught in the middle, Culture of teamwork, and Increased nursing workload. An overarching theme was Nurses' keen sense of responsibility. Findings revealed that factors within the nurse, the patient, and the work environment influence each component of noticing, interpreting, and initiating an effective response to deteriorating patients.

CONCLUSIONS

Findings have implications for health care systems regarding interventions to support timely recognition and response to deterioration. Nurses' clinical judgment and factors that influence each aspect (noticing, interpreting, and responding) should be a key consideration in organizational efforts to improve the overall response to patient deterioration. Research is needed to enhance understanding of the contextual factors that impact nurses' clinical judgment to inform interventions to support timely recognition and response.

COVID-19 does not influence functional status after ARDS therapy

RATIONALE

Health-related quality of life after surviving acute respiratory distress syndrome has come into focus in recent years, especially during the coronavirus disease 2019 pandemic.

OBJECTIVES

A total of 144 patients with acute respiratory distress syndrome caused by COVID-19 or of other origin were recruited in a randomized multicenter trial.

METHODS

Clinical data during intensive care treatment and data up to 180 days after study inclusion were collected. Changes in the Sequential Organ Failure Assessment score were used to quantify disease severity. Disability was assessed using the Barthel index on days 1, 28, 90, and 180.

MEASUREMENTS

Mortality rate and morbidity after 180 days were compared between patients with and without COVID-19. Independent risk factors associated with high disability were identified using a binary logistic regression.

MAIN RESULTS

The SOFA score at day 5 was an independent risk factor for high disability in both groups, and score dynamic within the first 5 days significantly impacted disability in the non-COVID group. Mortality after 180 days and impairment measured by the Barthel index did not differ between patients with and without COVID-19.

CONCLUSIONS

Resolution of organ dysfunction within the first 5 days significantly impacts long-term morbidity. Acute respiratory distress syndrome caused by COVID-19 was not associated with increased mortality or morbidity.

Adaptive Risk Modeling: Improving Risk Assessment of Geriatric Hip Fracture Patients Throughout their Hospitalization

INTRODUCTION

The purpose of this study was twofold: 1. To assess how adaptive modeling, accounting for development of inpatient complications, affects the predictive capacity of the risk tool to predict inpatient mortality for a cohort of geriatric hip fracture patients. 2. To compare how risk triaging of secondary outcomes is affected by adaptive modeling. We hypothesize that adaptive modeling will improve the predictive capacity of the model and improve the ability to risk triage secondary outcomes.

METHODS

Between October 2014-August 2021, 2421 patients >55 years old treated for hip fracture obtained through low-energy mechanisms were analyzed for demographics, injury details and hospital quality measures. The baseline Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) tool for hip fractures (STTGMA_HIP) was calculated in the emergency department setting. A new mortality risk score (STTGMA_{HIP_ADPTV}) was created including inpatient complications. Each models' predictive ability was compared using DeLong's test. Patients were grouped into quartiles based on their respective STTGMA_{HIP_ADPTV} and comparative analyses were conducted.

RESULTS

AUROC comparison demonstrated STTGMA_{HIP_ADPTV} significantly improved the predictive capacity for inpatient mortality compared to STTGMA_HIP (p < 0.01). STTGMA_{HIP_ADPTV} correctly triaged 80% and 64% of high-risk patients with inpatient and 30-day mortality compared to 64% and 57% for STTGMA_HIP. STTGMA_{HIP_ADPTV} quartile stratification demonstrated that the highest risk cohort had the worst mortality outcomes and hospital quality measures. Patients whose risk classification changed from minimal risk using STTGMA_HIP to high risk using STTGMA_{HIP_ADPTV} experienced the highest rate of mortality, readmission, ICU admission, with longer lengths of stay and higher hospital costs.

DISCUSSION

Adaptive modeling accounting for inpatient complications improves the predictive capacity and risk triaging of the STTGMA_HIP tool. Real-time modulation of a patient's mortality risk profile can inform their requisite level of medical management to improve the quality and value of care as patients progress through their index hospitalization. STTGMA_{HIP_ADPTV} can better identify patients at risk for developing complications whose mortality and readmission risk profile increase significantly, allowing their new risk classification to inform higher levels of care. While this may increase length of stay and total costs, it may improve outcomes in both the short and long-term.

LEVEL OF EVIDENCE

III.

A multidisciplinary safety briefing for acutely ill and deteriorating patients: A quality improvement project

BACKGROUND

Safety briefings can help promoting situational awareness, interprofessional communication and improve patient safety.

LOCAL PROBLEM

A clinical survey highlighted that 90% of the participants including the medical team and the critical care outreach team nurses perceived the meeting for escalating acutely ill and deteriorating patients during the out-of-hours period (20.00 to 08.00) to have unconstructive and unwelcoming atmosphere with belittling, hostility and unhelpful criticisms. The participants reported that the communication across teams lacked in structure and clear information given; but staff also self-reported lacking confidence in communicating key issues.

METHOD

A quality improvement project with Plan-Do-Study-Act was adopted to design and implement a dedicated multidisciplinary safety briefing with a structured format.

RESULTS

The multidisciplinary safety briefing was to 90% of clinicians, and it took a median of 10 min to complete. Delayed referrals to the critical care outreach team were reduced by 46%. Positive changes included increased situational awareness and clearer communication across teams. Barriers identified were variable usage and need for face-to-face presence. Considering all the findings and the time constraint during the SARS-CoV-2 pandemic, we changed to a telephonic safety briefing directly to the team leaders.

CONCLUSION

A structured multidisciplinary safety briefing can improve patient safety and support management of deteriorating and acutely ill patients on the wards during the out-of-hours period.

Arriving Safely: Decreasing Rapid Escalations in Care for Incoming Transported Pediatric Patients

Accurate inpatient placement at the level of care needed for incoming transported patients can present challenges that may result in a rapid escalation in care following admission to the general inpatient unit. The Pediatric Early Warning System (PEWS) score is useful for early recognition of clinical deterioration. Therefore, we aimed to reduce rapid escalations in care for incoming transported patients via the implementation of an escalation algorithm with a goal of 80% PEWS score completion rate during transport within 6 months.

Methods

We created an escalation algorithm utilizing PEWS scores and direct lines of communication between emergency medical technicians and receiving physicians. Audit and feedback increased the adoption of the process. We defined rapid escalations as transfer to a higher level of care within 6 hours of admission.

Results

PEWS score completion increased from a mean of 48% to 70%. This result varied by emergency medical technician crew level of care. Eleven percent (n = 114) of PEWS scores required physician notification, 20% (n = 23) of which resulted in interventions en route. There were no differences in rapid escalation rates over time, but it remained low at <2% of all incoming transported patients. Some crew members report improved communication with hospital providers and feel more empowered to speak up when a patient's assessment is not as expected following algorithm implementation.

Conclusions

This project improved PEWS score completion and maintained a low rate of rapid escalations of care among incoming transfers.

Length-of-Stay in the Emergency Department and In-Hospital Mortality: A Systematic Review and Meta-Analysis

The effect of emergency department (ED) length of stay (EDLOS) on in-hospital mortality (IHM) remains unclear. The aim of this systematic review and meta-analysis was to determine the association between EDLOS and IHM. We searched the PubMed, Medline, Embase, Web of Science, Cochrane Controlled Register of Trials, CINAHL, PsycInfo, and Scopus databases from their inception until 14−15 January 2022. We included studies reporting the association between EDLOS and IHM. A total of 11,337 references were identified, and 52 studies (total of 1,718,518 ED patients) were included in the systematic review and 33 in the meta-analysis. A statistically significant association between EDLOS and IHM was observed for EDLOS over 24 h in patients admitted to an intensive care unit (ICU) (OR = 1.396, 95% confidence interval [CI]: 1.147 to 1.701; p < 0.001, I2 = 0%) and for low EDLOS in non-ICU-admitted patients (OR = 0.583, 95% CI: 0.453 to 0.745; p < 0.001, I2 = 0%). No associations were detected for the other cut-offs. Our findings suggest that there is an association between IHM low EDLOS and EDLOS exceeding 24 h and IHM. Long stays in the ED should not be allowed and special attention should be given to patients admitted after a short stay in the ED.

Implementation of a medical intensive care team in the emergency department of a tertiary medical center in the USA

OBJECTIVE

Critically ill patients boarding in the ED have higher mortality rates. Several strategies have been implemented to deliver care to boarding patients. Our institution opted for a strategy consisting on deploying an Intensive Care team in the ED. This article reports outcomes before-and-after implementation of that team.

METHODS

On November 2020, a Medical Intensive Care Team was deployed in the ED. The team performed consultations for ICU patients boarding in the ED. A retrospective analysis of critically ill patients arriving to the ED before-and-after team implementation was performed. Outcome data were reviewed. Direct hospitalization costs per patient, and direct costs per department were assessed. Wilcoxon rank sum and Chisq-test were utilized to compare differences pre- and post-implementation. Multivariate analyses to model outcomes toward pre- and post-implementation and other variables were performed.

RESULTS

1,828 and 3,272 patients were included in the pre- and post-intervention groups. ICU LOS (days) pre- and post-intervention were 3 (1,6) and 3 (1,6), respectively (p = 0.41). ICU readmission rates were 6.7% pre-intervention and 7.4% post-intervention (p = 0.37). Total direct costs were US$ 19,928 (11,006, 37,815) and US$ 15,795 (9016, 28,993), respectively (p < 0.01). Multivariate analysis showed no association between team deployment and ICU LOS or readmission. However, there was association between its implementation and hospitalization cost reduction per patient of US$ 7,171.

CONCLUSION

The implementation of a Medical Intensive Care team in the ED is not associated with a reduction of ICU LOS or ICU readmission. Nevertheless, its implementation is associated with a reduction of hospitalization costs.

Risk Factors for Longer Pediatric Intensive Care Unit Length of Stay Among Children Who Required Escalation of Care Within 24 Hours of Admission

OBJECTIVE

Children who require early escalation of care (EOC) to the pediatric intensive care unit (PICU) after floor admission have higher mortality and increased hospital length of stay (LOS) as compared with direct emergency department (ED) admissions. This study was designed to identify subgroups of patients within this cohort (EOC to PICU within 24 hours of hospital admission) who have worse outcomes (actual PICU LOS [aLOS] > predicted PICU LOS [pLOS]).

METHODS

This was a retrospective single-center cohort study. Patients who required EOC to PICU from January 2015 to December 2019 within 24 hours of admission were included. Postoperative patients, missing cause of EOC, and mortality were excluded. Predicted LOS was calculated based on Pediatric Risk of Mortality scores. Patients with aLOS > pLOS (group A) were compared with patients with aLOS ≤ pLOS (group B). Multivariable logistic regression was performed to adjust for confounders.

RESULTS

Of 587 patients transferred to PICU after hospital admission during the study period, 286 patients met the study criteria (group A, n = 69; group B, n = 217). The 2 groups were similar in age, race, the severity of illness, and ED vitals and therapies. A higher proportion of patients in group B had EOC ≤ 6 hours of admission (51.1% vs 36.2%, P = 0.03), and a higher proportion in group A required Mechanical ventilation (56% vs 34%, P = 0.01). On multivariable regression, patients who required EOC to PICU after 6 hours after admission (adjusted odds ratio, 2.27; 95% confidence interval [CI] 1.2, 4.0), p,<0.01) and patients admitted to the floor from referral hospitals (adjusted odds ratio, 1.8; 95% confidence interval, 1.0-3.2), P = 0.04) had higher risk of greater than PLOS.

CONCLUSIONS

Among patients who required EOC to PICU, risk factors associated with aLOS > pLOS were patients who required EOC to PICU longer than 6 hours after admission to the hospital and patients admitted to the floor as a transfer from referral hospitals.

Examination of Impact of After-Hours Admissions on Hospital Resource Use, Patient Outcomes, and Costs

Background. Nighttime and weekends in hospital and intensive care unit (ICU) contexts are thought to present a greater risk for adverse events than daytime admissions. Although some studies exist comparing admission time with patient outcomes, the results are contradictory. No studies currently exist comparing costs with the time of admission. We investigated the differences in-hospital mortality, ICU length of stay, ICU mortality, and cost between daytime and nighttime admissions. Methods. All adult patients (≥18 years of age) admitted to a large academic medical-surgical ICU between 2011 and 2015 were included. Admission cohorts were defined as daytime (8:00–16:59) or nighttime (17:00–07:59). Student’s t-tests and chi-squared tests were used to test for associations between days spent in the ICU, days on mechanical ventilation, comorbidities, diagnoses, and cohort membership. Regression analysis was used to test for associations between patient and hospitalization characteristics and in-hospital mortality and total ICU costs. Results. The majority of admissions occurred during nighttime hours (69.5%) with no difference in the overall Elixhauser comorbidity score between groups ( $p=0.22$ ). Overall ICU length of stay was 7.96 days for daytime admissions compared to 7.07 days ( $p=0.001$ ) for patients admitted during nighttime hours. Overall mortality was significantly higher in daytime admissions (22.5% vs 20.6, $p=0.012$ ); however, ICU mortality was not different. The average MODS was 2.9 with those admitted during the daytime having a significantly higher MODS (3.0, $p=0.046$ ). Total ICU cost was significantly higher for daytime admissions ( $p=0.003$ ). Adjusted ICU mortality was similar in both groups despite an increased rate of adverse events for nighttime admissions. Daytime admissions were associated with increased cost. There was no difference in all hospital total cost or all hospital direct cost between groups. These findings are likely due to the higher severity of illness in daytime admissions. Conclusion. Daytime admissions were associated with a higher severity of illness, mortality rate, and ICU cost. To further account for the effect of staffing differences during off-hours, it may be beneficial to compare weekday and weeknight admission times with associated mortality rates.