Association between Shock Index and Emergency Department Cardiac Arrest

Background. In the emergency department (ED), early identification of patients at risk of cardiac arrest is paramount, especially in the context of overcrowding. The shock index (SI) is defined as the ratio of heart rate to systolic blood pressure. It is a tool used for predicting the prognosis of critically ill and injured patients. In this study, we have discussed the relationship between SI and cardiac arrest in the ED. Methods. Patients who experienced cardiac arrest in the ED were classified into two groups, SI ≥ 0.9 and < 0.9, according to their triage vital signs. The association between SI ≥ 0.9 and in-hospital mortality was analyzed in five different etiologies of cardiac arrest, including hypoxia, cardiac cause, bleeding, sepsis, and other metabolic problems. Results. In total, 3,313 patients experienced cardiac arrest in the ED. Among them, 1,909 (57.6%) had a SI of ≥0.9. The incidence of SI ≥ 0.9 in the five etiologies was 43.5% (hypoxia), 58.1% (cardiac cause), 56.1% (bleeding), 58.0% (sepsis), and 65.5% (other metabolic problems). SI was associated with in-hospital mortality (adjusted odds ratio (aOR), 1.6; 95% confidence interval (CI), 1.5–1.8). The aOR (CI) in the five etiologies was 1.3 (1.1–1.6) for hypoxia, 1.8 (1.6–2.1) for cardiac cause, 1.3 (0.98–1.7) for bleeding, 1.3 (1.03–1.6) for sepsis, and 1.9 (1.5–2.1) for other metabolic problems. Conclusion. More than half of the patients who experienced cardiac arrest in the ED had a SI ≥ 0.9. The SI was also associated with in-hospital mortality after cardiac arrest in the ED. SI maybe used as a screening tool to identify patients at risk of cardiac arrest in the ED and a predictor of mortality in those experiencing cardiac arrest in the ED.

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P131: Emergency department falls risk management screening tool comparison

CJEM ◽

10.1017/cem.2016.305 ◽

2016 ◽

Vol 18 (S1) ◽

pp. S121-S122

Author(s):

R. Tomlinson ◽

T. Yokota ◽

P. Jaggi ◽

C. Kilburn ◽

D. Bakken ◽

...

Keyword(s):

At Risk ◽

Emergency Department ◽

Risk Management ◽

Fall Risk ◽

Screening Tool ◽

Assessment Tool ◽

Tertiary Care ◽

Screening Tools ◽

Procedural Sedation ◽

Patients At Risk

Introduction: Emergency Department (ED) fall risk screening has been newly implemented in Alberta based on Accreditation Canada requirements. Two existing inpatient tools failed to include certain ED risk conditions. One tool graded unconsciousness as no risk for falling, and neither considered intoxication or sedation. This led to the development of a new fall risk management screening tool, the FRM (Tool1). This study compared Tool1 with inpatient utilized Schmid Fall Risk Assessment Tool (Tool2) and the validated Hendrich II Fall Risk Model (Tool3). Methods: Patients (≥17 years old) in a tertiary care adult ED with any of the following; history of falling in the last 12 months, elderly/frail, incontinence, impaired gait, mobility assist device, confusion/disorientation, procedural sedation, intoxication/sedated, or unconscious were included. Forms were randomized to score patients using different paired screening tools: Tool1 paired with either Tool2 or Tool3. Percent agreement (PA) between the tools based on identification of a patient at either risk/no risk for falling; higher PA indicating more tool homogeneity. Results: A total of 928 screening forms were completed within our 8-week study period; 452 and 443 comparing Tool1 to Tool2 and Tool1 to Tool3, respectively. Thirty-two forms included only Tool1 scores, excluding them from comparative analysis. The average patient age (n=895) was 64.8±21.4 years. Tool1 identified 66.4% of patients at risk, whereas Tool2 and Tool3 identified only 19.2% and 31.4%, respectively. Tool1 and 2 had a PA of 50.2%, whereas Tool1 and Tool3 had a PA of 65.9%. Conclusion: The FRM tool had higher agreement with the validated assessment tool, identifying patients at risk for falling but better identified patients presenting with intoxication, need for procedural sedation and unconsciousness. The other tools generally miss these common ED conditions, putting these patients at risk. Validation and reliability assessments of the FRM tool are warranted.

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Examining the utility of the Hamilton early warning scores (HEWS) at triage: Retrospective pilot study in a Canadian emergency department

CJEM ◽

10.1017/cem.2017.21 ◽

2017 ◽

Vol 20 (2) ◽

pp. 266-274 ◽

Cited By ~ 6

Author(s):

Steven Skitch ◽

Benjamin Tam ◽

Michael Xu ◽

Laura McInnis ◽

Anthony Vu ◽

...

Keyword(s):

At Risk ◽

Emergency Department ◽

Early Warning ◽

Vital Signs ◽

Roc Curves ◽

Early Warning Score ◽

Critical Event ◽

Discriminative Ability ◽

Early Warning Scores ◽

Patients At Risk

ABSTRACTObjectivesEarly warning scores use vital signs to identify patients at risk of critical illness. The current study examines the Hamilton Early Warning Score (HEWS) at emergency department (ED) triage among patients who experienced a critical event during their hospitalization. HEWS was also evaluated as a predictor of sepsis.MethodsThe study population included admissions to two hospitals over a 6-month period. Cases experienced a critical event defined by unplanned intensive care unit admission, cardiopulmonary resuscitation, or death. Controls were randomly selected from the database in a 2-to-1 ratio to match cases on the burden of comorbid illness. Receiver operating characteristic (ROC) curves were used to evaluate HEWS as a predictor of the likelihood of critical deterioration and sepsis.ResultsThe sample included 845 patients, of whom 270 experienced a critical event; 89 patients were excluded because of missing vitals. An ROC analysis indicated that HEWS at ED triage had poor discriminative ability for predicting the likelihood of experiencing a critical event 0.62 (95% CI 0.58-0.66). HEWS had a fair discriminative ability for meeting criteria for sepsis 0.77 (95% CI 0.72-0.82) and good discriminative ability for predicting the occurrence of a critical event among septic patients 0.82 (95% CI 0.75-0.90).ConclusionThis study indicates that HEWS at ED triage has limited utility for identifying patients at risk of experiencing a critical event. However, HEWS may allow earlier identification of septic patients. Prospective studies are needed to further delineate the utility of the HEWS to identify septic patients in the ED.

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P120: Exploring the utility of the Hamilton early warning score at triage: pilot study in a Canadian emergency department

CJEM ◽

10.1017/cem.2016.295 ◽

2016 ◽

Vol 18 (S1) ◽

pp. S118-S118

Author(s):

S. Skitch ◽

L. McInnis ◽

A. Vu ◽

B. Tam ◽

M. Xu ◽

...

Keyword(s):

At Risk ◽

Emergency Department ◽

Early Warning ◽

Tertiary Care ◽

Vital Signs ◽

Early Warning Score ◽

Critical Event ◽

Likelihood Ratios ◽

Discriminative Ability ◽

Patients At Risk

Introduction: Early warning scores (EWS) use vital signs to identify patients at risk of critical events as defined by unplanned intensive care unit (ICU) admission, cardiopulmonary resuscitation (CPR), or death. Systems that combine an EWS with a ICU outreach team can improve hospital survival and cardiac arrest rates. Although initially developed for use in ward patients, evidence suggests that EWS are useful in emergency department (ED) patients and may aid in the earlier identification of sepsis. The Hamilton Early Warning Score (HEWS) was recently developed as part of quality improvement process in our health system. The current study examined HEWS at ED triage among a cohort of patients who experienced a critical event during their hospitalization. HEWS were also evaluated as a predictor of sepsis. Methods: Patient were selected from a database of patients admitted to a medical or surgical ward at two tertiary care hospitals over a six-month period. Cases were patients who experienced a critical event during admission and were admitted via the ED. Controls were randomly selected from the database in a two-to-one ratio using an algorithm to match cases based upon burden of comorbid illness. Receiver operator curves (ROC) and likelihood ratios were used to evaluate HEWS at ED triage as a predictor of likelihood of critical deterioration and sepsis. Results: The sample included 845 patients of whom 267 experienced a critical event. The median time to occurrence of critical event from admission was 124 hours. ROC analysis indicated that HEWS at ED triage had poor discriminative ability for predicting likelihood of experiencing a critical event 0.63 [95%CI: 0.58-0.67]. HEWS had fair discriminative ability for predicting likelihood of meeting criteria for sepsis 0.75 [95%CI: 0.71-0.80], and good discriminative ability for predicting likelihood of experiencing a critical event among patients meeting criteria for sepsis 0.80 [95%CI: 0.74-0.86]. Conclusion: This retrospective study indicates that HEWS at ED triage has limited utility for identifying patients at risk of experiencing a critical event. This may be because deterioration commonly occurred days after admission. However, HEWS may have utility as tool for aiding earlier identification of critically ill septic patients. Prospective studies are needed to further delineate the utility of the HEWS in the ED.

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P036: A comprehensive quality improvement initiative to prevent falls in the emergency department

CJEM ◽

10.1017/cem.2017.238 ◽

2017 ◽

Vol 19 (S1) ◽

pp. S90

Author(s):

P. Samuel ◽

J. Park ◽

F. Muckle ◽

J. Lexchin ◽

S. Mehta ◽

...

Keyword(s):

At Risk ◽

Emergency Department ◽

Quality Improvement ◽

Literature Review ◽

Fall Risk ◽

Screening Tool ◽

Risk Screening ◽

Constructive Feedback ◽

Patients At Risk ◽

Fall Risk Screening

Introduction: Patients from all population groups visit the emergency department (ED), with increasing visits by elderly patients. Patient falls in the ED are a significant safety concern, and they can lead to serious injuries and worse outcomes. Toronto Western Hospital’s ED Quality Improvement (QI) team identified as a problem our assessment and management of patients at risk for falls. The aim of this project was to develop a comprehensive and standardized approach to patients at risk of falls in the ED, including implementing timely interventions for fall prevention. Methods: A literature review of existing tools was completed to develop our own reliable and valid fall risk screening tool for ED patients. QI methods were used to devise a comprehensive strategy starting with detection at triage and implementation of action-driven steps at the bedside, through multiple PDSA cycles, randomized audits, surveys, and education. Repeated measurements were undergone throughout the project, as were staff satisfaction surveys. Results: The chart audits showed a five-fold increase in the completion rate of the fall risk screening tool in the ED by the end of the QI initiative (from 10% to 50%). Constructive feedback by an engaged team of nurses was used to iteratively improve the tool, and there was mostly positive feedback on it after various PDSA cycles were completed. The various component of this novel and useful ED-based falls screening tool and bundle will be presented in tables and figures for other leaders to replicate in their EDs. Conclusion: We developed a completely new ED-specific fall risk screening tool through literature review, front-line provider feedback, and iterative PDSA cycles. It was used for the identification, prevention, and management of ED patients with fall risk. We also contributed to a positive change in the culture of a busy ED environment towards the promotion of patient safety. Education and feedback continue to be provided to the ED nurses for reflective practice, and we hope to continue to improve our tool and to share it with other EDs.

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