Accuracy of Emergency Department Nurse Triage Level Designation A

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Accuracy of Emergency Department Nurse TriageLevel Designation and Delay in Care of Patientswith Symptoms Suggestive of Acute MyocardialInfarctionSusan S. SammonsGeorgia State University, [email protected]

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Recommended CitationSammons, Susan S., "Accuracy of Emergency Department Nurse Triage Level Designation and Delay in Care of Patients withSymptoms Suggestive of Acute Myocardial Infarction" (2012). Nursing Dissertations. Paper 27.

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ACCEPTANCE

This dissertation, ACCURACY OF EMERGENCY DEPARTMENT NURSE TRIAGE LEVEL DESIGNATION AND DELAY IN CARE OF PATIENTS WITH SYMPTOMS SUGGESTIVE OF ACUTE MYOCARDIAL INFARCTION by Susan Sanders Sammons was prepared under the direction of the candidate’s dissertation committee. It is accepted by the committee members in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Nursing by the Byrdine F. Lewis School of Nursing and Health Professions, Georgia State University. ____________________________________ Cecelia M. G. Grindel, PhD, RN, FAAN Committee Chairperson ____________________________________ Ptlene Minick, PhD, RN Committee Member ____________________________________ Holli DeVon, PhD, RN Committee Member ____________________________________ Date This dissertation meets the format and style requirements established by Byrdine F. Lewis School of Nursing and Health Professions. It is acceptable for binding, for placement in the University Library and Archives, and for reproduction and distribution to the scholarly and lay community by University Microfilms International. _________________________________ Joan Cranford, EdD, RN Assistant Dean for Nursing Byrdine F. Lewis School of Nursing and Health Professions _________________________________ Cecelia M. G. Grindel, PhD, RN, FAAN Professor & Interim Dean Byrdine F. Lewis School of Nursing and Health Profession

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AUTHOR’S STATEMENT

In presenting this dissertation as a partial fulfillment of the requirements for an advanced degree from Georgia State University, I agree that the Library of the University shall make it available for inspection and circulation in accordance with its regulations governing materials of this type. I agree that permission to quote from, to copy from, or to publish this dissertation may be granted by the author or, in his/her absence, by the professor under whose direction it was written, or in his/her absence, by the Assistant Dean for Nursing, Byrdine F. Lewis School of Nursing and Health Professions. Such quoting, copying, or publishing must be solely for scholarly purposes and will not involve potential financial gain. It is understood that any copying from or publishing of this dissertation which involves potential financial gain will not be allowed without written permission from the author. ____________________________________ Susan Sanders Sammons

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NOTICE TO BORROWERS

All dissertations deposited in the Georgia State University Library must be used in accordance with the stipulations prescribed by the author in the preceding statement. The author of this dissertation is: Susan Sanders Sammons The director of this dissertation is: Dr. Cecelia M. G. Grindel Professor Byrdine F. Lewis School of Nursing and Health Profession Georgia State University P.O. Box 3995 Atlanta, GA 30302-4019 Users of this dissertation not regularly enrolled as students at Georgia State University are required to attest acceptance of the preceding stipulations by signing below. Libraries borrowing this dissertation for the use of their patrons are required to see that each user records here the information requested. NAME OF USER ADDRESS DATE TYPE OF USE (EXAMINATION ONLY OR COPYING)

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VITA

Susan S. Sammons

ADDRESS: 1417 Dale Drive Savannah, GA 31406 EDUCATION: PhD 2012 Georgia State University Atlanta, Georgia MSN 2005 Armstrong Atlantic State University Savannah, Georgia BSN 2005 Armstrong Atlantic State University Savannah, Georgia ADN 1984 Florida State College Jacksonville, Florida PROFESSIONAL EXPERIENCE:

2011 - Present Emergency Services Clinical Nurse Specialist, St. Joseph’s Candler Health System

2007 – 2011 Assistant Professor, Armstrong Atlantic State University

2001 – 2011 Staff Nurse, Senior Nurse, Clinical Nurse Specialist, Emergency Department, Memorial University Medical Center

1996 – 2001 Staff Nurse, Compliance Manager, Hospice Savannah

1994 – 1996 Staff Nurse, Oncology Unit, Candler General Hospital

1989 – 1994 Charge Nurse, Medical/Surgical Unit, Memorial University Medical Center

1986 – 1989 Director of Nursing, Helping Hands Home Care 1985 – 1986 Staff Nurse, Candler Home Health Services 1984 – 1985 Staff Nurse, Oncology Unit, Memorial University

Medical Center

PROFESSIONAL ORGANIZATIONS AND CERTIFICATIONS: 2007 – Present Certification in Emergency Nursing (CEN) 2002 – Present Emergency Nurses Association (ENA) 2012 – Present President, ENA Coastal Empire Chapter 2001 - Present Sigma Theta Tau International, Rho Psi Chapter 2005 – Present Georgia Nurses Association (GNA) HONORS:

2010 Kaiser-Permanente Evidence-Based Practice Research Award

2011 Armstrong Atlantic State University, Brockmeier Faculty Award Nominee

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ABSTRACT

ACCURACY OF EMERGENCY DEPARTMENT REGISTERED NURSE TRIAGE

LEVEL DESIGNATION AND DELAY IN CARE OF PATIENTS WITH SYMPTOMS

SUGGESTIVE OF ACUTE MYOCARDIAL INFARCTION

by

SUSAN S. SAMMONS

More than 6 million people present to emergency departments (EDs) across the

US annually with chief complaints of chest pain or other symptoms suggestive of acute

myocardial infarction (AMI). Of the million who are diagnosed with AMI, 350,000 die

during the acute phase. Accurate triage in the ED can reduce mortality and morbidity, yet

accuracy rates are low and delays in patient care are high. The purpose of this study was

to explore the relationship between (a) patient characteristics, registered nurse (RN)

characteristics, symptom presentation, and accuracy of ED RN triage level designations

and (b) delay of care of patients with symptoms suggestive of AMI. Constructs from

Donabedian’s Structure-Process-Outcome model were used to guide this study.

Descriptive correlational analyses were performed using retrospective triage data

from electronic medical records. The sample of 286 patients with symptoms suggestive

of AMI comprised primarily Caucasian, married, non-smokers, of mean age of 61 with

no prior history of heart disease. The sample of triage nurses primarily comprised

Caucasian females of mean age of 45 years with an associate’s degree in nursing and 11

years’ experience in the ED.

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RNs in the study had an accuracy rate of 54% in triage of patients with symptoms

suggestive of AMI. The older RN was more accurate in triage level designation.

Accuracy in triage level designations was significantly related to patient race/ethnicity.

Logistic regression results suggested that accuracy of triage level designation was twice

as likely (OR 2.07) to be accurate when the patient was non-Caucasian. The patient with

chest pain reported at triage was also twice as likely (OR 2.55) to have an accurate triage

than the patient with no chest pain reported at triage. Electrocardiogram (ECG) delay was

significantly greater in the patient without chest pain and when the RN had more

experience in ED nursing. Triage delay was significantly related to patient gender and

race/ethnicity, with female patients and non-Caucasian patients experiencing greater

delay. An increase in RN years of experience predicted greater delay in triage. Further

studies are necessary to understand decisions at triage, expedite care, improve outcomes,

and decrease deaths from AMI.

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ACCURACY OF EMERGENCY DEPARTMENT REGISTERED NURSE TRIAGE

LEVEL DESIGNATION AND DELAY IN CARE OF PATIENTS WITH SYMPTOMS

SUGGESTIVE OF ACUTE MYOCARDIAL INFARCTION

by

SUSAN S. SAMMONS

A DISSERTATION

Presented in Partial Fulfillment of Requirements for the Degree of Doctor of Philosophy in Nursing in the Byrdine F. Lewis

School of Nursing and Health Professions Georgia State University

Atlanta, Georgia

2012

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Copyright by

Susan S. Sammons

2012

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ACKNOWLEDGMENTS

This dissertation is the culmination of years of hard work and perseverance both

from my family, my committee, and myself. I must thank first Dr. Laura Kimble who

planted the seed of what could be. She gave me direction in the very early stages of my

research in emergency cardiac care and allowed me to pursue my passion. Each of my

committee members, Drs. Grindel, Minick, and DeVon, have given of their time and

expertise to guide me, and for that I am grateful. A sincere thank you to my friends and

colleagues who have watched me each step of the way, class after class after class. You

have asked, and truly seemed to care, about my topics and homework all along the way.

You emergency nurses are my inspiration—I watch you work magic daily, and I am

proud to be among you. A cohort of doctoral students traveled this path with me, driving

mile after mile, reading and having philosophical discussions at every turn. The road less

traveled was made less lonely because of them. To Dee Tanner, Jean Pawl, and Janeen

Amason, I am thankful for each of you. My family has been there for me, faithfully

taking whatever I dished out, literally and metaphorically. I love you totally.

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TABLE OF CONTENTS

Section Page

List of Tables...................................................................................................................x

List of Figures ............................................................................................................... xi

List of Abbreviations .................................................................................................... xii

I. INTRODUCTION ...............................................................................................1

Statement of Problem ......................................................................................................1

Purpose and Aims ............................................................................................................2

Significance .....................................................................................................................2

Standards of Emergency Cardiac Care ............................................................2

Standards of ED RN Triage ............................................................................3

Importance Of Accurate Triage Level Designation .........................................6

Theoretical Framework ....................................................................................................7

Selection of a Theoretical Framework ............................................................7

Overview of Donabedian’s Model ..................................................................8

Use of Donabedian’s Model in Studies ......................................................... 10

Strengths of Donabedian’s Model ................................................................. 12

Summary ....................................................................................................................... 14

II. REVIEW OF LITERATURE ............................................................................. 15

Accuracy Rates in Triage ............................................................................................... 15

Delay in Emergency Care .............................................................................................. 18

Patient Characteristics ................................................................................................... 21

RN Education, Experience, and Triage .......................................................................... 24

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Symptom Presentation ................................................................................................... 26

Summary ....................................................................................................................... 28

III. METHODOLOGY ............................................................................................ 30

Research Design ............................................................................................................ 30

Setting 30

Sample31

Measures and Instruments.............................................................................................. 32

Variables of Interest ..................................................................................... 33

Accuracy ...................................................................................................... 33

Symptoms Suggestive of AMI ...................................................................... 33

Triage Level Designation ............................................................................. 35

Patient Characteristics .................................................................................. 35

RN Characteristics ....................................................................................... 36

Delay ........................................................................................................... 36

Data Collection .............................................................................................................. 36

Data Analysis ................................................................................................................ 38

Protection of Human Subjects ........................................................................................ 38

Summary ....................................................................................................................... 39

IV. RESULTS .......................................................................................................... 40

Preliminary Screening Procedures ................................................................................. 41

Descriptive Statistics ..................................................................................................... 45

Description of the Sample of Patients ........................................................... 45

Description of the Sample of RNs ................................................................ 47

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Statistical Analysis ........................................................................................................ 49

Predictors of Accuracy of Triage Level Designation ..................................... 49

Predictors of Delay of ECG .......................................................................... 50

Predictors of Amount of Delay of Care ......................................................... 52

Summary ....................................................................................................................... 54

V. DISCUSSION AND CONCLUSION ................................................................. 57

Accuracy ....................................................................................................................... 57

Accuracy and Patient Characteristics ............................................................ 58

Accuracy and RN characteristics .................................................................. 59

Triage Delay .................................................................................................................. 61

Triage Delay and Patient Characteristics ...................................................... 62

Triage Delay and RN Characteristics ............................................................ 63

ECG Delay .................................................................................................................... 63

ECG Delay and Patient Characteristics ......................................................... 64

ECG Delay and RN Characteristics .............................................................. 65

Accuracy and Delay....................................................................................................... 65

Conclusions ................................................................................................................... 67

Limitations .................................................................................................................... 68

Implications for Nursing Practice................................................................................... 69

Future Research ............................................................................................................. 70

REFERENCES .............................................................................................................. 72

APPENDICES ............................................................................................................... 88

Appendix A: Registered Nurse Demographics Tool ....................................................... 88

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Appendix B: Selection of Electronic Medical Records ................................................... 90

Appendix C: Informed Consent ..................................................................................... 92

Appendix D: Institutional Review Board Approval ........................................................ 94

x

LIST OF TABLES

Table Page

1. Triage Scale and Maximum Wait Times in Minutes .............................................5

2. Data List ............................................................................................................ 34

3. Skewness and Kurtosis Statistics ........................................................................ 43

4. Patient Demographics ........................................................................................ 46

5. Patient Medical History ...................................................................................... 47

6. Characteristics of Registered Nurses .................................................................. 48

7. Electronic Medical Record Matched Registered Nurse Demographics ................ 48

8. Accuracy of Triage Level Designation Model .................................................... 50

9. Delay of Electrocardiogram Model .................................................................... 51

10. Minutes of Delay in Care ................................................................................... 52

11. Correlation of Registered Nurse Age and Experience ......................................... 53

12. Amount of Delay of Triage Model ..................................................................... 54

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LIST OF FIGURES

Figure Page

1. Donabedian’s model. ...........................................................................................9

2. Model of emergency department registered nurse triage of patients with

symptoms suggestive of acute myocardial infarction. ...........................................9

3. Histogram for minutes to triage. ......................................................................... 43

4. Histogram for minutes to triage (transformed). ................................................... 44

5. Registered nurse years of experience in emergency department. ......................... 44

6. Registered nurse years of experience in emergency department (transformed). ... 45

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LIST OF ABBREVIATIONS

ACC American College of Cardiology

ACS Acute Coronary Syndrome

ADN Associate Degree in Nursing

AHA American Heart Association

AMI Acute Myocardial Infarction

ATS Australasian Triage Score

BMI Body Mass Index

BSN Bachelor of Science in Nursing

CABG Coronary Artery Bypass Graft

CHD Coronary Heart Disease

CPR Cardiopulmonary Resuscitation

CTAS Canadian Triage and Acuity Scale

DTN Door-to-Needle

DTB Door-to-Balloon

ECG Electrocardiogram

ED Emergency Department

EMR Electronic Medical Record

ENA Emergency Nurses Association

ESI Emergency Severity index

IHI Institute for Healthcare Improvement

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IRB Institutional Review Board

LPN Licensed Practical Nurse

MCAR Little’s Missing Completely at Random

MTS Manchester Triage Scale

NCHS National Center for Health Statistics

NHAMES National Hospital Ambulatory Medical Care Survey

NHLBI National Heart Lung and Blood Institute

NSTEMI Non-ST segment Elevation

PAWS Predictive Analytics Software

PCI Percutaneous Coronary Intervention

RN Registered Nurse

RNDT Registered Nurse Demographic Tool

SES Socioeconomic Status

STEMI ST-segment Elevation Myocardial Infarction

UA Unstable Angina

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CHAPTER I

INTRODUCTION

This chapter provides an overview of the significance of rapid cardiac care in the

emergency department (ED). The standards of emergency cardiac care are identified as

well as the standards of ED triage and the importance of accurate triage and rapid cardiac

care. The aims of this study are identified. Donabedian’s Structure-Process-Outcome

model (Donebedian’s model; Donabedian, 1966) is presented as a theoretical framework

to investigate accuracy and delay in triage of patients with symptoms suggestive of acute

myocardial infarction (AMI).

Statement of Problem

Coronary heart disease (CHD) is the leading cause of death in the US (Murphy,

Xu, & Kochanek, 2012). More than 6 million patients present to EDs across the US every

year with a chief complaint of chest pain; 6 million more present with possible symptoms

of CHD such as dizziness, nausea, or shortness of breath (National Center for Health

Statistics [NCHS], 2008). Annually in the US, 1 million patients are diagnosed with

AMI, and 350,000 of those die during the acute phase (Institute for Healthcare

Improvement [IHI], 2009). Accurate and timely triage level designation in the ED can

reduce mortality and morbidity, yet data indicate that accuracy rates are low and delays in

patient care are high. The current economic downturn is associated with more people

seeking primary care from EDs than ever before, leading to overcrowding. ED

overcrowding means that the role of the triage registered nurse (RN) in evaluating those

2

who need urgent care and those who can wait is more pressing than ever before.

Therefore, there is a need to investigate conditions involved in ED RN triage level

designations.

Purpose and Aims

The purpose of this study was to explore the relationship between (a) patient

characteristics (gender, age, race/ethnicity, symptom presentation), (b) RN characteristics

(age, years of experience, years of ED experience, and education), (c) accuracy of ED RN

triage level designations, and (d) delay of care of patients with symptoms suggestive of

AMI. Specifically, the aims of this study were

1. to determine if patient characteristics (gender, age, race/ethnicity) and RN

characteristics (age, years of experience, years of ED experience, and education)

predict accuracy of ED RN triage level designation of patients with symptoms

suggestive of AMI, and

2. to determine if patient characteristics (gender, age, race/ethnicity, symptom

presentation), RN characteristics (age, years of experience, years of ED

experience, and education), and triage level designation predict delay of care of

patients with symptoms suggestive of AMI.

Significance

Standards of Emergency Cardiac Care

AMI is defined as a sudden lack of oxygen to the cardiac muscle due to a clot or

atherosclerotic changes that occlude a coronary artery. Cardiac cell death is not

immediate but can occur within 20 minutes and up to 2 hours after the initial occlusion

(Thygesen, Alpert, & White, 2007). The American College of Cardiology (ACC) and the

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American Heart Association (AHA) recommend in national guidelines that health care

providers meet certain emergency cardiac care goals: obtain an electrocardiogram (ECG)

within 10 minutes of arrival, have a patient evaluated by a physician within 10 minutes,

and initiate thrombolytic medications within 30 minutes or provide percutaneous

coronary intervention (PCI) within 90 minutes of point of entry into the ED with

symptoms of AMI (Krumholz et al., 2008). The initiation of intravenous thrombolytic

medications is also called door-to-needle (DTN), and the provision of PCI is designated

as door-to-balloon (DTB). Rapid assessment and treatment are crucial to restoring blood

flow to the heart, preserving cardiac function, and saving lives. Because of their ability to

recognize the AMI patient and take quick action, ED triage RNs are in the best position

to directly affect early intervention and care.

Standards of ED RN Triage

ED administrators, RNs, and physicians struggle with how to handle the volume

of patients arriving for healthcare (Derlet & Richards, 2000). Determining the severity of

illness and urgency of care required are the main functions of the triage RN. Triage RNs

in the ED have a responsibility to identify patients with cardiac emergencies who need

prompt care. However, triage is not straightforward and few, if any, diagnostic tests are

conducted in triage to aid in that decision. Triage level designation is a subjective

decision based on input from several directions. Along with observational data collected

during a brief nursing assessment, numerous pieces of information, such as previous

medical history and symptoms, are elicited from the patient, and sometimes family,

before the triage level designation is decided. A decision is made to assign the patient to

one of several categories or levels of priority. Although there are no nationally

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established time parameters to complete the triage process itself, the goal during triage is

to assess the patient and make a triage level designation indicating urgency of symptoms

within 2 to 5 minutes (Travers, 1999).

In the US, there is no standard set of triage guidelines; however, most hospitals in

the US have adopted a three or five level system for triage. Many hospitals use the

Emergency Severity Index (ESI; Gilboy, Tanabe, Travers, Rosenau, & Eitel, 2005), a five

level system. The Emergency Nurses Association (ENA; 2010) supports the use of this

five level triage system. In the ESI, patients are assigned a triage level based on the

following scale: Level 1-resuscitation needed, Level 2-emergent, Level 3-urgent but

stable and can safely wait in the waiting room, Level 4-nonurgent, and Level 5-referable

to another provider of care such as a clinic setting. The triage RN must first assess

whether the patient has a life-threatening issue, noted as a high triage level designation

(ESI Level 1 or 2). Level 1 asks the question: Is this patient dying (i.e., not breathing and

in need of cardiopulmonary resuscitation [CPR])? Level 2 asks the question: Is this a

patient who should not wait? If the patient can wait without harm, then the triage RN

moves to a decision regarding estimation of number of resources needed for the physician

to determine a diagnosis or disposition (Level 3, 4 or 5). The ESI system does not

mandate specific time frames (i.e., how long a patient can wait to see a physician).

However, symptoms of AMI must always be considered a Level 2-emergent in the ESI

system so that national guidelines for cardiac emergencies can be met and prompt care

can begin.

Hospitals in other countries use five level triage systems, including the Canadian

Triage and Acuity Scale (CTAS; Beveridge et al., 1999), the Australasian Triage Score

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(ATS; Australasian College for Emergency Medicine [ACEM], 2000), or the Manchester

Triage Scale (MTS; Manchester Triage Group, 1997). All three scales use a numbering

system with Level 1 designating the most critical patient situation. The ATS, the CTAS,

and the MTS set maximum wait times for patients in each level (see Table 1).

Table 1

Triage Scale and Maximum Wait Times in Minutes

Scale Level 1 Level 2 Level 3 Level 4 Level 5

Australasian Triage Scale 0 10 30 60 120

Canadian Triage and Acuity Scale 0 15 30 60 120 Manchester Triage Scale 0 10 60 120 240

In synthesizing the current research of accuracy in ED RN triage level

designations, an emerging issue is inconsistency in the type of triage scales used. Portions

of the EDs in the US do not use the ESI scale but instead use a three-level system: Level

1-emergent, Level 2-urgent, and Level 3-non-urgent. Both three-level and five-level

systems are in use in the United Kingdom, Canada, Australia, and other countries.

Comparing the accuracy of assessments in triage systems is problematic because of the

inconsistency in the number of triage levels in the differing systems (three versus five).

Travers, Waller, Bowling, Flowers, and Tintinalli (2002) compared the five-level

and the three-level systems. A triage level designation assigned a lesser urgency than

needed was denoted as under-triage in the study and a triage level designation assigned

higher than the necessary urgency was denoted over-triage. The under-triage rate for the

three-level systems was 28% but improved to 12% when the five-level ESI was used. The

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ability to correctly identify those patients who required urgent care was 23% in the three-

level systems, but 75% in the five-level ESI. Travers et al. (2002) concluded that the five-

level ESI was superior for triage of patients in the ED.

Importance Of Accurate Triage Level Designation

A growing body of evidence points to the association between early intervention

and decreased mortality in patients with AMI. Studies have demonstrated associations

between time to PCI and mortality risk. In a study reviewing the medical records of

27,080 patients with AMI and PCI at 661 hospitals, Cannon et al. (2000) found a median

DTB time of 116 minutes. An increase in DTB time increased in-hospital mortality by

40-60%, with an increase in mortality higher with DTBs greater than 120 minutes.

In a study of 1,791 patients with ST-segment elevation myocardial infarction

(STEMI) treated with angioplasty, DeLuca, Suryapranata, Ottervanger, and Antman

(2004) found risk of dying within 1 year of AMI increased by 7.5% for every 30 minutes

of delay. More importantly, any increase in DTB time equaled an increase in 1-year

mortality, and the longer the duration of the occlusion, the larger the degree of infarct.

In a retrospective database analysis, McNamara et al. (2006) found increased

DTB times that were associated with increase in hospital mortality in patients (N =

29,222) with STEMI and PCI. As DTB time increased so did in-hospital mortality. In a

study investigating DTB times and mortality in STEMI patients (N = 43,801), 42.1% of

patients were delayed past the 90-minute mark, with 18.8% being delayed greater than 2

hours (Rathore et al., 2009). The overall mortality rate for the study cohort was 4.6%. A

significant trend was noted in mortality in that the longer the DTB time, the higher the

mortality rate.

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As demonstrated in the literature, time to initiation of PCI or fibrinolytic

medication administration is critical. Any action that increases that time is potentially

harmful. Accurate triage level designation is one tool ED RNs can use to facilitate early

intervention and affect patient outcomes.

Theoretical Framework

The individual ED triage process involves a patient presenting to an ED for

medical care. Thus, the patient presenting already has decided that a healthcare need

exists based on symptoms. Once the patient and the triage RN interact, data gathering by

the RN begins. This may be (a) physical evidence such as pale skin, diaphoresis, active

bleeding, or labored breathing or (b) symptoms the patients report, such as pain,

weakness, or fatigue. In either instance, a degree of uncertainty exists. The unknown in

this situation is the seriousness and urgency of the underlying condition responsible for

causing the signs and symptoms. Obtaining symptom progression information and a

health history are part of the triage process for the purpose of data gathering. Initial

diagnostics, such as obtaining a blood pressure, heart rate, respiratory rate, temperature,

and oxygen saturation level, begin in triage. It is unknown whether the patient’s gender,

age, and race/ethnicity or RN experience and education affect this process. For this study,

understanding what happens during the process of ED triage required a framework that

speaks to the processes involved. Donabedian’s model (Donabedian, 1966) was used to

address this process.

Selection of a Theoretical Framework

The Donabedian model is useful in framing studies examining ED RN triage of

AMI patients and factors associated with accuracy of triage level designation and delay

8

of care. The use of this framework in this study was appropriate because the framework

mirrors ED triage in that it has a data input point of multiple factors possibly affecting a

process, which in turn affects the output or outcome.

Overview of Donabedian’s Model

Donabedian’s model evolved from Donabedian’s work in health services quality

and patient outcomes. The primary goal of quality assurance processes is improvement in

outcomes directly related to patient care. The key concepts in the model are structure,

process, and outcome. As demonstrated in Figure 1, Donabedian’s model proposes that

each component has an effect or direct influence on the next (Donabedian, 1980).

Characteristics of the healthcare setting, the healthcare provider, or the healthcare

encounter have the potential to influence both process and outcome. Donabedian’s model

provides a way of understanding the ED RN-patient encounter at triage and the effect of

accuracy of triage level designation and delay in treatment of AMI.

Figure 2 demonstrates the application of Donebedian’s model in this study. The

concept of structure refers to attributes of the healthcare setting, the healthcare provider,

or the healthcare encounter in which care is delivered and may include (a) patient

characteristics and RN characteristics; (b) environmental factors that compose the setting

(e.g., day of the week and time of day), and (c) extrinsic factors (e.g., staffing levels, unit

patient volume, overcrowding, and boarding of admitted patients). Measurement of

extrinsic factors was beyond the scope of this project. Factors that compose the attributes

of the setting in ED RN triage were defined in this study as (a) the patient characteristics

of gender, age, race/ethnicity, and symptom presentation and (b) the RN characteristics of

age, years of experience, years of ED experience, and education.

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Figure 1. Donabedian’s model.

Figure 2. Model of emergency department registered nurse triage of patients with symptoms suggestive of acute myocardial infarction.

Structure Process Outcomes

Structure

Patient characteristics gender age race/ethnicity symptom presentation RN characteristics age race/ethnicity symptom presentation

Process

Triage level designation decisions of patients presenting with symptoms suggestive of AMI

Outcomes

Accurate triage level designation; time to triage and time to ECG

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Process refers to the interpersonal aspects of activities between service providers

and their clients. In ED triage, process is the action that is occurring on the patient’s

behalf and involves the interaction between the ED triage RN and the patient presenting

for care. In this study, process was defined as the triage interaction between patient and

RN and the resulting triage level designation.

In Donabedian’s model, the outcome is the result of the structure and process.

Outcomes in most quality assurance programs are generally described in terms of better

survival rates, lower infection rates, quality of life indicators, or some measure of benefit

to the recipient of care, the patient. In this study, the outcome, or measure of benefit to

the recipient of care, was defined as accuracy of ED RN triage level designation of

patients with symptoms suggestive of AMI and delay or no delay in care as measured by

triage and obtainment of ECG within 10 minutes of arrival.

Use of Donabedian’s Model in Studies

Donabedian’s model has been used extensively to frame studies examining (a) the

performance of community organizations (Chen, Hong, & Hsu, 2007), (b) radiation

oncology services (Christian, Adamietz, Willich, Schafer, & Micke, 2008), (c) AMI

treatment in Germany (Wubker, 2007), (d) compliance with infection control strategies

(Chou, Yano, McCoy, Willis, & Doebbeling, 2008), and (e) medical care for depressed

elders (Hong, Morrow-Howell, Proctor, Wentz, & Rubin, 2008). Using a sample of 195

community organizations in Taiwan, Chen et al. (2007) conducted a correlational study

examining relationships between community organization capacity characteristics and

performance scores validating the theoretical relationships among concepts identified in

the Donabedian model. The model focused on the relationships between structure and

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outcome. The performance outcomes were directly influenced by structure factors such as

funding type, designated department, full-time worker, funding linkage, partnership

score, multiple committee use, attitude toward participation, number of volunteers,

education level of volunteers, and position and age of administrator.

Using the Donabedian model in a study of continuing after-hours emergency

radiation therapy services in Germany, Christian et al. (2008) described outcomes which

were based on the characteristics of each institution providing services (N = 140), reasons

for treatment (structure), day and time treatment occurred, dosage delivered, and

equipment used (process). Outcomes were reported in percentages of improvement in

patient indicators. No relationship was identified between structure variables, process

variables, and outcomes leading the authors to re-evaluate continuation of emergency

radiation services. Donabedian’s model also helped the researchers identify the need to

begin formation of national benchmarks.

Wubker (2007) used the Donabedian model to assess outcomes associated with

diagnostics and treatment of AMI patients in 16 German federal states. Structure was

defined as the number of cardiologists and the number of catheterization facilities;

process was defined as the number of coronary angiography and coronary artery bypass

grafts (CABG) in a 10 year period and adherence to medical standards of care; and

outcomes were mortality rates and potential years of life lost. The study hypothesis was

based on the premise that the better the structure and process, the better the outcome.

However, data revealed only the structure variable of the number of catheterization

facilities was significantly related to better outcomes. Other factors, mainly

socioeconomic factors and risk factors, were found to have an influence on outcomes.

12

Using Donabedian’s model as a guide in a study of antimicrobial resistance (Chou

et al., 2008), infection control professionals (N = 448) were surveyed about structural

factors such as hand washing policies, operating room procedures, and administrator

support, along with process factors such as the culture of the hospital and

communication. The outcome was the degree of adherence to national guidelines to

optimize antimicrobial use as well as strategies to detect, report, and prevent

antimicrobial resistance. Researchers found numerous structural and process factors

(administrator support, feedback systems, forms, formal processes, policy distribution,

formularies, and computer support) significantly related to the outcome of adherence to

national guidelines to optimize antimicrobial use.

Hong et al. (2008) used Donabedian’s model to assess medical care for depressed

elders (N = 110) and found that only about 70% of patients received the minimum needed

medical care for co-morbidities with 22% of depressed elders receiving less than half of

care needed. Significant correlations were noted between insurance coverage, marital

status, income (structure factors) and medical services provided (process factor)

indicating that quality outcomes were related to the functions of structure and process.

In these studies, Donabedian’s model allowed for evaluation of the effectiveness

of a current process or the consideration of a new process based on expected outcomes.

Donabedian’s model also allowed for the identification of factors not initially included as

structure or process variables to be considered or reconsidered for further studies.

Strengths of Donabedian’s Model

Using a systematic approach for assessing the usefulness of a model, as defined

by Chinn and Kramer (1995), familiarity, simplicity, and effectiveness were examined to

13

determine the usefulness of Donabedian’s model in examining ED triage of the patient

with symptoms suggestive of AMI. First noted is the widespread familiarity with the

Donabedian’s structure-process-outcome model and its simple structure. The diagram

itself is simplistic. Secondly, diagrams illustrating structure-process-outcome are used

effectively to demonstrate links between concepts. The model allows for the

identification of independent variables that can be included. Possible independent

variables that can be investigated include (a) the patient characteristics of gender, age,

race/ethnicity, socioeconomic status (SES), marital status, symptom presentation, and

medical history, (b) the RN characteristics of knowledge, years of experience, years of

ED experience, gender, age, degree, and clinical experience, and (c) the unit

environmental factors of crowded waiting rooms, staffing pattern, acuity of patients, time

of day, available beds, RN/physician communication patterns, culture of the unit,

autonomy of the RN, and protocol use.

Many identified research studies investigating ED triage accuracy and delay lack

a conceptual or theoretical framework. This theory gives direction to begin to understand

the relationships and connections of concepts vital to understanding triage, such as

decision-making, delay, accuracy, symptom presentation, and patient and RN

demographic factors. Donabedian’s model focuses on structure and process with an

overall goal of achieving a positive outcome. Donabedian’s model can be used to identify

possible factors affecting ED RN triage level designation. The model can be linked to

empirical indicators testing theoretical relationships and can be used to identify gaps in

the literature. The model can also be used as an organizing framework for ED RN triage

of patients with possible AMI to inform future recommendations for triage in the ED.

14

According to Donabedian (1980), structural characteristics of the setting in which care

takes place have a propensity to influence the process. Similarly, changes in the process

of care will influence outcome. This sets the stage for correlational studies that examine

the relationship of structure and process factors and the rapid treatment of patients with

possible AMI.

There are limitations to the use of Donabedian’s framework for the study of ED

RN triage level designations for patients with symptoms suggestive of AMI. While

Donabedian’s model can identify relationships and associations between structure,

process, and outcomes, it is not helpful in determining causality. However, understanding

how structure and process affect delay in treatment of AMI patients has important

implications that may affect policy, education, and training of staff in the ED.

Summary

In this chapter, the standards of emergency cardiac care were identified, and the

significance of rapid cardiac care was discussed. The aims of the study were identified

and a theoretical model proposed as a framework to study accuracy and delay in the ED.

The Donabedian model has been presented, and its usefulness to examine healthcare

work processes, specifically ED RN triage of the patient with symptoms suggestive of

AMI, has been discussed. Key concepts have been identified and strengths and

limitations analyzed. The theoretical framework of structure-process-outcome

(Donabedian, 1980) was used to investigate ED RN triage accuracy and delay and the

relationship to patient and RN characteristics.

15

CHAPTER II

REVIEW OF LITERATURE

This review of the literature includes a discussion of previous research

investigating accuracy of ED RN triage level designations and delay in ED care. Patient

characteristics as well as RN characteristics in relation to patient care have been

identified in studies and are discussed in this literature review. A discussion of symptom

presentation differences addressed in nursing research studies is included in this review.

Accuracy Rates in Triage

Kosowsky, Shindel, Liu, Hamilton, and Pancioli (2001) hypothesized that ED

triage RNs would be able to identify patients whose condition was serious enough to

warrant hospital admission. Triage RNs were asked to predict during the triage process

which patients would be admitted. RNs (N = 39) in the study had a 62% accuracy rate in

predicting general hospital admission. The researchers found that RNs were only able to

identify patients who were ill enough to need a critical care bed admission 50% of the

time. Arslanian-Engoran (2004) also examined accuracy of the ED triage RN in a study

predicting hospital admission. Registered Nurses (N = 13) in the study exhibited poor

accuracy with a 58% sensitivity and failed to identify acute coronary syndrome (ACS) in

44% during triage of patients who were admitted with a diagnosis of ACS. Holdgate,

Morris, Fry, and Zecevic (2007) examined accuracy of triage RNs in predicting hospital

admission in 1,342 triages. RNs in the study had a 76% accuracy rate, but in 36% of the

cases, the ED RN did not answer the prediction question, leading one to surmise that the

16

RN was unsure. The accuracy rate for patients in the study with cardiovascular disease

was only 59%.

In a study of US trends and predictors of wait times, Wilper et al. (2008) found

that 30% of patients with a diagnosis of AMI had an incorrect triage level designation.

The study retrospectively analyzed National Hospital Ambulatory Medical Care Survey

(NHAMES) data pertaining to 92,173 adult visits to EDs from 1997-2004. Considine,

Ung, and Thomas (2000) in a study of RN (N = 31) consistency in triage level

designation noted a 58% accuracy rate when scoring 10 written vignettes. In a study

comparing paper versus computer vignettes to test ED triage RN performance, Considine,

LeVasseur, and Villanueva (2004) found an overall accuracy rate of 61% when RNs (N =

322) scored written vignettes (N = 4,614) depicting all types of illnesses in adult and

pediatric cases. Atzema, Schull, and Tu (2011) identified an accuracy rate at triage of

67.6% in patients (N = 680) with AMI who also happened to have a charted history of

depression.

In a study of ED RN accuracy in triage level designation, Goransson, Ehrenberg,

Marklund, and Ehnfors (2005) noted a mean accuracy rate of 57.6%, with a range of 22-

89% accuracy per RN (N = 423) in responding to written vignettes (N = 7,550) using

CTAS. In a retrospective review of electronic medical records (EMRs), Atzema, Austin,

Tu, and Schull (2009) investigated triage accuracy in the care of patients with AMI (N =

3,088) and identified a 50% accuracy rate.

In a study of 55 RNs and emergency medical technicians (EMT), Wuerz,

Fernandes, and Alarcon (1998) found poor interrater agreement (k = 0.347) in deciding

triage levels using a 3-level ESI scale in five written vignettes. In test-retest reliability,

17

participants scored five vignettes initially and the same five vignettes 4 to 6 weeks later

with only 24% of the participants assigning the same triage level at time 2. In studies

testing the reliability, validity, and inter-observer agreement of specific triage scales,

researchers found inaccuracies and inconsistencies. In a study testing agreement using the

CTAS, Manos, Petrie, Beveridge, Walter, and Ducharme (2002) noted a good inter-rater

agreement (k = 0.77). In the study, five RNs, five physicians, five EMTs, and five

paramedics scored 41 vignettes with an accuracy rate of 63.4%.

In a study testing reliability of triage using CTAS (Worster, Sardo, Eva,

Fernandes, & Upadhye, 2007), researchers compared written vignettes versus direct

observation of triage. RNs (N = 9) triaged a total of 90 patients while being observed

(Time 1) and triaged the exact scenario 6 months later (Time 2) by written vignette.

Triage level assignment was found to be significantly different from Time 1 to Time 2

with a higher triage level scored on the written vignette. It is possible that RNs assign a

higher ED triage level score when there is more time to make a decision than during live

triage of actual patients.

Numerous studies have identified inaccuracies in triage level designations and an

inability of the ED triage RN to consistently identify patients with emergent symptoms.

Accurate triage level designations by the ED triage RN determine how rapidly a patient

receives medical care in the ED, that is, whether or not the patient is taken straight to a

treatment area or sent back to the waiting room. However, current nursing research has

continued to identify inaccuracies in triage RN decisions. Urgent cases assigned non-

urgent status put patients at risk for delayed treatment and poor outcomes. In the field of

cardiac emergency care, specifically AMI, the consequences can be permanent cardiac

18

muscle damage and even death. Patients are sometimes judged not to have a medical

emergency when one exists. When this occurs, the patient is said to be under-triaged,

meaning the patient was assigned a lower triage level than is actually warranted. Patients

are also over-triaged, assigned a triage level higher than necessary, which may cause a

stable patient to be seen ahead of a patient with a medical emergency and fill treatment

areas needed for those emergent patients.

A large portion of these studies identified a descriptive method of exploration to

identify the degree of accuracy at triage without an attempt to investigate the source of

inaccuracies. Atzema et al. (2009), however, used a correlational design investigating a

possible association between inaccurate triage and delay in care of patients with AMI.

Atzema et al. investigated the accuracy of triage as a possible factor in delay of care for

patients with AMI (N = 3088) in a total of 87 EDs. Of the patients, 50% were assigned a

lower triage score of Level 3, 4 or 5. Median door-to-ECG time was 12 minutes, with

only 45.9% of patients having an ECG within 10 minutes. Time from arrival to

thrombolytic medication administration, also called DTN time, was 40 minutes with only

35.6% of patients’ care meeting the DTN goal time of 30 minutes. Incorrect triage level

designation was found to be significantly associated with delay in door-to-ECG and DTN

time.

Delay in Emergency Care

Delay in care of patients with cardiac symptoms is determined by assessing the

time of arrival, the time of triage, the time of ECG completion, and the time of

assessment by a physician or other healthcare provider. The standard for emergency

cardiac care, set by ACC/AHA guidelines, is an ECG obtained within 10 minutes of

19

arrival to an ED. In a study of adherence to ACC/AHA guidelines for AMI care, ED RNs

were asked if they initiated specific steps in the rapid care of patients with symptoms

suggestive of AMI (Arslanian-Engoren, Eagle, Hagerty, & Reits, 2011). The participants

(N = 158) were specifically asked about nine steps that together make up the ACC/AHA

AMI guidelines. Questions about the guidelines included items such as rapid ECG,

intravenous (IV) access, lab work, minutes to cardiac catheterization, oxygen and aspirin

administration. Only 27% of the participants stated they initiate all nine steps every time.

O’Donnell, Condell, Begley, and Fitzgerald (2005) investigated delays in ED care

of patients with AMI (N = 890). Several points of care were assessed and times

identified: door to triage, 6-7 minutes; triage to first medical assessment, 10-19 minutes;

door to first medical assessment, 20-30 minutes; first medical assessment to thrombolytic

medication administration, 31-45 minutes; and DTB, 103-148 minutes. There are no

specific time frames for the first four steps identified; however, the DTB guideline is < 90

minutes. Delays of even a few minutes at the first points of care will generate an overall

delay in DTN and DTB and must be avoided. Weber, McAlpine, and Grimes (2011)

noted unsafe delays in high-acuity patients (N = 3,932) who were assigned a Level 1 or

Level 2 triage designation. Less than half completed the triage process in an appropriate

time frame of 10 minutes or less and 35% spent >20 minutes in the overall triage process,

both waiting to be triaged and during the triage process itself.

Venkat et al. (2003) investigated delay in handling a patient with a chief

complaint of chest pain when presenting to an ED. A registry of patients (N = 7,935) with

chest pain was used to generate the sample. ECG within 10 minutes of ED presentation

was successfully met in approximately 30-40% for patients with AMI and in

20

approximately 33% of patients with unstable angina or non-STEMI. In a study of 63,478

patients (Diercks, Peacock, et al., 2006) found ECG delay in 65.2% of the sample with a

median delay of 25 minutes. Pearlman, Tanabe, Mycyk, Zull, and Stone (2008)

conducted a study of patients presenting to an ED with a chief complaint of chest pain (N

= 214). Median ECG time was noted to be 29 minutes (intra-quartile range 17-52

minutes). In a secondary analysis of 425 patients (Zegre-Hemsey, Sommargren, & Drew,

2011), researchers reported that only 41% of patients with ischemic symptoms received

an ECG within 10 minutes.

Delays other than the ECG window are important to investigate as the factors

influencing each point of care may differ. These points of time are minutes waiting to be

seen by the triage RN, triage to first physician assessment, and time to aspirin

administration. Few researchers have conducted studies in these areas. Only O’Donnell,

et al. (2005) investigated some of these specific times in delay of ED care in the triage of

patents with AMI. In this study, at several points of care, gender-based delays were

identified; however, triage levels were not identified nor were possible inaccuracies

leading to these delays addressed. Atzema et al. (2009) did specifically investigate the

association between inaccuracy and delay at two specific time points in a secondary

analysis. The odds of achieving the goal of less than 10 minutes to ECG and less than 90

minutes to PCI were 0.54 and 0.44, respectively, and were independently associated with

an inaccurate triage level assignment. These odds are troubling in the care of patients

with AMI and require further research into the contributing factors.

Wilper et al. (2008) conducted a secondary analysis of NHAMCS data, which

included 92,173 adult visits to EDs from 1997-2004. Mean wait time to see a physician

21

was 27 minutes for patients with AMI and 23 minutes for overall Level 2 patients. In a

study investigating wait times to see a physician in over 151,000 patients (Horwitz &

Bradley, 2009), the median wait time to see a physician for Level 1 and Level 2 patients

combined was 15 minutes. Only 48% of patients in this combined emergent category

were seen in the appropriate amount of time.

Patient Characteristics

Patients with symptoms suggestive of AMI are experiencing delays in treatment

in EDs (O’Donnell et al., 2005). Factors including gender, age, race/ethnicity,

socioeconomic status (SES), and other factors have been reported in the literature. In a

study by Diercks, Peacock, et al. (2006), the sole predictor of delay in obtaining an ECG

in the ED in patients with non-ST-elevation ACS was female gender. African American

patients of both genders and Caucasian women experience greater delays in ECG

obtainment (Blomkalns et al., 2005; Diercks, Kirk, et al., 2006;; O’Donnell et al., 2005;;

Pearlman et al., 2008; Takakuwa, Shofer, & Hollander, 2006; Zegre-Hemsey et al.,

2011), aspirin administration (Blomkalns et al., 2005; Enriquez, Pratap, Zbilut, Calvin, &

Volgman, 2008;; O’Donnell et al., 2005), initiation of PCI (Kaul, Chang, Westerhout,

Graham, & Armstrong, 2007; O’Donnell et al., 2005;; Roger et al., 2000), thrombolytic

therapy (Blomkalns et al., 2005; Roger et al., 2000), hospital admission (Arslanian-

Engoran, 2001; Kaul et al., 2007; O’Donnell et al., 2005;; Pope et al., 2000), and

administration of beta blockers and statin drugs (Blomkalns et al., 2005; Enriquez et al.,

2008). The possibility that RNs include patient characteristics during the assignment of

triage level designations was not examined in these studies for a possible relationship to

accuracy and delay.

22

Investigation of accuracy and delay related specifically to ED RN triage level

designations based on patient characteristics are minimal, with only two studies

addressing these issues. In the first regarding delay in the ED, O’Donnell et al. (2005)

reported a significant difference in length of time spent by the RN in triage based on

patient gender with ED RN triage taking twice as long for women. In the second,

Arslanian-Engoran (2001) investigated accuracy using written vignettes and found a

significant difference based on gender and age. The 43 year old female patient vignette

was less likely to be given an urgent triage level designation compared to the 43 year old

male patient vignette or the 66 year old patient vignette of either gender despite evidence

of the same symptoms suggestive of AMI.

Studies were identified that investigated age as a possible factor in ED RN triage

accuracy and delay. Arslanian-Engoren (2000) conducted focus group sessions with ED

RNs and found that RNs held different perceptions based on the age of the patient. Age

biases were identified ranging from considering the patient over 70 years old to be more

believable to being more skeptical of symptoms in a younger patient. RNs in these focus

groups admittedly did not consider AMI as a first diagnosis in middle-aged women

despite presenting symptoms. In a study attempting to identify predictive factors

influencing triage level designation during RN-patient triage interactions (N = 334),

Garbez, Carrieri-Kohlman, Stotts, Chan, and Neighbor (2011) found age of the patient

was a significant factor (p = 0.013) influencing triage level designations. Participants (N

= 18) in that study completed a survey immediately after each triage selecting factors

used in the triage decision. No data is given as to which age group influenced the nurses

decisions in triage level designations. Platts-Mills et al. (2010) identified triage

23

inaccuracies in a study of triage accuracy in the elderly population, defined as the > 65

age group, with only 57.7% of those needing immediate lifesaving measures being

assigned a Level 1. Platts-Mills et al. cited high rates of comorbidities and triage by

proxy, i.e., obtaining information from a family member instead of the patient, as reasons

for possible incorrect triages of the elderly.

Pope et al. (2000) found patients were less likely to be hospitalized if they were

less than 55 years old and nonwhite. In fact, the risk of being sent home despite an AMI

was 4 times higher for nonwhite patients. Pearlman et al. (2008) investigated gender, age,

and race/ethnicity in door-to-ECG times for patients with chest pain and found a median

delay of 29 minutes overall. No significant difference was found in gender and

race/ethnicity, but door-to-ECG time was significantly greater (p = .002) for patients in

age categories of 18-39 and 40-59. This might be expected in the younger age group but

not in the 40-59 age category, as the incidence of AMI is greater in this age group.

In a recent study of cardiac triage decision-making (Arslanian-Engoren, 2009),

RNs were found to hold cultural biases and stereotypes. Specific cues utilized in triage

decision-making included past medical history, patient demographics, attitudes,

perceptions, cultural beliefs, and the specific complaint of chest pain. Using focus group

methodology, the researcher reported that statements elicited from RNs (N = 12) reflected

a lack of believing the patient and doubting what the patient told the triage RN. Also

reported was the notion that females who took time to apply makeup prior to the ED visit

caused the RN not to consider the symptoms as being serious in nature. This suggests that

the RN does not trust the female patient to be truthful in reporting symptoms or that the

symptoms were not sufficiently severe to initiate an immediate patient response.

24

RN Education, Experience, and Triage

Studies investigating the RN role in patient care outcomes identify RN education

level and years of experience as two main variables of interest. Benner and Tanner (1987)

hypothesized that the novice RN is hesitant and slow in assessment of patients in their

care, and the experienced RN is rapid and fluid in problem solving in patient situations.

Although Benner’s work (Benner, 1984) emphasized stages of knowledge from novice to

expert, it is unclear whether these stages influence ED triage accuracy.

In a study of RN staffing models in Canada, researchers found that the less

experienced the RN, the higher the number of wound infections (McGillis-Hall, Doran, &

Pink, 2004). In examining structures and processes of patient care for 46,993 patients in

Canada, Tourangeau et al. (2007) found a higher percentage of bachelor of science in

nursing (BSN) staff associated with lower 30-day mortality rates. The correlations

between increased RN education and decreased mortality rates were also noted in an

analysis of Canadian hospital outcome data for 18,142 patients (Estabrooks, Midodzi,

Cummings, Ricker, & Giovannetti, 2005). Aiken, Clarke, Cheung, Sloane, and Silber

(2003) investigated the association between RN educational preparation and patient

outcomes in a study of 168 U.S. hospitals. Data indicated that as the percentage of nurses

with BSN degrees increased, patient mortality decreased; however, years of experience in

nursing was not found to be associated with decreased mortality.

In a study of ED RN triage decisions, Arslanian-Engoran (2004) found no

association between years of experience and triage accuracy. Registered Nurses in the

study were said to be at the expert level with a mean 12 years of experience. As this was

a small convenience sample (N = 13), the results must be interpreted with caution.

25

Studies testing experience level and the possible association to accuracy with a larger

participant sample are warranted.

In a national survey of 69 EDs in Sweden, Goransson, Ehrenberg, and Ehnfors

(2005) found that qualifications to perform in the triage role varied greatly from basic

nursing training to special education sessions about triage. In fact, 87.5% of the EDs

surveyed had no special requirement or training when assigning RNs in the triage role for

the shift. These researchers reported that only 3 (4.3%) of the 69 EDs in their study

reported criteria limiting new graduate RNs from being in the triage role. Once the degree

of training was surveyed, the authors attempted to identify a relationship between

accuracy of ED triage and RN characteristics of education, age, and experience.

Goransson, Ehrenberg, Marklund, and Ehnfors (2006) noted an accuracy rate of 57.6%,

with a range of 22-89% accuracy per RN (N = 423) responding to written vignettes using

CTAS. The researchers were unable to identify a relationship between RN age, triage

education, years of experience in general nursing or emergency nursing, and accuracy of

ED triage. A limitation of the study was that CTAS was not part of the daily practice of

the RNs in this Swedish study.

Worster et al. (2004) found experience was not related to consistency in triage

level designations in a study of 10 Canadian RNs who scored 400 scenarios, half using

the ESI scale and half using the CTAS scale. The ESI group had more years of

experience (M = 25.2 v. 14.4) but triaged with the same degree of consistency as the

CTAS group (kappa = .91 and .89 respectively). A limitation of this study was that none

of the RNs were experienced in using the ESI 5-level triage system, as it was not part of

26

their daily practice. Actual accuracy of triage level designation decisions was not

identified, only consistency.

Considine et al. (2000) hypothesized that if a triage scale is valid, a patient should

be triaged to the same level designation regardless of which RN is assigning the triage

level. The researchers found a 58% accuracy rate among 31 RNs in two Australian EDs

using the National Triage Scale. Despite 35.5% of the participants being either an ED

CNS or ED manager, no correlation was identified between accuracy and years of

experience. Educational preparation was also assessed in a secondary analysis

(Considine, Ung, & Thomas, 2001) and the researchers noted a positive correlation

between BSN-degreed RNs and accuracy; however, no significant relationship was found

between accuracy and ED training or critical care training. The sample size was small (N

= 31). Correlations between educational preparation and triage accuracy need to be tested

in larger samples of participants.

Symptom Presentation

The AHA and the National Heart, Lung, and Blood Institute (NHLBI) provide a

description of a classic AMI as central chest discomfort that may be described as

pressure, fullness, squeezing, or pain with radiation to the arms, neck, jaw, back, and

abdomen. These symptoms may be accompanied by shortness of breath, nausea,

lightheadedness, and sweating (AHA, 2010; NHLBI, 2010). The ED triage decision is

made more difficult because patients present with varying symptoms, some considered to

be typical of AMI and some atypical. The patient that presents with a classic set of signs

and symptoms suggestive of a heart attack (i.e., clutching the chest, short of breath, pale,

and diaphoretic), will undoubtedly get the attention of the ED triage RN. This immediate

27

recognition of an AMI will generally result in an accurate triage level assignment and a

rapid ECG, a cardiac monitor, and evaluation by an emergency physician. As previously

noted, not all patients present with easily recognizable symptoms and are seen so rapidly.

Previous studies have found the incidence of a classic set of symptoms during an AMI to

be as low as 67% (Canto et al., 2000; Gupta, Tabas, & Kohn, 2002; Horne, James, Petrie,

Weinman & Vincent, 2000). It is concerning that patients without classic symptoms may

be inaccurately triaged.

A recent study of symptoms of AMI found shortness of breath, weakness, and

fatigue as the most frequently occurring acute symptoms in women (McSweeney et al.,

2010). Also identified were racial differences, with 15 symptoms differing significantly

(p = .001) by race/ethnicity after adjustment for cardiovascular risk factors. The

symptoms were unusual fatigue, dizzy or faint, flushed, indigestion, heart racing,

numbness in hands, vomiting, loss of appetite, new vision problems, headache, coughing,

choking sensation, and pain in 10 specific sites. African American women reported more

flushing and indigestion. Hispanic women had the highest rates of pain in all body

locations.

Studies identifying gender-specific symptoms in ACS are noted in the literature

(DeVon, Ryan, Ochs, & Shapiro, 2008; McSweeney, Cody, & Crane, 2001; McSweeney,

et al. 2003). Further studies included (a) differences in the symptoms between unstable

angina (UA) and AMI (DeVon, & Zerwic, 2004), (b) symptom differences in patients

with and without diabetes in UA and ACS (DeVon, Penckofer & Larimer, 2008; DeVon,

Penckofer, & Zerwic, 2005), and (c) symptom clusters in AMI (Ryan et al., 2007).

DeVon and Zerwic (2003) found females with UA to have significantly higher rates of

28

reported weakness, nausea, shortness of breath, anorexia, and upper back pain. Patients

with UA and diabetes were noted to have less nausea, less squeezing, and less aching

pain (DeVon et al., 2005). Older diabetics reported less pain and more fatigue (DeVon,

Penckofer, et al., 2008).

Atypical (or less typical) symptoms may impact triage decisions (Albarran,

Clarke, & Crawford, 2007; Arslanian-Engoran et al., 2006; Carmin, Ownby, Wiegartz, &

Kondos, 2008; Dorsch et al., 2001) highlighting the complexity of patient assessment and

the variations in individuals. Symptoms are frequently attributed to another less serious

cause such as the presence of neck and back pain as reported by women in a study by

McSweeney et al. (2001). In studies about unstable angina and acute myocardial

infarction, DeVon and Zerwic (2003, 2004) identified symptoms of ACS which were

used in this study: chest pressure, chest discomfort, chest pain, shoulder pain, arm pain,

upper back pain, lightheadedness, shortness of breath, sweating, unusual fatigue, nausea,

palpitations, and indigestion. Patients frequently present with symptoms that are not

classic, potentially making triage level designations more complex and prone to

inaccuracies.

Summary

Disparities in emergency cardiac care and diagnostic treatments related to gender,

age, and race/ethnicity exist but have not been investigated thoroughly in relation to ED

RN triage level designations. Studies identify limited accuracy in triage level

designations and the inability of the ED triage RN to consistently identify the patient with

symptoms of possible AMI. Studies thus far have not examined the relationships between

delay in care and accuracy of triage decisions, coupled with patient characteristics.

29

Further studies investigating RN education, experience, and accuracy of triage level

designations are needed. Numerous studies exist that examine differences in rapid cardiac

care from time to ECG to the administration of aspirin to cardiac interventional

procedures. However, few studies were identified that included inaccurate RN triage

level designations as a contributor to delay. The rapid, accurate triage of patients with

symptoms suggestive of AMI remains a challenge in emergency care. There is a need to

investigate delay and inaccuracy of triage decisions to decrease patient wait time for

urgent symptoms, improve morbidity and mortality of patients with AMI, and possibly

lead to changes in ED triage RN educational preparation and training.

30

CHAPTER III

METHODOLOGY

This chapter introduces the research design and methodology. The study setting

and sample are described. Measures, instruments, and variables are identified. Procedures

used to collect data and methods used to protect human subjects are addressed.

Research Design

This study of ED RN triage was a correlational study using retrospective data

from EMRs. The relationships between (a) patient characteristics (gender, age,

race/ethnicity, symptom presentation), RN characteristics (age, years of experience, years

of ED experience, and education), and (b) delay in ECG obtainment and accuracy in

triage level designations made by ED triage RNs were examined. The dependent

variables were accuracy of triage level designations, time to triage, and time to

obtainment of ECG. The independent variables were patient characteristics (gender, age,

race/ethnicity, symptom presentation), RN characteristics (age, years of experience in

nursing, years of experience in ED nursing, and education level).

Setting

EMRs from a regional healthcare system in the southeast were used to generate

the data needed for this study. The study was conducted at a 660-bed general acute care

not-for-profit health system operating EDs at two separate geographical locations,

designated Site 1 and Site 2 for purposes of this study. At the time of this study, Site 1

31

employed 55 ED RNs and logged approximately 50,000 ED visits a year. Site 1 is only

blocks away from a Level 1 trauma center ED reporting a high volume of uninsured

patients. At the time of this study, Site 2 employed 37 ED RNs and logged about 32,000

ED visits a year. Site 2 advertised heavily as a heart hospital and boasted of delivering

rapid cardiac care. Combined, the two sites averaged approximately 2,200 AMI/ruled out

AMI patients per year. Protocol at the sites dictated that the charge RN at the start of the

shift assigns RNs to the triage role, with both sites generally assigning the same RN each

shift. New RN graduates are not assigned to the triage role until each has gained 1 year of

experience. Before they are assigned triage roles, new graduates receive triage training

from an ED educator as well as hands-on experience with their preceptor. Licensed

practical nurses (LPNs) were not employed in either ED. Paramedics, who were

employed in one of the two EDs, did not perform in the triage role. Both facilities had a

line of patients waiting to be triaged at most times of the day and night.

Sample

Inclusion criteria for the selected medical records included (a) patients with

symptoms suggestive of AMI and (b) patients ages 21 years of age and older. Exclusion

criteria include (a) patients who were in critical condition, required immediate intubation,

or had a severely altered level of consciousness; (b) patient records indicating triage by

an RN orienting in the role; (c) patients arriving via ambulance; and (d) patients with a

documented traumatic event.

Some patients were excluded from this study. Patients in critical condition,

requiring immediate intubation, or those with a severely altered level of consciousness

require immediate assistance and triage is deferred. Patients triaged by a RN orienting

32

with another RN is not the standard triage situation. Having two RNs triaging a patient

may change the outcome. Patients who arrive via ambulance are triaged immediately and

may be assigned an urgent level during the triage assessment solely based on mode of

arrival. Patients with a documented traumatic event also were excluded, as the source of

their symptoms is typically thought to be traumatic in nature rather than cardiac.

Based on calculations for determining sample size suggested by Field (2005),

with nine predictor variables, a minimum sample size of 113 was necessary to test

individual predictors in this study. A medium effect size was chosen for this study based

on the earlier described literature review of studies investigating accuracy in triage and

delay in ED care. Online power analysis calculation (Soper, 2004) using a maximum of

nine predictor variables, a medium effect size, and an alpha of < 0.05, with a power of

0.80, also confirmed a minimum sample size of 113 patient triages were needed for the

study. Retrospective data were collected going back approximately 4 months prior to the

month of data collection. No ED documentation system updates occurred during that time

period.

Measures and Instruments

Abstraction of data from the EMR was chosen as the method to capture data

pertaining to time points of care in ED triage and care of patients with symptoms

suggestive of AMI as well as patient demographics. A convenience sample of patient

EMRs was used to obtain variables related to ED triage taken from a general acute care

health system operating two separate EDs. To pull EMRs, the director of health

information systems provided a query with the following criteria: (a) the date of the ED

patient visit was in the 4-month time period prior to data collection and (b) the presenting

33

complaint was chest pain or discomfort, shortness of breath, weakness, nausea, vomiting,

syncope, palpitations, or diaphoresis.

Variables of Interest

Variables of interest (patient’s chief complaint, final diagnosis, triage level

assigned, patient gender, patient age, patient race/ethnicity, triage RN’s name, and clock

times at specific points of care) were obtained from data abstracted from the EMR (see

Table 2). Information regarding RN characteristics was obtained via the RN

demographics tool (RNDT; see Appendix A), which was completed by participating

RNs. The triage level designation decision was the main unit of measure, not the specific

ED triage RN, so that each triage level designation stood alone. Triage level designations

from EMRs were investigated in this study.

Accuracy

Accuracy was determined based on whether or not a patient with symptoms

suggestive of AMI was assigned a Level 2 triage designation. Delay was identified as

actual clock time in minutes from arrival until triage and ECG obtainment with delay

designated as greater than 10 minutes. The clock time was the time recorded by various

personnel in the EMR. Other possible delay points such as minutes to physician

assessment also were collected. Also collected during the EMR review was day of the

week, time of day, and shift.

Symptoms Suggestive of AMI

Symptoms suggestive of AMI, for purposes of this study, were defined as those

symptoms as defined by Hollander et al. (2004) which included chest discomfort or pain,

shortness of breath, weakness, nausea or vomiting, syncope, palpitations, and diaphoresis.

34

Table 2

Data List

Datum Measure Type of measure

Patient

Day of visit to ED Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday Nominal

Chief complaint As defined by Hollander et al. (2004) Nominal

Co-morbidities Diabetes, heart disease, obesity, smoking Nominal

Triage level designation 1, 2, 3, 4, 5 Ordinal

Gender Male, Female Nominal

Age Continuous ages Interval

Race/ethnicity 1-7 Nominal

Marital status Single, Married, Widowed, Divorced Nominal

Payor source 1-5 Nominal

Time of arrival Clock time as entered in EMR at first point of contact Interval

Time of triage Clock time as entered in EMR Interval

Busyness of unit Minutes from arrival time to triage time Interval

Time of MD assessment Clock time as entered in EMR Interval

Time of ECG Clock time as entered in EMR and ECG Interval

Registered Nurse

Name First and last name Nominal

Gender Male, Female Nominal

Age Continuous ages Interval

Race/ethnicity 1-5 Nominal

Education Diploma, ADN, BSN, MSN Categorical

Years of experience Actual years Interval

Years of ED experience Actual years Interval

Note. ED = emergency department; MR = electronic medical record; MD = medical doctor (physician); ECG = electrocardiogram; AND = associate in nursing degree; BSN = bachelor of science in nursing; MSN = master of science in nursing.

35

EMRs indicating a patient presentation of any of these symptoms, in the absence of

trauma, were considered for this study. It was expected that the patient’s chief complaint

might be one or more of these symptoms. It was also expected that the vague symptoms

of nausea and vomiting might be, in fact, a gastrointestinal complaint and possibly not a

cardiac event.

Triage Level Designation

The triage level designation was the level assigned by the ED triage RN during

the triage process. Triage levels were coded as Level 1, critical; Level 2, emergent; Level

3, urgent but stable; Level 4, nonurgent; and Level 5, minor (Gilboy et al., 2005). The

triage level designation determines which patient is seen next and whether immediate

treatment will be initiated or if the patient will be asked to wait in the waiting room.

Patients presenting with symptoms suggestive of AMI must have been given a triage

Level 2 designation. If this did not occur, the triage level designation was coded as

inaccurate for the purposes of this study. This dependent variable was dichotomously

coded as yes (accurate) or no (not accurate). Because the ED triage RN is unable to

determine for certain, at the point of first contact and without an ECG, whether a triaged

patient truly has a cardiac diagnosis such as AMI, the end diagnosis was not considered

as a variable in this study. Only presenting symptoms were considered.

Patient Characteristics

Gender was recorded as male or female, and age of the patient was recorded in

years. Race/ethnicity was recorded in one of the following seven categories as designated

by Health Information Systems of the participating site: Caucasian, African American,

American Indian/Alaskan Native, Asian, Hispanic or Latino, multiracial, or unknown.

36

Other demographic information collected during the EMR review included payer source

and marital status. Co-morbidities such as diabetes, obesity, smoking status, and previous

heart disease also were collected.

RN Characteristics

The registered nurse demographics tool (RNDT; Appendix A) created by the

researcher was used to collect RN characteristics: gender, age, race/ethnicity, years of

experience in nursing, years of experience in ED nursing, and education level (assessed

as the highest degree in nursing obtained at the time of participation in the study). The

RNDT included a tear away portion to separate the RN demographic information from

the participant’s name, providing a sense of privacy and confidentiality.

Delay

Time points of care included time of arrival to the ED, time to triage, time to

ECG, and time to physician assessment. All times were recorded in minutes using

military time notation. The time of arrival in the ED was documented automatically when

the patient’s name was entered into the computer system at the walk up desk in the ED

lobby. Time to ECG was calculated by subtracting the time of arrival from the time

electronically stamped on the ECG itself. If the electronically stamped ECG time was

different from the time charted in the EMR by the ED staff, the ECG stamp was the

accepted time for this study. Time to physician assessment was obtained from the

physician’s handwritten first notation documented during that first patient interaction. If

the physician did not note the time of assessment, then the time documented in the

computer was used.

Data Collection

37

Once institutional review board (IRB) approval was received from both the

healthcare system and Georgia State University, the director of health information

management provided a list of patient records to review for possible study inclusion. An

electronic data file was created to hold all data abstracted from the EMR. A working copy

was made of the database. No identifying information was recorded in this working file.

Data abstracted from the EMR included patient gender, age, race/ethnicity, mode of

arrival, and reason for ED visit as well as times associated with arrival to the ED, triage

by the RN, ECG performed, and physician evaluation. Triage level designation assigned

as well as the name of the triage RN were collected during the EMR review. RN

demographics were linked to the initial data file. Once the list of RN names was

available, consent was obtained from participating RNs. A flyer was posted in both EDs,

and a locked box was placed in the area as a receptacle for the completed surveys and

informed consent documents. The study topic, research aims, and risks and benefits of the

study also were discussed at several staff meetings. Each consenting RN completed the

RNDT, which took approximately 2 minutes per RN.

The researcher was given a separate cubicle in the medical records department as

a private place to access the computer system for the purposes of collecting variables for

this study. Between May 2011 and June 2011, 559 records were reviewed. Dates of ED

visit were from January 1, 2011 thru May 7, 2011. Records indicating that the patient

arrived by ambulance were excluded, which removed 175 records. An additional 98

records were excluded due to the chief complaint being other than cardiac in nature, such

as syncope related to seizure, asthma exacerbation, and chest pain due to trauma. The

remaining 286 records were included in this study, and data were recorded on the RNDT

38

for analysis. The triage level designation decision was the main unit of measure (i.e., not

the specific ED triage RN) so that each triage level designation stood alone. Triage level

designations from 286 EMRs were investigated in this study representing 40 triage RNs.

An even distribution of triage level designations among the RNs was not the goal of this

study.

Data Analysis

After collecting data for this study, the researcher conducted various analyses. In

order to describe the variables, the researcher first conducted descriptive statistics on both

the patients and the nurses. Frequencies and percentages were calculated for the patient

characteristics gender, race/ethnicity, marital status, and medical history (smoker, body

mass index [BMI], diabetes, previous cardiac disease, chest pain triage). Means, standard

deviations, and ranges were calculated for the RN characteristics age, years of

experience, and years of ED experience. The researcher then conducted inferential

statistics. These analyses included Pearson’s correlations and logistic regression.

Protection of Human Subjects

Selected data were coded and entered into an electronic data file. Patient and RN

identifiers were kept confidential. Information was kept private to the extent allowed by

law. There was no compensation for RNs participating in this study. All RN and patient

identifier information were removed from the data, and unique case numbers were

assigned to data so that no actual patient or RN names were on study records. The data

were stored in a locked file cabinet in the office of the researcher and on a computer with

password and firewall protection. Only the researcher had access to the uncoded data.

The confidentiality of patients, clinicians, and institutions was maintained.

39

Summary





AMI. Specifically, the aims of this study were to determine the predictive nature of (a)

patient and RN characteristics on the accuracy of ED RN triage level designations of

patients with symptoms suggestive of AMI, and (b) patient and RN characteristics, and

accuracy of ED RN triage level designations on delay of care of patients with symptoms

suggestive of AMI. Exploration of this relationship was conducted via retrospective EMR

review and data abstraction from one hospital system in the Southeastern US operating

two EDs. RN demographic information was collected via survey, the RNDT, after

obtaining written consent and confidentiality was maintained.

40

CHAPTER IV

RESULTS





AMI. Specifically, the aims of this study were

1. to determine if patient characteristics (gender, age, race/ethnicity) and RN

characteristics (age, years of experience, years of ED experience, and education)

predict accuracy of ED RN triage level designation of patients with symptoms

suggestive of AMI, and

2. to determine if patient characteristics (gender, age, race/ethnicity, symptom

presentation), RN characteristics (age, years of experience, years of ED experience, and

education), and triage level designation predict delay of care of patients with symptoms

suggestive of AMI.

Data were obtained from the EMRs of a health system in a Southeast region of the

US. In this chapter, preliminary screening procedures and results are described.

Following that, a description of the sample and the variables used in the study are

presented. In the last section, results are elucidated.

41

Preliminary Screening Procedures

Descriptive statistics, frequencies for the categorical variables, and descriptives

for the continuous variables were calculated to determine (a) whether there were

missingvalues and (b) the distribution of the data. A 2-tailed p value of .05 was

considered significant in all analyses. Predictive Analytics Software (PAWS; Version

18.0) software package for statistical analysis was used for all analyses. There were 92

RNs listed as staff members in the two EDs at the time of the study. However, only 66 of

the RNs in the two EDs were identified in EMRs selected for inclusion in the study. Of

those, 40 RNs consented to participate, giving an overall response rate of 60.6%. The

final sample of 40 RNs consisted of 28 females (70%) and 12 males (30%). The triage

level designation decision was the main unit of measure (i.e., not the specific ED triage

RN), so that each triage level designation stood alone. Triage level designations from 286

EMRs were investigated in this study representing 40 triage RNs. An even distribution of

triage level designations among the RNs was not the goal of this study. Of the nurses who

agreed to participate (N = 40), the range of triages conducted was 1 to 22, with five RNs

in the study triaging 10 or more patients (range 10-22). For a portion of Aim 1,

considering nurse demographics, the total sample was 192 EMRs; for the remainder,

considering accuracy and delay and patient demographics, the total sample of EMRs was

286 (see Appendix B).

There were missing values for the following RN characteristics: ethnicity,

education, age, years of experience, and years of ED experience. Accordingly, Little’s

Missing Completely at Random (MCAR) test was conducted to determine whether the

pattern of missing data was random or systematic. Results indicated that the pattern was

42

missing at random (χ2 (3) = 4.17, p = .243). In addition, cross-tabulation procedures

between cases with and without missing values and the dependent measures were all non-

significant. Values for the continuously measured variables were thus imputed using the

expectation-maximization method (Tabachnick & Fidell, 2007).

The distributions of the variables measured on either an interval or ratio scale

were assessed for normality by inspecting histograms and skew indices, i.e., skewness

statistic/SE. When the distribution of the variable resembles a normal curve (Tabachnick

& Fidell, 2007) and its skew index is below three (Kline, 2005), then the distribution is

deemed to be normal. As seen in Table 3 and in Figures 3 and 4, the distribution of the

minutes to triage was highly skewed as was years of ED experience (see Table 3, Figures

5 and 6). Accordingly, these two variables were transformed using the natural log

function (Tabachnick & Fidell, 2007). After the variables were transformed, the skew

indices fell below three (see Table 3). The transformed variables were used in subsequent

inferential analysis although descriptive statistics are reported in their original metric to

facilitate interpretation.

All continuously measured variables were standardized. Cases whose

standardized values fell above the absolute value of 3.29 were identified as outliers

(Tabachnick & Fidell, 2007). Three cases had extremely low standardized values for RN

experience in the ED (z-score for each case was -3.40) and thus were deleted from the

data set.

43

Table 3

Skewness and Kurtosis Statistics

Variable Skew Kurtosis Skew indices

Patient

Age .20 -.32 Minutes to triage 3.41 16.22 23.68

Minutes to triage (transformed) .198 1.375 Registered nurse

Age .04 .34 Years of experience -.03 -1.49

Years of ED experience 1.28 .48 8.89 Years of ED experience (transformed) -.348 2.42

Note. N = 286. SE for kurtosis = .29; SE for skew indices = .144; ED = emergency department.

Figure 3. Histogram for minutes to triage.

44

Figure 4. Histogram for minutes to triage (transformed).

Figure 5. Registered nurse years of experience in emergency department.

45

Figure 6. Registered nurse years of experience in emergency department (transformed).

Descriptive Statistics

Description of the Sample of Patients

Patients (N = 283) were between 26 and 95 years old; the mean age was 61.44

(SD + 13.02). The frequencies and percentages of the variables describing the sample of

patients are displayed in Table 4. Slightly more than half of the patients were female

(51.9%). The majority of patients were Caucasian (67.1%); a minority were African

American (31.1%) or other ethnicity (0.8%). Most were married (59.4%), with the

remaining being single (11%), divorced (14.5%), or widowed (14.1%).

46

Table 4

Patient Demographics

Variable Frequency Percentage

Gender

Male 136 48.1

Female 147 51.9

Race/ethnicity Caucasian 190 67.1

African American 88 31.1

Hispanic or Latino 1 .4

Multiracial 1 .4 Missing 3 1.1

Marital Status Single 31 11.0

Married 168 59.4 Divorced 41 14.5

Widowed 40 14.1 Missing 3 1.1

Note. N = 283.

Clinical characteristics of the sample are presented in Table 5. Most of the

patients were non-smokers (74.6%). Just less than half of the patients had a BMI over 29

(48.1%). One third (30.4%) of the patients had diabetes, and 43.1% reported a history of

cardiac disease. A majority of the patients (88.7%) reported experiencing chest pain in

addition to their other symptoms at triage, which was unexpected.

47

Table 5

Patient Medical History


Smoker

No 211 74.6

Yes 72 25.4

Body mass index > 29 No 129 45.6

Yes 136 48.1

Missing 18 6.3

Diabetes No 197 69.6

Yes 86 30.4 Previous cardiac disease

No 161 56.9 Yes 122 43.1

Chest pain triage No 32 11.3

Yes 251 88.7

Note. N = 283. Description of the Sample of RNs

The descriptive statistics without the imputed values for the demographic

variables measured are displayed in Table 6. Age of RNs (N = 194) ranged from 26 to 64

years with a mean age of 45.46 (SD + 11.72). Years of nursing experience ranged from 3

to 35 years (M = 17.96; SD + 10.43). Similarly, years of ED nursing experience ranged

from 3 to 35 years (M = 10.98; SD + 8.51). As previously discussed, RN demographic

data were determined to be MCAR and therefore did not affect the results of this study.

48

Table 6

Characteristics of Registered Nurses

Variable N Range M SD

Age 194 26-64 45.46 11.72

Years of experience 193 3–35 17.96 10.43

Years of ED experience 194 3-35 10.98 8.51

The frequencies and percentages of the variables describing the sample of RNs

are displayed in Table 7. The majority of the RNs were female (70.3%), and all of those

whose ethnicity were reported were Caucasian. A majority had an ADN (45.6%), while

the remainder had a BSN (19.1%) or were diploma RNs (3.5%). No nurses participating

in the study had an advanced practice nursing education.

Table 7

Electronic Medical Record Matched Registered Nurse Demographics


Gender Male 84 29.7

Female 199 70.3 Race/ethnicity

Caucasian 204 72.1 Missing 79 27.9

Level of education Diploma 10 3.5

Associate degree 129 45.6 Bachelor degree 54 19.1

Missing 90 31.8

49

Statistical Analysis

Predictors of Accuracy of Triage Level Designation

All patients should have been coded as a triage Level 2 (or Level 1 if truly in need

of immediate resuscitation). If they were coded a Level 3, the triage was considered

inaccurate. The overall accuracy rate was 54%. Aim 1 was to determine if patient

characteristics (gender, age, and race/ethnicity, and symptom presentation) and RN

characteristics (age, years of experience, years of ED experience, and education) predict

accuracy of ED RN triage level designation of patients with symptoms suggestive of

AMI. Two logistic regression procedures were conducted. RN level of education data

was missing in 90 cases; therefore, only 196 cases were included in the regression model.

Accordingly, two logistic regression procedures were conducted, one with level of

education and one without level of education.

Because level of education did not significantly predict accuracy of triage level

designation, only the findings of the second logistic regression procedure (that does not

include the education variable) are presented in Table 8. Patients’ race/ethnicity and

symptom presentation and RNs’ age significantly predicted accuracy of triage level

designation. Non-Caucasians were more likely to receive an accurate triage level

designation than Caucasians (OR = 2.07, p = .010). Patients who experienced chest pain

were more likely to receive an accurate triage level designation than patients who did not

experience chest pain (OR = 2.55, p = .022). The older the RN, the greater the likelihood

that the triage level designation was accurate (β = .07, p = .037).

50

Table 8

Accuracy of Triage Level Designation Model

Variable B SE Wald OR

Patient

Gender -.37 .26 2.07 .69

Caucasian vs. non-Caucasian patient .73 .28 6.58 2.07

No chest pain vs. chest pain .94 .41 5.24 2.55 Registered Nurse

Age .07 .03 4.34 1.07

Years of experience -.03 .03 .53 .98

Years of ED experience -.05 .27 .04 .95

Note. N = 283. OR = odds ratio. Overall model χ2 (7) = 25.44, * p = .001. Predictors of Delay of ECG

A majority of patients (82.6%) did not receive an ECG within the ACC/AHA

guidelines of 10 minutes. Three logistic regression procedures were conducted to address

Aim 2. Aim 2 was to determine if patient characteristics (gender, age, race/ethnicity, and

symptom presentation), RN characteristics (years of experience, years of ED experience,

and education), and triage level designation predict delay of ECG for patients with

symptoms suggestive of AMI. RNs level of education data were missing in 90 cases.

Only 196 cases were included in the regression model. Thus, a regression procedure with

RN’s level of education was conducted and a second procedure was conducted without

the level of education variable. Because the second logistic regression procedure did not

converge, a third procedure was conducted. Because the coefficient and standard error of

51

the main symptom presentation variable (i.e., chest pain or discomfort) were very high

and unlikely, this variable was not included in the third procedure.

Given that level of education did not significantly predict delay of ECG, only the

findings of the third logistic regression procedure are presented in Table 9. The findings

revealed that only the number of years spent working as a RN significantly predicted the

odds of delay of ECG. The more experienced the RN, the greater the probability that

there would be a delay in ECG (β = .10, p = .026).

Table 9

Delay of Electrocardiogram Model

Variable B SE Wald OR

Patient

Age -.02 .01 1.65 .98

Gender .35 .33 1.11 1.42

Caucasian vs. non-Caucasian patient .75 .40 3.58 2.12 Registered Nurse

Age -.05 .04 1.59 .95 Years of experience .10 .04 4.98 1.10

Years of ED experience -.26 .39 .45 .77

Note. N = 283. OR = odds ratio. Overall model χ2 (6) = 13.32, *p = .038.

Because chest pain was not included in the final logistic regression model, a

logistic regression procedure with only the chest pain variable was conducted. This

procedure still yielded very unlikely parameters. Thus, a chi-square procedure was

52

conducted to determine whether there would be a significant relationship between

symptom presentation and delay of ECG. The chi-square procedure revealed that there

was a significant relationship between symptom presentation and delay of ECG, χ2 (1) =

7.56, p = .006. The difference between delay and no delay for those patients who did not

experience chest pain was significantly higher than the difference for those patients who

experienced chest pain. Accordingly, the probability that there would be a delay in ECG

was higher for those patients who did not experience chest pain than for those who

experienced chest pain.

Predictors of Amount of Delay of Care

Delay of care was defined as the number of minutes a patient waited to be triaged

and the number of minutes a patient waited to have an ECG performed. Those time points

are identified in Table 10. The mean time to triage was 11.78 minutes, with women

waiting a mean of 14.01 minutes and non-Caucasian patients waiting a mean of 12.73

minutes. At a mean of 46.32 minutes, the minutes to ECG time was significantly outside

of the recommended 10 minutes for the patient group in this study.

Table 10

Minutes of Delay in Care

Variable M Range SD

Minutes to triage 11.78 0-116 +14.9

Male 9.36

Female 14.01 Caucasian 11.31

Non-Caucasian 12.73

Minutes to electrocardiogram 46.32 1-326 +50.7

53

To determine if patient characteristics, RN characteristics, and triage level

designation would predict the amount of delay of care, three linear regression procedures

were conducted. Because RN’s level of education could not be imputed, only 196 cases

were included in the regression model. Accordingly, one regression procedure was

conducted with the level of education variable. Another procedure was conducted without

the level of education variable. Bivariate associations among variables were evaluated

using Pearson’s product moment correlation (Table 11). Lastly, because RN age,

experience in nursing, and experience in ED nursing were highly correlated with each

other, a third procedure, with only the significant RN characteristic predictor of years of

experience, was conducted.

Table 11

Correlation of Registered Nurse Age and Experience

1 2 3 M SD

1. Age --- .904** .585** 45.46 11.72

2. Years of experience --- .510** 17.96 10.43

3. Years of ED experience --- 10.98 8.51

**p < .01 Because level of education did not significantly predict amount of delay of ECG,

only the results of the regression without level of education are presented. The findings in

Table 12 reveal that patient’s gender significantly predicted the amount of delay of triage,

F (1, 277) = 5.53, p = .019). In particular, female patients waited for triage longer (M =

14.01, SD + 17.39) than male patients (M = 9.36, SD + 11.23). Patient’s race/ethnicity also

54

significantly predicted amount of delay of triage, F (1, 277) = 4.43, p = .036). Non-

Caucasians waited for triage longer (M = 12.73, SD + 12.58) than Caucasian patients (M =

11.31, SD + 15.94). Lastly, RN experience in years also predicted the amount of delay of

triage, F (1, 277) = 29.90, p = .001); the more experienced the RN, the longer the delay in

triage (β = .31).

Table 12

Amount of Delay of Triage Model

Variable B SE β F TOL

Patient

Age -.00 .00 -.02 .14 .98

Gender .25 .11 .14 5.53* .96

Caucasian vs. non-Caucasian patient .24 .11 .12 4.43* .93 Level 2 TLD vs. Level 3 TLD .09 .11 .05 .75 .94

Registered nurse Years of experience .03 .01 .31 29.90** .97

Note. N = 283. TLD = triage level designation; TOL = Tolerance. Overall model F (5, 277) = 8.08, p = .001. * p < .05. ** p < .001.

Summary

EMR review revealed 286 triage level designations conducted by predominantly

white females. Of the potential participants, 40 ED RNs consented to participate in the

study, representing 194 triage decisions. The remaining 89 were MCAR and therefore did

not affect the results of the study. All RNs reporting race/ethnicity were Caucasian, and

70.3% were female. The mean age of the RN participants was 45.46 years. A minority

55

(19.1%) of the RNs held a BSN. The mean number of years’ experience as an RN was

17.96 years, with 10.98 years working in the ED.

Patients in the sample (N = 286) had a mean age of 61.44, and gender was evenly

distributed (48.1% male; 51.9% female). Of the sample, 67% (n = 190) was Caucasian,

and a majority (59.1%) were married. A majority of the patients did not smoke (74.6%).

About a third (30.4%) of the patients had diabetes, and 43.1% reported a history of

cardiac disease. A majority of the patients (88.7%) reported some type of chest symptom,

described by participants as pain, pressure, discomfort, heaviness, or squeezing.

Accuracy in triage level designations was significantly related to race/ethnicity of

the patient with the non-Caucasian patient twice as likely (OR 2.07) to be triaged

accurately. The patient with chest pain was 2.5 times as likely (OR 2.55) to be accurately

triaged than the patient with no chest pain. Age and gender were not found to be

significant predictors of accuracy of triage level designation. ECG delay was significantly

greater in patients without chest pain. ECG delay was not related to the patient

characteristics of gender, age, or race/ethnicity. Triage delay was significantly related to

the patient’s gender and race/ethnicity with female and non-Caucasian patients waiting

longer than male and Caucasian patients. Triage delay was not significantly related to the

patient’s age.

RNs in the study had an overall accuracy rate of 54% in triage level designations

of patients with symptoms suggestive of AMI. Neither RN level of education nor years of

experience predicted accuracy of triage level designation; however, older RN age was

predictive of accuracy. The RN demographic of age was significantly related to accuracy

in triage level designations. However, level of education, experience in nursing, and

56

experience in ED nursing were not significant predictors of accurate triage level

designation. ECG delay times were also significantly greater when the RN had more

experience in nursing. ECG delay was not related to RN age, level of education, or years

of experience in ED nursing. Triage delay was significantly related to the RN years of

experience in nursing.

57

CHAPTER V

DISCUSSION AND CONCLUSION

In this study, the researcher examined patient and RN characterisitcs that may be

associated with accuracy of ED RN triage level designation and delay in care of patients

with symptoms suggestive of AMI. This chapter includes a discussion of the study results

and conclusions of the study. Implications for future research are explored.

Accuracy

Of the patient records (N = 286) included in the study, only 155 (54.1%) had an

appropriate triage level designation of Level 2 required for a patient with symptoms

suggestive of AMI. This triage level designation is crucial in determining how quickly

the patient receives an ECG and is examined by a healthcare provider. Thus, an accuracy

rate of 54% is concerning. It is possible that RNs had trouble determining if symptoms

represented ACS. Previous studies of triage accuracy have identified accuracy rates of

50% to 76 % (Arslanian-Engoren, 2004; Atzema et al., 2009; Considine et al., 2004;

Considine et al. 2000; Goransson, Ehrenberg, Marklund, et al., 2005; Holdgate et al.,

2007; Kosowsky et al., 2001; Wilper et al., 2008). In this study, variables were identified

that may be predictive of accuracy in triage level designations. Of the eight patient and

RN variables investigated, only patient race/ethnicity and symptom presentation and RN

age were identified as significant in predicting accuracy in triage.

58

Accuracy and Patient Characteristics

A significant relationship was found between accuracy and patient race/ethnicity

in that non-Caucasian patients in the study were more likely to be accurately triaged. This

was an unexpected finding based on the literature. Arslanian-Engoran (2004) found no

difference in accuracy in triage based on race/ethnicity. However, in a study of pain-

related decision-making, Hirsh, George, and Robinson (2009) found that race/ethnicity

was a significant contributor during assessment of pain, with older African American

females perceived by RNs as having and expressing more pain. Although Hirsh et al. did

not identify accuracy of triage level designation, the visual portrayal of pain by patients

was noted as a significant decision point for the RNs (N = 54) in that study.

Although the accuracy rate was only 54%, a significant relationship was found

between accuracy and patient report of chest pain, in that the patients reporting chest pain

as one of their symptoms were more likely to be accurately triaged. It was expected that

more patients would present with atypical symptoms and not report chest pain; however

only 11.3% reported with no chest pain and other symptoms such as shortness of breath,

weakness, nausea or vomiting, syncope, palpitations, and diaphoresis. Chest pain was

identified in the initial triage documentation for 88.7% of the patients in the study. It

could be that upon questioning by the triage RN about chest pain, patients gave a positive

response hoping that they would be seen sooner or be believed as having a true

emergency. Chest pain is the hallmark symptom of cardiac ischemia; therefore, it is

surprising that these patients were not triaged correctly 46% of the time. Of the patients

triaged correctly, recognizing chest pain as a classic symptom of possible cardiac

59

ischemia most likely led to the Level 2 triage level designation for patients in this study,

resulting in increased triage accuracy for patients with chest pain.

Neither gender nor age of patient was found to be a significant predictor of

accuracy in the study. This is contrary to previous studies by Arslanian-Engoren (2000,

2001) who identified gender as a predictor of accuracy with men more likely than women

to be triaged to an accurate triage level designation despite identical symptoms generated

in a vignette. Arslanian-Engoren (2000) also identified age biases in triage decisions

when considering the AMI diagnosis. Similarly, Garbez et al. (2011) and Hirsh et al.

(2009) found increased patient age a significant factor influencing patient assignment of a

triage Level 2 designation instead of a “stable to wait” Level 3 designation. Although

older patients may be more likely to have CHD, it is possible that the high number of

patients presenting with chest pain increased the accuracy rate and overrode the possible

predictors of patient gender and age.

Accuracy and RN characteristics

The RN characteristic of age was found to be a significant predictor of accuracy

in triage level designation of patients with symptoms suggestive of AMI. The older the

RN, the greater the likelihood of an accurate triage level designation. This may be

explained by the high correlations between age and experience. Older RNs may have

better assessment skills, better critical thinking skills, and be able to synthesize history

and clinical presentation. It is possible that the older RN may have personal or family

experiences with cardiac related events leading to the more accurate triage level

designation for patients triaged. However, age does not necessarily equate to years of

experience in nursing as more adults enter the field of nursing as a second career.

60

During qualitative focus groups of RNs (N = 12) with a mean age of 42,

Arslanian-Engoren (2000) found that RNs tended not to think of AMI in patients who

matched their own age group using the rationale that if it could happen to the patients, it

could happen to the RNs. Nurses in that study perceived the older patient (70 to 80 years)

to be more believable and the younger patients (30 to 40 years) to be more dramatic. Age

of the nurse performing triage has not been identified as a factor in accurate triage

decisions in nursing research studies. In fact, only one study of triage accuracy identified

nurse age as a study variable. In a study of 423 ED triage RNs in 48 EDs, Goransson et

al. (2006) found no relationship between accuracy and nurse age.

Although studies identify the BSN education level as positively affecting overall

patient outcomes (Aiken et al., 2003; Considine et al., 2001; Estabrooks et al., 2005;

Tourangeau et al., 2007; Tourangeau, Giovannetti, Tu, & Wood, 2002), RN education

was not identified as a predictor of accuracy in triage level designations in this study.

Triage level designation decisions are a nursing function that could lead to poor patient

outcomes. Nearly half of the patients in this study (n = 139) were triaged by an RN with a

level of nursing education at below the BSN level (see Table 7).

Neither RN experience in ED nursing nor nursing experience in general was a

predictor of accuracy in triage of patients with symptoms suggestive of AMI. This is

consistent with findings by Arslanian-Engoren (2004) specifically addressing acute

coronary syndromes. Studies have consistently failed to identify a link between

experience in nursing and accuracy in triage level designations (Considine et al., 2000,

2001; Goransson et al., 2006; McGillis-Hall et al., 2004; Worster et al., 2004).

61

Atzema, Austin, Tu, and Schull (2010) defined RN experience as triaging a high

volume of patients and suggested that high volume EDs were better at recognizing AMI

patients and assigning the appropriate triage level designation. Quite possibly the

opposite may be true. The repetitive nature of triaging the same type patient symptoms

over and over may desensitize the nurse to the urgent need and actually result in

inaccuracy by choosing an incorrect triage level. It is possible that the years of experience

in nursing, and ED nursing especially, may color the judgment of the experienced RN

such that more obvious patient deterioration during presentation at triage is deemed

necessary for an RN to decide a true emergency exists and assign a Level 2 designation.

There may also be other factors involved in the decision to choose a Level 3 designation

instead of a Level 2 designation for a patient presenting with symptoms suggestive of

AMI.

Triage Delay

Many studies identify overall delay in the ED for patients with AMI (Diercks,

Peacock, et al., 2006;; O’Donnell et al., 2005; Pearlman et al., 2008; Venkat et al., 2003;

Weber et al., 2011; Zegre-Hemsey et al., 2011). However, only a few separate waiting to

be triaged as a specific portion of delay in care when investigating overall delay (Lyons,

Brown, & Wears, 2007; O’Donnell et al., 2005; Weber et al., 2011). This study addressed

delay in the waiting room. Although rapid recognition is crucial to the initiation of

interventions to reperfuse cardiac muscle, patients with symptoms suggestive of AMI

waited, prior to being seen by an RN to begin the triage assessment, a mean of 11.78

minutes (range 0-116 minutes).

62

Numerous studies have identified overall ED wait times that are lengthy and fall

outside the ESI level recommendations to ensure proper care and best results. Horwitz

and Bradley (2009) found wait times to be dangerously long for patients categorized as

Level 1 and 2, with only 48% of those patients being seen by a physician within 15

minutes. Wilper et al. (2008) noted mean wait times of 27 minutes for patients with AMI.

O’Donnell et al. (2005) specifically identified a time delay of 26 minutes in the triage

process. Lyons et al. (2007) also identified a delay to triage of 14 minutes regardless of

severity of chief complaint.

Triage Delay and Patient Characteristics

Non-Caucasians waited significantly longer for triage (M = 12.73 minutes). This

is consistent with previous literature. Studies have associated race/ethnicity with delay in

care with non-Caucasian patients waiting longer for care in EDs (James, Bourgeois, &

Shannon, 2005; Wilper et al., 2008). In addition, James et al. (2005) suggested that

provider-related variables such as stereotyping, cultural unawareness, and prejudices may

play a role in delay of care. However, Wilper et al. (2008) did not find triage biases as

causative for excessive delay in the non-Caucasian ED patient population. These

variables were not investigated in the current study.

Regression analysis revealed that female patients waited longer (14.01 minutes) to

be triaged (p < .001) than male patients. This is consistent with the literature. Numerous

studies have identified delay in the care of females (Concannon et al. 2009; DeLuca et al.,

2004; Diercks, Peacock, et al., 2006; O’Donnell et al., 2005; Wilper et al., 2008) relating

to several points of care, from pre-hospital care to post intervention and critical care

placement, but no studies were identified that specifically quantified triage delay and

63

gender. Researchers have identified that females are more likely to present with atypical

symptoms during ACS (Albarran et al., 2007; DeVon, Ryan, et al., 2008; DeVon &

Zerwic, 2002, 2003), which may affect the recognition of the possible AMI. However, in

this study, 88.4% of females and 89.2% of males reported chest pain.

Patient age was not found to be a significant predictor of delay in triage. It is

possible that the RN identifies additional co-morbidities in the older population, resulting

in more timely care. This is not consistent, however, with a study by DeLuca et al. (2004)

who found delay in ED treatment for AMI patients in the > 70 year old patient

population. Also, Elkum, Fahim, Shoukri, and Al-Madouj (2009) identified patient age as

one predictor of delay in ED care with the > 65 age group waiting longer.

Triage Delay and RN Characteristics

Experience in nursing was a significant predictor of triage delay. The more

experienced the RN, the more delay in triage. Studies investigating delay in care

generally do not include demographics pertaining to the ED triage RN. Like accuracy, the

experienced RN may have a higher threshold as to what constitutes an emergency, which

may unnecessarily cause delay in a patient with symptoms suggestive of AMI.

ECG Delay

Of the patient characteristics of gender, age, race/ethnicity, and symptom

presentation and the RN characteristics of age, years of experience in nursing, years of

ED experience in nursing, and education, only patient symptom presentation and RN

experience in nursing were found to be significant predictors of delay in ECG

obtainment. Of the patient records (N = 286) included in this study, only 51 (17.8%)

patients received an ECG within the recommended 10 minutes of arrival. Mean wait time

64

for an ECG was 46.32 minutes. A small number of patients in the study received an ECG

prior to being seen by a physician, but most waited for an assessment by a physician and

an order to do an ECG leading to a further delay in ECG. As with triage delay, ECG

delay was also significantly predicted by RN general experience in nursing. Delay in

ECG may be related to perceptions of autonomy and the older RN may feel less

autonomous especially if this is a change in performance expectation for that RN. If

autonomy has increased as a unit expectation, it could be that the older RN has not

blended that into clinical practice.

Experience may not be the factor that matters in triage level designation

decisions. In an unpublished qualitative study (Sammons & Minick, 2012) ED RNs were

asked to describe triage. Nurses identified two main processes that they used to work

toward the right decision: a) connecting with the patient, which included caring enough to

ask the right questions and b) reading between the lines to identify the salient features of

a patient’s history or signs and symptoms.

ECG Delay and Patient Characteristics

Patients not reporting chest pain waited longer for an ECG, which was an

expected finding. Studies link atypical presentations to delay in identification of AMI

including a diagnostic ECG (Atzema et al., 2009; Canto et al., 2000). Atypical symptom

presentation, generally discussed as symptoms other than chest pain, may increase the

difficulty of recognizing an AMI at triage. Although not identified in this study, gender

and race/ethnicity have been previously identified in the literature as predictors of delay

in various points of care including ECG (Diercks, Kirk, et al., 2006; Diercks, Peacock, et

al., 2006; Takakuwa et al., 2006; Zegre-Hemsey et al., 2011). There are few studies

65

evaluating age as a possible factor in ECG delay; however, Pearlman et al. (2008)

identified age differences in ECG times with a median ECG time of 29 minutes and a

significant delay noted in the 18-39 and 40-59 age groups as compared to the > 60 age

group.

ECG Delay and RN Characteristics

Increased RN experience was noted as a significant predictor of ECG delay.

Because triage occurred before ECG in a majority of the cases in the study, this ECG

delay may be, in fact, due to the triage delay that occurred. The experienced RN may

have a higher threshold as to what constitutes an emergency, which may unnecessarily

cause delay in obtaining an ECG for a patient with symptoms suggestive of AMI. In other

words, if the triage RN has seen numerous patients do well who presented with shortness

of breath, diaphoresis, or other symptoms suggestive of AMI, the nurse may decide the

next patient can wait, which delays ECG obtainment. Previous studies investigating delay

in obtaining an ECG did not include RN demographics for comparison and no studies

were identified investigating a specific relationship between ECG delay and RN

experience. The experienced RN may be less likely to participate in ongoing education in

the ED leading to a knowledge deficit regarding atypical symptom presentation. If this

RN then becomes the preceptor for new RNs, this lack of knowledge could be

perpetuated.

Accuracy and Delay

Accuracy was not correlated with decreased delay. Accurately choosing a triage

level designation of Level 2 for the patient with symptoms suggestive of AMI did not

guarantee that the patient would receive an ECG within 10 minutes of arrival. The RN

66

may assign a Level 2 designation but not actively seek an ECG or possibly let the patient

continue to wait in the waiting room. This delay may be due to overcrowding in the ED

or processes in the ED itself such as the physical location of the triage booth or

availability of personnel to perform an ECG. For the triage RN to stop the triage process

for the remaining waiting room patients is not appropriate, yet there may not be

additional personnel available to perform this crucial diagnostic test.

Choosing an inaccurate triage designation of Level 3 for the possible AMI may

result in prolonged delay before treatment, especially when there is a high volume of

patients in the ED. Having a large number of Level 3 patients is not uncommon in any

ED on any given day. To inaccurately include the possible AMI in this group is

dangerous and could be deadly. Studies were identified that did identify an association

between assigning an incorrect triage level designation and delay in care of patients with

AMI. Atzema et al. (2009) found an independent association between incorrect triage

level designations and delay in ECG for patients (N = 3,088) diagnosed with AMI. In a

subsequent study, Atzema et al. (2011) found an association between inaccurate triage

level designations and ECG delay in AMI patients (N = 6,784) with a past medical

history of depression. It is possible in those studies that the Level 2 patient is always

taken straight to a treatment room. It is also possible that the Level 3 patient is also able

to get a room quickly thereby decreasing ECG times.

There are several specifically measured time points of care in the ED: from arrival

by ambulance or by public or private vehicle to triage; from triage to ECG; from triage to

physician assessment; from physician assessment to diagnosis, generally noted as

disposition; and from disposition to initiation of interventions to reestablish cardiac

67

muscle perfusion. The total of these time points equals the DTB and DTN times

frequently discussed in cardiac literature. Delay at any point decreases the chances of

meeting the ACC/AHA goal of < 90 minutes DTB or < 60 minutes DTN for

establishment of cardiac muscle reperfusion.

Conclusions

In this study, the accuracy rate of triage level designations for patients with

symptoms suggestive of AMI was 54%. Triage was delayed a mean of 11.78 minutes and

ECG was delayed a mean of 46.32 minutes. Female gender of patient was predictive of

triage delay but not ECG delay nor accuracy of triage level designations. Patient age was

not predictive of accuracy or delay. Patient race/ethnicity was not predictive of ECG

delay but was a predictor in accuracy of triage level designations and triage delay. A

report of chest pain was predictive of increased accuracy and decreased delay in ECG.

RN age played a role in accuracy but not in delays for triage and ECG. RN

experience played no role in accuracy and was predictive of increased delays in both

triage and obtainment of ECG. Neither RN ED experience nor level of education was

predictive of accuracy and delay.

In patients with symptoms suggestive of AMI, delays in individual segments of

care may result in a significant delay in emergent cardiac care. In this study, 11.78

minutes from door to triage plus 46.32 minutes to obtain an ECG led to a prolonged delay

in emergent cardiac care. This study adds to the body of evidence regarding ED triage of

patients arriving by private vehicle with symptoms suggestive of AMI. However,

inconsistency in nurse triage decisions may be due to other condition not yet explored,

68

such as RN critical thinking skills, intelligence, and executive functions. A further

investigation is warranted to assess factors affecting triage level designations.

Limitations

A limitation of this study is that portions of the data were gathered by

retrospective electronic chart review. Patients may have reported additional symptoms

that were not documented by the nurse at time of triage. Missing information in a medical

record has been previously identified in the literature (DeVon, Ryan & Zerwic, 2004).

This missing information could be the report of symptoms such as dizziness or nausea

reported by the patient or family to the triage RN but not documented in the EMR during

triage. This missing information may also have led to the exclusion of some EMRs in the

study, as data collection was dependent on RN documentation of chief complaint.

A second limitation is related to the nurse’s participation in the research study. A

portion (n = 26) of the nursing staff in the two EDs did not wish to disclose their

demographic information, citing reasons such as a constant barrage of computerized

surveys required of staff by other departments and upper management. Also noted by the

researcher during conversations with staff was a fear of reprisal, a suspicious approach to

research in general, a mistrust of how data are used, and a general reluctance to

participate. Reluctance to participate was also identified by Arslanian-Engoren (2000) in

a study of ED triage nurse decisions.

Other variables not identified in this study may have an impact on ECG delay

times and triage times such as ED overcrowding, physical limitations of the units, and

resource availability. These structure variables were not addressed in the study and

should be variables of interest for future research.

69

Implications for Nursing Practice

A 54% accuracy rate was identified in this study. A triage delay of 11.78 minutes

was also noted, and a majority of the patients in the study (82.6%) received an ECG

outside of the recommended 10 minute window despite symptoms suggestive of possible

AMI. Strategies must be explored—and implemented—that will improve accuracy and

decrease delay. Targeted educational interventions aimed at increasing awareness of AMI

multi-symptom presentations is an appropriate starting point and should be required

periodically for all ED RNs. In a survey of ED triage nurses, nurses reported provision of

(a) targeted educational information in the form of PowerPoint presentations, (b)

discussions of evidence in nursing literature, and (c) memory aids as useful in increasing

accuracy in cardiac triage decisions (Arslanian-Engoren, Hagerty, Antonakos, & Eagle,

2010). Initial education and ongoing competency assessment regarding the symptoms of

ACS for both the new graduate and the experienced nurse must occur. The ability to

recognize shortness of breath, weakness, nausea, vomiting, syncope, palpitations, or

diaphoresis as indicators of possible AMI is a crucial skill in triage.

Further studies are essential to explore the other features of decision making in

triage that may affect accuracy and delay of care in the ED. An exploration of RN

perceptions of the AMI patient population may give insight into nurse biases related to

triage that could be addressed. Studies exploring the cues nurses use to make decisions in

triage are numerous (Arslanian-Engoran, 2005, 2009; Edwards & Sines, 2007; Lyneham,

Parkinson, & Denholm, 2008; Pugh, 2002), yet no single solution exist.

Providing information to ED RNs regarding the differences in individual patient

outcomes when rapid care occurs could be a catalyst to increasing expediency of care in

70

the ED of patients with symptoms suggestive of AMI. This could take the form of follow

up information or case review of patients cared for in the ED who went on to receive care

in the acute care hospital setting and rehabilitation area.

Patient safety indicators often demand acceleration in care without adequate

resources. As pressures in EDs across the nation increased to care for more and more

patients while improving efficiency, streamlined processes for obtaining rapid ECGs

must be explored and instituted. Processes to improve ED RN triage practice such as

clinical case review and supervision as well as documentation audits may need to be

developed.

Future Research

Further studies investigating the impact of ED overcrowding and resource

availability are warranted. Meeting professional guidelines for patients presenting to an

ED with symptoms suggestive of AMI is imperative; however, the task is difficult due to

the multiple variables inherent in the processes surrounding emergent care. Studies must

focus on the factors surrounding inaccuracy and delay in ED care of patients with AMI.

This study investigated variables associated with triage RN inaccuracy and delay in care.

Further studies are necessary to begin to understand decisions at triage and improve the

expedience of care, which will preserve cardiac muscle, improve outcomes, and decrease

deaths from AMI.

A review of the current literature on the topic of ED cardiac emergency care of

patients with AMI failed to identify studies that examined mode of patient arrival in

relation to accuracy of ED RN triage and delay of treatment in the ED. The processes that

occur in the care of a patient who arrives via ambulance are not the same as that of

71

patients who arrive by public or private vehicles. Further studies specifically identifying

mode of arrival are needed. Secondly, there is little evidence of the role continuing ED

education and ED orientation of the novice RN and the experienced RN plays in accuracy

of triage and delay of care. Studies are needed that examine this possible predictor of

accurate triage decisions in the ED and could be conducted by identifying EMRs per

nurse so that an appropriate sample size could be obtained representing each triage RN

equally. Lastly, studies investigating patient outcomes in those who are inaccurately

triaged are needed. This gap in the current literature provides an opportunity to improve

emergency care of all patients with heart disease.

There are three considerations in the research of triage RN accuracy and delay of

care in the ED for patients with suspected AMI: (a) exploring whether or not inaccuracies

and delays exist, (b) identifying possible contributing conditions, and (c) possible

interventions to improve the accuracy and decrease delay. Numerous studies have

addressed the first phase. This study begins to address the second component of possible

factors contributing to inaccuracy in triage and delay of care. The last phase will need to

take the form of intervention studies to identify what strategies are effective in improving

accuracy of ED RN triage of the AMI patient based on data obtained from the second

component of research.

72

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APPENDICES

APPENDICES

APPENDIX A

REGISTERED NURSE DEMOGRAPHICS TOOL

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REGISTERED NURSE DEMOGRAPHICS TOOL Please circle one in each category: Code _____ (to be assigned by researcher) Gender: M F Race: Caucasian African American Hispanic Asian other Education: diploma ADN BSN MSN doctoral level Age: ___________ Month and year of first RN licensure: _________________________ Years of experience as an RN: _______ years _______ months Years of experience in any Emergency Department: _______ years _______ months Please print your name on the lower portion of this form. _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

Researcher to tear away here after coding. NAME OF NURSE: ___________________________________________ (This form will be given a code and your name will be removed from the data) Created: 02-10-2010 Revised: 05-18-2011

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APPENDIX B

SELECTION OF ELECTRONIC MEDICAL RECORDS

91

S e l e c t i o n o f E M R s

A r r i v a l m o d e P O V ?

5 5 9 E M R s ( l i s t g e n e r a t e d b y M e d i c a l R e c o r d s )

1 7 5 a m b u l a n c e ( e x c l u d e d )

3 8 4 p r i v a t e v e h i c l e

S / S X o f A M I

9 8 o t h e r o b v i o u s s o u r c e

( e x c l u d e d )

2 8 6 y e s , S / S X s u g g e s t i v e o f

A M I

R N c o n s e n t

9 2 E M R s , n o R N c o n s e n t

( 2 6 R N s )

1 9 4 E M R s w i t h R N

c o n s e n t ( 4 0 R N s )

92

APPENDIX C

INFORMED CONSENT

93

94

APPENDIX D

INSTITUTIONAL REVIEW BOARD APPROVAL

95

INSTITUTIONAL REVIEW BOARD Mail: P.O. Box 3999 In Person: Alumni Hall Atlanta, Georgia 30302-3999 30 Courtland St, Suite 217 Phone: 404/413-3500 Fax: 404/413-3504

May 16, 2011

Principal Investigator: Grindel, Cecelia Marie

Student PI: Susan Sammons

Protocol Department: B.F. Lewis School of Nursing

Protocol Title: Accuracy of Emergency Department Nurse Triage Level Designation and Delay in Care of Patients with Symptoms Suggestive of Acute Myocardial Infarction

Funding Agency: Kaiser Permanente

Submission Type: Protocol H11455

Review Type: Expedited Review

Approval Date: May 13, 2011

Expiration Date: May 12, 2012 The Georgia State University Institutional Review Board (IRB) reviewed and approved the above referenced study and enclosed Informed Consent Document(s) in accordance with the Department of Health and Human Services. The approval period is listed above. Federal regulations require researchers to follow specific procedures in a timely manner. For the protection of all concerned, the IRB calls your attention to the following obligations that you have as Principal Investigator of this study.

1. When the study is completed, a Study Closure Report must be submitted to the IRB. 2. For any research that is conducted beyond the one-year approval period, you must

submit a Renewal Application 30 days prior to the approval period expiration. As a courtesy, an email reminder is sent to the Principal Investigator approximately two months prior to the expiration of the study. However, failure to receive an email reminder does not negate your responsibility to submit a Renewal Application. In

96

addition, failure to return the Renewal Application by its due date must result in an automatic termination of this study. Reinstatement can only be granted following resubmission of the study to the IRB.

3. Any adverse event or problem occurring as a result of participation in this study must

be reported immediately to the IRB using the Adverse Event Form.

4. Principal investigators are responsible for ensuring that informed consent is obtained and that no human subject will be involved in the research prior to obtaining informed consent. Ensure that each person giving consent is provided with a copy of the Informed Consent Form (ICF). The ICF used must be the one reviewed and approved by the IRB; the approval dates of the IRB review are stamped on each page of the ICF. Copy and use the stamped ICF for the coming year. Maintain a single copy of the approved ICF in your files for this study. However, a waiver to obtain informed consent may be granted by the IRB as outlined in 45CFR46.116(d).

All of the above referenced forms are available online at https://irbwise.gsu.edu. Please do not hesitate to contact Susan Vogtner in the Office of Research Integrity (404-413-3500) if you have any questions or concerns. Sincerely, Susan Laury, IRB Chair

Federal Wide Assurance Number: 00000129