ASSIGNMENT 1

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FInalPaper.pdf

EFFICACY OF THE IMPLEMENTATION OF EARLY SEVERE SEPSIS STRATEGIES ON A MEDICAL SURGICAL UNIT

Presented in Fulfillment of the Requirements for the Degree of

Doctor of Nursing Practice

Nova Southeastern University Health Professions Division

College of Nursing

Jorge Hirigoyen 2015

Copyright by Jorge Hirigoyen, 2015

All Rights Reserved

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Abstract

Background: Septicemia is among the leading causes of death in the U.S. Severe sepsis has been largely studied in the intensive care unit. Limited research is available regarding sepsis identification and treatment in medical-surgical units. Purpose: The purpose of this capstone study was to evaluate the efficacy of a severe sepsis bundle in a medical surgical non-ICU, specifically focusing on reducing sepsis transfer to higher levels of care and sepsis hospital length of stay. The sensitivity and specificity of the severe sepsis tool was also evaluated. Theoretical Framework: Donabedian’s model was used as a guiding framework for this project. Methods: A quasi-experimental pre-post comparison design was utilized to evaluate the sepsis transfers to higher level of care and sepsis hospital length of stay before and after the implementation of a severe sepsis bundle. Same approach was used to calculate the sensitivity and specificity of the tool. Results: The tests revealed that there was no statistical significance (p = .291) in terms of length of stay between the pre- and post-implementation groups. The study revealed that in fact there was a decrease in sepsis length of stay, from pre implementation of 8.53 days to post implementation of 7.26 days. Evaluation of sepsis transfers to higher level of care revealed that during the 6-month period of the study, there were zero transfers of septic patients. In regards to the sensitivity and specificity of the tool, the study yielded a sensitivity of 55.85% and a specificity of 99.54%. The positive predictive value (PPV) of the tool was estimated at 95.83%, negative predictive value (NPV) was estimated at 92.83% and disease prevalence was 15.95%. Area under the receiver operating curve was 0.777. Conclusions: The study’s results could have been obtained due to multiple limitations to the study. These limitations could be potential opportunities for future research. Nevertheless, the study demonstrated that early identification and early interventions of sepsis bundles are effective in delivery of evidence-based care. The severe sepsis bundle should be incorporated into all medical surgical wards within the organization and even be adapted to other sister institutions.

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Acknowledgments

I would like to thank the following people:

I would like to thank my Capstone committee: Dr. C. Christine Orton, my chairperson,

Dr. Diane Whitehead, and Dr. Andra Hanlon for their continued guidance and support

that with much determination were able to guide me in the right direction with their

insightful comments and words of encouragement.

I would like to express my sincere gratitude to my mentor Jill M. Szymanski for the

continuous support of my DNP study and related research, for her patience, motivation,

and immense knowledge. Her guidance led me throughout the development,

implementation, and writing of this capstone. I could not have imagined having a better

advisor and mentor for my DNP study.

I would like to also thank God among all things, my family: my parents and my sister,

colleagues, and staff at Baptist Hospital of Miami for their endless support, patience, and

eagerness, which provided me with the motivation and desire to complete this project.

I would like to express special thanks to my wife Stephanie, for her never-ending support

during the completion of this project. I would have not been able to complete this

without her support, especially since she acted as my catalyst in beginning this journey.

Lastly, I would like to dedicate this degree to my two lovable children, Ryan and Elise;

they are everything to me.

Table of Contents Title Page .........................................................................................................................i Signature Pages .............................................................................................................. ii Copyright ....................................................................................................................... iv Abstract ........................................................................................................................... v Acknowledgements ........................................................................................................ vi Table of Contents ..........................................................................................................vii List of Tables.................................................................................................................. ix List of Figures ................................................................................................................. x

Chapter 1: Nature of Project and Problem Identification ..................................................1

Significance of the Problem .........................................................................................4 Problem Statement and Purpose ...................................................................................5 Project Objectives ........................................................................................................7 Theoretical Framework: Donabedian's Model ..............................................................8 Theoretical Framework as It Relates to Clinical Problem ........................................... 12 Significance of the Study ........................................................................................... 14

Healthcare Practice ................................................................................................. 14 Healthcare Outcomes .............................................................................................. 15 Healthcare Delivery ................................................................................................ 15 Healthcare Policy ................................................................................................... 17

Summary ................................................................................................................... 18

Chapter 2: Literature Review ......................................................................................... 19 Epidemiology ............................................................................................................. 20 Treatment Recommendations and Modalities ............................................................. 22 Implementation Strategies .......................................................................................... 25 Biomarkers for Sepsis Identification........................................................................... 27 Procalcitonin Biomarker as a De-Escalation of Antibiotic Therapy ............................ 32 Summary ................................................................................................................... 33

Chapter 3: Methods ....................................................................................................... 34 Project Design ............................................................................................................ 34 Setting ....................................................................................................................... 35 Inclusion/Exclusion Criteria ....................................................................................... 36 Ethical Considerations and Confidentiality ................................................................. 37

Waiver of Informed Consent................................................................................... 37 Risk and Benefits.................................................................................................... 38

Goals and Objectives ................................................................................................. 38 Project Phases ............................................................................................................ 39 Budget ....................................................................................................................... 43

Budget Analysis ..................................................................................................... 43 Information Technology ............................................................................................. 44

Research Department ................................................................................................. 44 Timeline of Project .................................................................................................... 44 Determination of Sample Size: Power Analysis .......................................................... 45 Statistical Tests .......................................................................................................... 46 Outcome Measures ..................................................................................................... 46 Validity and Reliability of the Sepsis Screening Tool ................................................. 48 Summary ................................................................................................................... 49

Chapter 4: Results and Discussion ................................................................................. 50 Descriptive Results .................................................................................................... 51

Objective 1 ............................................................................................................. 51 Objectives 2 and 3 .................................................................................................. 51 Objective 4 ............................................................................................................. 52 Statistical Results ................................................................................................... 53

Strengths and Limitations of the Project ..................................................................... 57 Strengths ................................................................................................................ 57 Limitations ............................................................................................................. 59

Implications of the Study ........................................................................................... 60 Implications for Nursing Practice ........................................................................... 60 Implications for Healthcare Delivery ...................................................................... 61 Implications for Healthcare Policy .......................................................................... 62 Future Research ...................................................................................................... 63

Summary ................................................................................................................... 64

References ..................................................................................................................... 66 Appendix A: Nova IRB Exempt Letter .......................................................................... 71 Appendix B: Letter of Project Support from Medical Surgical Unit ............................... 73 Appendix C: Paper Copy of Severe Sepsis Tool............................................................. 75 Appendix D: Proposed Severe Sepsis Algorithm ........................................................... 76 Appendix E: Sepsis Order Set in Medical Surgical Floor ............................................... 77 Appendix E: Sepsis Order Set in Medical Surgical Floor ............................................... 78 Appendix F: Education Flyer ......................................................................................... 79 Appendix G: International Classification of Diseases (ICD-9) Coding ........................... 80

List of Tables

Table 1 Description of Comparison Groups ................................................................. 52 Table 2 Independent t-Test Results for Each Group ..................................................... 54 Table 3 2x2 Tabulation Design .................................................................................... 56 Table 4 Area Under the Curve ..................................................................................... 56 Table 5 Sensitivity and Specificity ............................................................................... 57

List of Figures

Figure 1. Adaptation of structure, process, and outcome model (Donabedian, 1980). ..... 81 Figure 2. Receiver operating curve (ROC). ................................................................... 82

Chapter 1: Nature of Project and Problem Identification

Sepsis is the tenth leading cause of death in the United States. The number and

rate per 10,000 hospitalizations for sepsis or severe sepsis has more than doubled from

2000 to 2008, with incidence increasing approximately 5%-10% each year (Hall,

Williams, DeFrances, & Golosinskiy, 2011). Sepsis is also the leading cause of death in

the critical care population regardless of multiple innovations in diagnosing and

resuscitation therapy (Sankar & Webster, 2013). According to the Centers for Disease

Control and Prevention (CDC), hospitalization for severe sepsis as the primary diagnosis

increased from 326,000 in 2000 to 727,000 in 2008 and as a secondary diagnosis from

621,000 in 2000 to 1,141,000 in 2008 (Hall et al., 2011). Severe sepsis and septic shock

are not only a problem in the United States but also worldwide. This pandemic affects

millions of individuals every year worldwide, approximately one out of four individuals

diagnosed with sepsis or septic shock dies (Dellinger et al., 2013). Anderson and

Schmidt (2010) concluded, that worldwide there are approximately 18 million new cases

of sepsis each year, with a mortality rate range estimated about 30% to 60%. Recent

approaches have targeted both diagnosing sepsis and rapidly treating those septic

patients, thus preventing further decompensation. Accurately identifying sepsis at an

early stage can potentially decrease mortality by 5%-10%, consequently accentuating the

importance of early detection and prompting therapeutic treatment (Singer, 2013).

Connecting early sepsis recognition with pathogen identification allows for practitioners

to effectively administer proper antibiotic therapy and treatment more rapidly, thereby

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decreasing mortality and morbidity (Singer, 2013). Sepsis can be defined according to

the Surviving Sepsis Campaign of 2012 as a systemic, poisonous host response to an

infected pathogen leading to severe sepsis (Dellinger et al., 2013). In order for an

individual to be considered septic, serial ordinal symptoms must be present including

systemic inflammatory response syndrome (SIRS). SIRS describes a systemic

inflammation resulting from any major insult to the body, leading to a specific criteria

and affecting either temperature, respiratory rate, white blood cell count, and/or heart

rate. Sepsis is identified by the presence of SIRS criteria along with a known or

suspected infection. Severe sepsis with organ failure occurs in the presence of sepsis

with one of the signs and symptoms of organ failure leading to septic shock, which is

defined as severe sepsis with hypotension without response to fluids resuscitation

(Dillinger et al., 2013).

End organ failure is extremely important in the topic of sepsis; the goal of

healthcare providers is to identify and treat sepsis before any organ dysfunction occurs.

Tromp et al. (2011) reported on their wide-ranging study on septicemia that organ failure

occurred in 19.1% of sepsis patients from 1979 to 1989 and 30.2% from 1990 to 2000. In

the same study, the number of patients who experienced organ failure more than doubled

from 2.7% to 7.1%, demonstrating that sepsis is on a steady incline (2011). Rohde et al.

(2013) conducted a study evaluating the infection rate and organ dysfunction in patients

with severe sepsis in non-ICU, the study concluded that organ dysfunction was associated

with an increased mortality rate by 41%, hypotension being the most common

dysfunction.

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In a combined approach to improve the increasing rate and complications of

sepsis and severe sepsis, healthcare providers have formulated different methods to not

only rapidly identify sepsis but also treat it. As a result, the Surviving Sepsis Campaign

(SSC) was launched in 2004 (Tromp et al., 2011), and a set of guidelines was created for

sepsis management. Since the initial creation of the SSC in 2004, two newer versions

have been developed: one in 2008 and more recently in 2012. Within the guidelines

recommended by the SSC, the resuscitation bundle and the management bundle are

among the most important components for the treatment of septic patients (Dillinger et

al., 2013). Since 2004, the sepsis bundles have been implemented in ICUs, emergency

departments and step-down units but have failed to be adopted in medical surgical units

(Levy et al., 2010). Roughly 24% of patients who develop severe sepsis or septic shock

will do so in a medical-surgical unit (Tazibir, 2012). The SSC strongly encourages early

treatment and sepsis recognition through the guidelines, bundle recommendations, and

early goal-oriented therapy (EGDT). Application of such approaches has led to a

continuous quality improvement in sepsis care and has been associated with a reduction

in mortality rate (Dillinger et al., 2013). The utilization of early goal-oriented therapy

(EGDT) and sepsis bundles as recommended by SSC has demonstrated its effectiveness

through the decrease in mortality rates by about 15%-20% (Rivers & Ahrens, 2008). A

study conducted by Marwick and Davey, (2009) on the utilization of the resuscitation and

sepsis bundles concluded that care bundles can indeed improve the reliability of

evidence-based care and patient outcomes in reference to septic patients. However, as

indicated by the authors, it remains to be seen whether such success can be reproduced in

a non-ICU area such as a medical-surgical unit.

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Significance of the Problem

Since the initial development of the Surviving Sepsis Campaign guidelines

published in 2004 outlining the management of severe sepsis and septic shock, there has

been an absolute disregard on the management of septic patients in medical surgical

units. The lack of attention to medical surgical units in regard to sepsis has formulated a

problem among healthcare providers including nurses on the proper guidelines to

diagnose and treat septic patients (Nelson, LeMaster, Plost, & Zahner, 2009). Although

in recent years there has been an effort to improve the early recognition and treatment of

septic and severe septic patients in non-ICU, there is still much improvement required.

Currently, no unified approach exists to diagnose and treat sepsis in medical surgical

units. More recently with the utilization of prognostic biomarkers for sepsis

identification, there has been more confusion on proper guidelines to treat sepsis in

medical surgical units (Pierrakos &Vincent, 2010). The SSC encourages the

implementation of early evidence-based therapies, but with ICU as the main target.

“Sepsis screening tools have been developed to monitor ICU patients, and their

implementation has been associated with decreased sepsis-related mortality” (Dellinger et

al., 2013, p. 558). However, there is no mention by the SSC on creating a sepsis bundle

for non-ICU.

Healthcare providers have difficulty diagnosing sepsis not only in the ICU and the

Emergency Department but also in the medical-surgical wards (Dillinger et al., 2013). A

study conducted by Carter (2007) identified that 29% of mortality occurred in septic

patients when a sepsis bundle was implemented within the first 24 hours of admission,

versus 49% mortality when the bundle was implemented after 24 hours or not

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implemented at all. The same study also indicated the necessity to implement a sepsis

screening tool for early sepsis recognition (Carter, 2007).

Given the indistinctness of sepsis diagnosis, the use of biomarkers has become a

new frontier in identifying sepsis, especially lactic acid, procalcitonin (PCT), and serum

soluble triggering receptor expressed on myeloid cells-1(s-TREM-1). Nevertheless, it

presents a dilemma in that there is not sufficient data to support any particular biomarker

as the gold standard for sepsis identification (Pierce, McCabe, White, & Clancy, 2012).

As a result, clinicians must rely on the sensitivity and specificity of sepsis tools and a

combination of various biomarkers.

Problem Statement and Purpose

The problem is that there are no guidelines or protocols on the identification and

treatment of sepsis on medical surgical units. Healthcare providers have difficulty

diagnosing sepsis not only in the ICU and the emergency department but also in the

medical surgical wards (Dillinger et al., 2013).

The purpose of this pilot study was to develop and implement a severe sepsis

bundle on a medical surgical unit to determine if there was a reduction in hospital length

of stay and transfers to higher level of care. The bundle included a severe sepsis

screening tool already utilized at a community hospital in Miami, Florida, a newly

implemented severe sepsis algorithm for early identification of severe septic patients in a

medical surgical non-ICU and a severe sepsis order set. The rationale of the severe sepsis

screening tool was to identify severe sepsis patients before they decompensated and

became hemodynamically unstable. The purpose of the severe sepsis algorithm was to

guide nurses on the appropriate steps to implement early goal-oriented therapy in the

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event a patient screened positive for severe sepsis. The algorithm delineated the

implementation of two sepsis biomarkers, procalcitonin, and lactic acid. The idea was

that by having medical surgical nurses adhere to the implementation of the severe sepsis

tool and algorithm, they would be able to identify severe septic patients before requiring

transfer to progressive care units or ICUs and consequently reducing the length of

hospital stay.

Following the SCC 2012 sepsis guidelines, a sepsis bundle (screening tool,

algorithm, order set) was developed specifically for medical surgical non-ICU. The

bundle included an already implemented severe sepsis screening tool, a new algorithm

for nurses to follow whenever a patient screened positive for severe sepsis and a set of

orders based on the patient's condition and algorithm outcome.

It is important to understand that although the majority of severe septic patients

require ICU admission, the assessment of sepsis is not solely the domain of the physician,

critical care nurse, or emergency department nurse but of every nurse involved in the care

of the patient (Nelson et al., 2009). All nursing assessments need to take into account the

signs and symptoms of sepsis. This pilot study evaluated severe sepsis patient outcomes

by monitoring patient transfers to higher level of care and sepsis hospital length of stay.

The already implemented severe sepsis tool utilized at a community hospital in Miami,

Florida consisted of an electronic instrument that reports admitted patient information,

such as the individual's latest vital signs and laboratory work in order to detect sepsis

status. This assessment tool was performed by each nurse every shift on every patient

and was only deferred if a patient screened positive for severe sepsis. The screening tool

screened for systemic inflammatory response syndrome (SIRS), sepsis, and severe sepsis,

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based on the definitions provided by the SSC in 2012. In order to appraise the

significance of the severe sepsis tool, a retrospective study was conducted evaluating the

sensitivity and specificity of the tool.

Project Objectives

The main focus of this pilot study was to provide awareness of sepsis in the

medical surgical units by not only educating the staff but also providing better tools to

easily identify and treat septic patients in non-ICU areas. Given the growing medical and

economic burden of sepsis, by early identification and treatment of septic patients,

practitioners can ensure adequate prevention and therapy for all septic patients, thus

improving severe sepsis incidences and decreasing transfers to progressive care units and

lengthy hospital stays. This pilot study also provided the foundation of a severe sepsis

algorithm and sepsis bundle specifically designed for medical surgical units that could be

adapted into other units and hospitals. The research objectives were designed to improve

the diagnosis of sepsis and identification of patients at risk for severe sepsis and septic

shock, while empowering nurses to implement early goal directed therapy in an attempt

to decrease hospital length of stay and transfers of septic patients to higher level of care.

The objectives of this project were as follows:

1. Generate administration and management support for the project (Appendix B).

2. Evaluate septic patient’s hospital length of stay and patients transfer to higher

level of care on medical-surgical unit prior to implementation.

3. Develop and implement a severe sepsis bundle (Tool, Algorithm, Order Set) for

medical-surgical units:

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A. Phase 1: Educate medical surgical nurses on the topic of sepsis (not part of

the measurement of the study).

B. Phase 2: Decrease septic patient’s hospital length of stay and decrease

septic patients transfer to higher level of care after implementation of

bundle.

4. Evaluate the sensitivity and specificity of a severe sepsis tool.

The findings of this study had a significant impact in the areas of nursing education,

nursing practice, nursing research, and healthcare policy within the organization.

Theoretical Framework: Donabedian's Model

Donabedian's structure-process-outcome model has been utilized as a useful

theoretical framework for quality assessment, highlighting the significant relationship

between process and outcome (Donabedian, 1998). Donabedian has been recognized as

the father of quality assessment, and much of his life work was dedicated to formulating

the underpinning for improving the quality of the healthcare system (El Haj, Lamrini, &

Rais, 2013). Although born of Armenian parents, Avedis Donabedian studied medicine

in Beirut. Later as a physician, he developed a profound interest in the quality of health,

which led him to travel to the United States in 1953 in pursuit of a public health degree

(Donabedian, 1998). After receiving his Master of Public Health from Harvard

University, Donabedian assembled an extensive quantity of literature regarding health

services measuring the quality of the care being delivered. He later published his

research findings in 1966 with an article titled “Evaluating the Quality of Medical Care”

(Donabedian, 1998). “Evaluating the Quality of Medical Care” outlines all of

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Donabedian's methodology regarding the assessment and value of care and …