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Running head: IMPACT OF A HEART FAILURE SERVICE 1

Impact of a Heart Failure Service: A Solution to 30-day heart failure readmissions

A Scholarly Project Presented to

The Faculty of the Maryville University

Catherine McAuley School of Nursing

In Fulfillment of the Requirements

For the Degree of Doctor of Nursing Practice

Patricia Chafin

Spring 2018


Table of Contents

Title Page 1

Table of Contents 2

Abstract 5

Acknowledgements 6

Dedication 7

Chapter 1: Introduction 8

Study Purpose and Aims 10

Background and Significance 11

Chapter II: Review of Related Literature 18

PICO Question 18

Search History 18

Integrated Review of Literature 19

Theme 1: Single Interventions 19

Theme 2: Multiple Interventions 23

Theme 3: Proactive Approach to Heart Health 26

Theme 4: Evidence-based Research: from Practice to Policy Formation 27

Concepts and Definitions 29

30-day Heart Failure Readmissions 29

Heart Failure Service 30

Quality Improvement Path 31


Theoretical Framework 31

Conclusion 33

Table of Contents

Chapter III: Methods 35

Methodology 35

Needs Assessment 35

Study Design 36

Setting 36

Sample

36

Data Collection 37

Data Collection Instruments 38

Data Analysis Plan 38

Conceptual and Operational Definitions 39

Resources 39

Protecting Human Subjects 40

Chapter IV: Findings

42

Data Analysis 42

Results 44

Chapter V: Discussion 48


Strengths and Limitations 49

Implications for Education, Research and Practice 50

Recommendations 50

References 53

Appendix A: Human Subjects Training/Education Certification 62

Appendix B: Approval letter from Maryville University IRB 63

Appendix C: Approval letter from single facilities IRB 64

Appendix D: Sample of excel data collection sheet 67

Appendix E: IRB checklist 68


Abstract

Impact of a Heart Failure Service: A Solution to 30-day Heart Failure Readmissions

Background: Our nation’s health care system needs to prepare for this continued impact from

the baby boomers insurgency of becoming 60 years of age, and the predicted peak of heart

failure (Ellen, 2012: American Heart Association, 2017). According to the results of a data

analysis done in the government run facility, 30-day heart failure readmissions were rising, and a

solution was needed.

Objective: The purpose of the scholarly project was to determine the impact the heart failure

service (HFS) has had on 30-day heart failure readmissions.

Design: A retrospective chart review was conducted on all patients with a primary diagnosis of

heart failure or acute on chronic heart failure exacerbation from October 1st, 2013 to September

30th, 2017 (Terry, 2014). A chi-square was calculated comparing a standard heart failure follow

up group to the HFS follow up group.

Results: The results showed a significant statistical difference p =.001. Under the old follow-up

system (1) data revealed 43 non-readmits and 20 readmits, and under the new HFS system (2)


data revealed 58 non-readmits and only five readmits. The Chi-Square reported the Pearsons

crosstabulation was p = .001

Conclusions: The HFS multi-interventional approach provided a sustained continuity of care

and significantly reduced 30-day HF readmissions. Future studies can focus on 30-day

readmission rates of patients with other chronic diseases.

Keywords: 30-day heart failure readmissions, primary diagnosis of heart failure, congestive

heart failure, chronic systolic heart failure, 30-day heart failure readmissions, heart failure

follow-up protocols, preventing heart failure, and quality control measures for heart failure.

Acknowledgements

The author expresses her gratitude to her chair, Dr. Jacqueline Saleeby; you have been

invaluable, and you’re editing comments allowed me to grow as a writer. Your research

knowledge and follow-up questions challenged me as a researcher. Thank you. To Dr. Toni

Fleming, you are a daily inspiration. I appreciate your mentoring and helping me grow as a

provider. To Dr. Michael Landry, thank you for the supporting statistical analysis and for

making statistics such an uplifting and exciting learning experience. To Michele Hernandez

APRN, FNP-C, I am so thankful we shared one of the most challenging times of our lives

together as classmates. Thank you, new friend, could not have made it without you.

The author wants to acknowledge and thank Dr. Kodangudi Ramanathan and Dr. Kevin

Newman for this job opportunity and for sharing your wealth of cardiology knowledge. Thank

you, Lilly Johnson, you are a research saint. To Memphis Veterans Administrative Medical

Center for striving every day to be the best, you can be. I hope my scholarly project can become

a small part of a huge goal of improving the quality of life for our Veterans. Our Soldiers fought

for us; let us continue to fight for them.


Dedications

I dedicate this work to my family and friends and thank them for all their love and

support throughout this educational journey. Scott, you are the definition of “True Grit,” your

unyielding courage and determination over the years have proven to be a trait I most envy, and

has allowed me to persevere ever obstacle I have faced. To my sons Logan and Corey, thank you

for all the support and the many “goodnight mom, I love you” as you passed me in the office, it

was the added fuel I needed to get me through those last few hours each night. Mom, you are the

reason I stand tall with pride and thank God each day for my life. Lastly, thank you, Dad, I will

never stop missing you and will never forget your words, "Just remember when you’re walking

across that stage, I will be watching.” Thank you both for your lifelong support, sharing your

beliefs in always bettering yourself, and to never stop caring for others.

Dear God, thank you for your patience, guidance, and for never leaving my side.


Chapter I

Our nation’s health care system needs to prepare for this continued impact from the baby

boomers insurgency of becoming 60 years of age, and the predicted peak of heart failure.

Between the years 2000-2050 the aged 60 and over population will have a dramatic increase

from 600 million to 2 billion (Ellen, 2012). Coupled with a recent statistic by American Heart

Association (AHA); Heart failure (HF) is the leading cause of hospitalization among the

population of 65 years and older, it is on the rise and forecasted to peak at a 46% increase by the

year 2030 (American Heart Association, 2017). These statistics collectively reveal that the

nature of heart disease is changing as evidenced by the forecasted impact.

As the baby boomers age and the elderly population increases, HF will become more

consequential. Patient quality of care will be in jeopardy if the healthcare system is not prepared

to take on this growing population of chronic disease. Health care facilities will be looking at

longer lengths of stay, a rise in 30-day readmissions and severely under estimated healthcare

costs.


Since the initiation of the Affordable Care Act in 2010, HF has been every hospital's

main topic of conversation from the business office, administrations, quality improvement, risk

management to nursing management (Giuliano, Danesh, & Funk, 2016). The most expensive

Medicare diagnosis in the United States is heart failure. The cost of heart failure overwhelmingly

exceeds those of breast and lung cancers combined. The annual costs are estimated at 35.1

billion dollars a year with projected increases over the next few years (American Heart

Association, 2017). Due to these overwhelming statistics, researchers have put this topic above

many other health care issues (Titler et al., 2008)

The interest for this project stems from a former Doctorate Nurse Practitioner (DNP)

student who did her scholarly project on 30-day readmission rates of congestive heart failure at

the same facility. According to the results of a data analysis done in the VAMC’s, 30-day heart

failure readmissions were rising, and a solution was needed. The Cardiology Department had a

flourishing heart failure clinic but due to the clinic volume, post-discharge follow-ups were seen

by one month, which proved to be too late. These findings led to an additional job opening for a

new Nurse Practitioner (NP) position in the Cardiology Department for the sole purpose of

beginning a Heart Failure Service (HFS) that focused on early follow-up to reduce 30-day

readmission rates.

That new NP of the HFS is now writing this DNP scholarly project on the construction,

trials, tribulations, and path that led to the development of the HFS. The new NP and a staff

cardiologist started the HFS in the fall of 2015. The initial plan was for the patients to be seen by

the HFS two-weeks after discharge. The NP quickly learned two weeks was too late because the

patients were already readmitted. So, it was back to square one. The NP realized better

preparation was needed for establishing the HFS, and the service needed to have a larger


inpatient role to meet the identified needs of the patient. This early initiation phase of the HFS

determined a broader approach was needed to meet the objective of reducing 30-day HF

readmissions. Single interventions were initiated one by one as the trials and tribulations of the

HFS began to reveal themselves (in other words 30-day readmissions continued to occur). The

HFSs approach evolved and grew daily as it experienced the causes of 30-day readmissions.

The HFS follows the patients admitted with a primary diagnosis of HF from admission to

discharge and for the following 30-days. The HFS has incorporated multiple interventions to

assist in reducing 30-day HF readmissions. The service concluded those patients diagnosed with

HF needed continuity of care to begin at diagnosis and to continue throughout their lifespan.

When continuity of care is lacking, poor patient outcomes ensue. This chronic disease needs

ongoing management, and by facilitating a continuity of care, improved patient outcomes are

sustained (Titler et al., 2008). A goal of this scholarly project is for the facility to adopt this

quality improvement design and apply these new guidelines for a sustainable and consistent

continuity of care that leads to the improvement of patient outcomes for all chronic diseases.

The HFS works much like the heart; it is made up of an inflow of patients, departments,

revolving doors, and an outflow of improved quality care. It began with one cardiologist and one

nurse practitioner, but now includes the services of Patient Aligned Care Team (PACT),

Hospitalists, Social Workers, Pharmacists, Physical Therapists, Home Based Primary Care

(HBPC), Care Coordination Home Telehealth (CCHT), Palliative Care, and Hospice Care.

Study Purpose and Aims

This scholarly project takes a practice change and utilizes a quality improvement path to

address the issue of 30-day heart failure readmissions. The purpose of the scholarly project is to

determine the impact the HFS has had on 30-day heart failure readmissions. The aim is to


improve patient continuity of care to allow for better outcomes, which in turn may decrease 30-

day heart failure readmissions. Presently there is no “one” standard of care for patients

discharged with heart failure. Patients admitted to the VA with an acute or chronic heart failure

exacerbation are discharged with either an order for follow-up by their primary care clinic,

cardiologist or the HFS, with varying time frames of 1 week to 3 weeks.

PICO Question

In patients with heart failure disease, what is the effect of a Heart Failure Service, in

comparison to the present outpatient follow-up practice, on readmissions within 30-days?

Background

Heart failure has become an epidemic. The astounding breakthrough in cardiology that is

allowing patients to survive myocardial infarctions is also one of the culprits that have led to this

vast population of heart failure patients. Paradoxically those patients that underwent an emergent

cardiac catheterization and intervention for myocardial infarction, and survived, are now living

with a weakened heart muscle caused by the acute cardiac insult (Pazos-López, 2011). The

American Heart Association recently revealed over six million Americans is living with heart

failure, and after the age of 40, one in five Americans in their lifetime will develop heart failure.

The cost to Americans each year is estimated at 14.3 billion dollars with an expected rise to 30

billion over the next 15 years (American Heart Association, 2017). The hospitals are affected as

well, since the initiation of the Affordable Care Act in 2010; hospitals have had to pay penalties

leveraged against them nationwide along with significant payment and reimbursement reductions

(Giuliano, Danesh, & Funk, 2016).

There are two types of heart failure, systolic and diastolic. Systolic heart failure is the

weakening of the heart muscle enabling the heart to pump blood sufficiently to meet the body’s


demands. Diastolic heart failure is the heart muscles’ inability to relax and allow for an adequate

amount of blood to fill the heart chambers, so when the heart contracts the volume of blood is

inadequate to meet the body’s demands. However, the outcomes are the same with equal

amounts of hospitalizations and mortality rates with both right and left sided heart failure

(American Heart Association, 2017).

The most common heart failure classification used in research and practice is the New

York Heart Association (NYHA) functional classification. The physical limitations define the

four classifications during physical activity: 1) Class I, no limitation of physical activity.

Ordinary physical activity does not cause undue fatigue, palpitation, and dyspnea, 2) Class II,

slight limitation of physical activity but comfortable at rest. Ordinary physical activity results in

fatigue, palpitations, and dyspnea, 3) Class III, marked limitation of physical activity and

comfortable at rest. Less than ordinary activity causes fatigue, palpitation, or dyspnea, 4) Class

IV, unable to carry on any physical activity without discomfort and experiences symptoms of

heart failure at rest. If any physical activity is undertaken, discomfort increases (American Heart

Association, 2017, p.1).

The most common heart failure rating system used in research and practice is the

American Heart Association (AHA) heart failure stages. The four stages are determined by the

progression of heart failure symptoms: 1) Stage A, no objective evidence of cardiovascular

disease. No symptoms and no limitation in ordinary physical activity, 2) objective evidence of

minimal cardiovascular disease. Mild symptoms and slight limitation during ordinary activity are

experienced and comfortable at rest, 3) objective evidence of moderately severe cardiovascular

disease. Marked limitation in activity due to symptoms, even during less-than-ordinary activity

are experienced and comfortable only at rest, 4) objective evidence of severe cardiovascular


disease. Severe limitations are experienced. Experiences symptoms even while at rest (American

Heart Association, 2017, p.1).

Heart failure is chronic, and there is no cure. As HF disease progresses, the patients

become more and more debilitated, leading to more hospitalizations and eventual palliative and

hospice care (American Heart Association, 2017). However, the HFSs goal is to slow down the

progression of a patient with HF through early education, so adherence to treatment is more

likely to occur. Once a HF patient is educated and realizes those factors that contribute to the

disease progression, the more likely he/she will choose to take control of their heart failure. A

HFS motto that is modeled after the Internal Locus of Control Theory “do not let your heart

failure be in control; you control your heart failure” (Lefcourt, 2014).

Researchers need to make HF prevention a priority. Strategies need to be created for the

detection and treatment of those patients at risk for HF (Hernandez, 2013). The U.S Preventive

Services Task Force (USPSTF) was organized over 25 years ago. Their mission has been to

improve the health of Americans. Their primary task over the years has been the development of

evidence-based screening and counseling recommendations to assist in battling those high

burden diseases. Screening for early detection of heart failure should be a priority of USPSTF

(U.S. Preventive, 2017).

Significance

Healthcare

The focus on 30-day HF readmissions gained further interest after the Affordable Care

Act was initiated in 2010. The “Hospital Readmissions Reduction Program” section 3025 of the

Affordable Care Act penalizes hospitals with an excessive 30-day readmission rate. The

penalties have been leveraged against hospitals nationwide and consist of significant payment


and reimbursement reductions (Giuliano, Danesh, & Funk, 2016). The pressure placed on

hospitals to remedy 30-day heart failure readmissions led to numerous research projects,

conferences, letters, and abstracts all focused on evidence-based strategies.

Quality Improvement and Risk Management Departments in every hospital throughout

the country began to review patient data so quality control measures could be developed to

reduce 30-day readmissions. Strategies for readmission reduction would require thorough

analysis, planning, and execution. Quality measures were evaluated, and patient outcomes were

identified. Gaps were found in the coordination of care for the heart failure patient, uniformity in

the continuity of care was missing (Ibrahim & Januzzi, 2016).

Nursing

The research on 30-day HF readmission strategies over the past decade has revealed a

statistically significant improvement in cost reduction and readmission rates related to HF

(White, Brown, & Terhaar, 2016). However, these comprehensive management approaches to

this epidemic focused on outpatient care only. The gap in evidence-based research was caused by

omitting interventions for the hospitalized inpatient with heart failure. Continuity of care is a

core element in health care management but seems to be lacking from the inpatient to outpatient

setting. The care for an acute or a chronic heart failure exacerbation admission should start on

the first day of admission, and not stop on the day of discharge (White, Brown, & Terhaar,

2016).

In the Giuliano et al., (2016), the patient outcomes were related to adequate nursing staff.

Hospital administration needs to evaluate the monetary gain it receives based on the reduction of

HF readmissions. Also, hospital administrators need to recognize the reduction of readmissions

is directly correlated with adequate nursing staff. The discontinuity of care leads to poor patient


outcomes, which leads to readmissions. A larger nursing staff would give rise to the needed

uniformity in the continuity of care. In turn hospitals would see direct cost savings, improved

quality of care, and a direct effect on quality improvement processes and approaches hospitals

need to battle this consequential epidemic.

Advanced Practice Nursing

The HFS works in close collaboration with the Patient Aligned Care Team (PACT) to

promote patient continuity. The PACT is known in the private sector as a Primary Care Clinic

and is often the first provider to see the patient with HF. The PACT needs to focus on those

patients with comorbidities that increase the risk of developing heart failure as in coronary artery

disease, hypertension, valvular disease, congenital heart defects, lung disease, alcohol, and drug

abuse. Providers should be the starting point for continuity of care. A preventive approach could

be considered an intervention and lower the incidence of HF in the patients aged 60 and older

(American Heart Association, 2017).

An objective of the HFS is to concentrate on preventive measures and assist the PACTs

in tackling “the elephant in the room.” The HFS NP role is to bring the primary care physicians,

practitioners, nurses and medical assistance to work together towards this one goal and all feel as

they are part of a big mission. That is to reduce the diagnosis of heart failure, and for those

patients already diagnosed to slow the progression of their heart failure disease.

The goal for the PACTs is to maintain the HF patients in NYHA Class I and II, and AHA

Stages A and B, through education. As health personnel we have all seen the multiple

hospitalizations, debilitating effects, shorten lifespan and the toll it takes on the patients with

heart failure and their families. The motivation is there, and with guidance from the HFS, this


additional approach can assist in the reduction of admissions and readmissions caused by heart

failure.

As outpatient care strategies emerge, readmission rate reduction looks promising

(Bowers, 2013). However, promising will not go any further unless the gap between research

evidence and standard of practice is unified. The knowledge acquired from our experience and

research is of little value if the evidence-based research is not placed into practice (White,

Brown, & Terhaar, 2016).

Practice Support for Project

The VAMC, as a whole, is very involved in academia. The Veterans Administration has a

well-funded research and development program. This scholarly project will be another welcome

addition to our department’s vast research resources.

Benefit of Project to Practice

The 30-day heart failure readmission rate continues to be a top priority of VA

administrators. Strategic Analytics for Improvement and Learning Value Model (SAIL) was

designed by the VA to allow each VAMC to summarize their system performance. There are a

total of 26 quality measures which assess death rate, complications, patient satisfaction and

overall efficiency of individual VAMC (Quality, 2017). This scholarly project will be of benefit

because it will describe the initial framework, multidisciplinary approach, and statistical analysis

outcomes of the heart failure service.

The HFS was developed with the objective to reduce 30-day HF readmissions. The

service began approximately two years ago as a result of a former DNP student’s scholarly

project. The DNP prepared nurse can close the research to practice gap by taking found

knowledge from a previous study and furthering research on the same topic. Research evolves


and leads to further questioning. The goal of this scholarly project is to examine the difference

between the HFS and present standard of care to make the HFS become the new standard of care.

Presently the patients with heart failure are referred to their PACT team, Cardiology or the Heart

Failure Service for their post discharge follow-up.

Conclusion

As the heart failure epidemic surges and the over 60 population multiply by the millions,

our health care system needs to execute and implement the appropriate strategies to head off this

potential catastrophic health related issue (Ellen, 2012). Healthcare facilities should focus on

heart failure prevention and slow the progression of those impaired by this disease. The focus of

hospitals and their medical teams should be one of continued care at the start of a new heart

failure diagnosis or a chronic heart failure exacerbation admission to 30-days after discharge.


Chapter II

The literature review reveals other aspects of this research phenomenon of interest on

heart failure and advocates a broader approach is needed to control this heart failure epidemic

(Ellen, 2012). This more comprehensive approach is how the HFS addressed reducing 30-day

readmissions. The patients admitted to the facility with an acute or chronic heart failure

exacerbation are followed by the HFS until discharged and then placed into a 30-day follow-up

protocol. At the onset of the HFS, the cardiologist and nurse practitioner (NP) identified the heart

failure population’s specific needs and realized additional services were needed. Their objective

was to establish a foundation of best practices so consistent continuity of care could ensue. The

goal is to develop new practice guidelines to result in improved patient outcomes and decreased

30-day readmissions.

PICO Question

In patients with heart failure disease, what is the effect of a Heart Failure Service, in

comparison to the present outpatient follow-up practice, on readmissions within 30 days?

Search History


The Maryville University Library was utilized for a database search to find evidence to

support the scholarly project. The search terms included; primary diagnosis of heart failure,

congestive heart failure, chronic systolic heart failure, 30-day heart failure readmissions, heart

failure follow-up protocols, preventing heart failure, and quality control measures for heart

failure.

By utilizing the Cochrane Research link, the following inclusion criterion was selected:

full test articles, peer reviews, research articles, clinical trials, meta-analysis and a limited date

from 2007 to 2017. The data were successfully recovered from Cumulative Index to Nursing and

Allied Health Literature (CINAHL), Medline, Medscape, EMBASE, and Google. A total of 50

journal articles were critiqued, and 30 of those articles were used in the literature review. A total

of 10 journals and periodicals delivered to the Cardiology department at the VAMC were

analyzed, and four articles were added for a total of 34 articles in the literature review.

Integrated Review of Literature

The purpose of this literature review is to integrate and synthesize the past and recent

studies of heart failure patients, and those interventions researchers have hypothesized to reduce

30-day readmissions. Though each researcher set out to accomplish the same goal, each study

ventures into separate directions with various outcomes. The literature review aims to identify

evidence-based research on the successful strategies of reducing 30-day heart failure readmission

rates. The literature review articles are organized under four themes: single interventions,

multiple interventions, proactive approach to heart health, and evidence-based research; from

practice to policy formation.

Research has shown the largest reduction in 30-day readmissions is related to the

combination and implementation of multiple single interventions. There have been no published


studies revealing the effectiveness of combining individual interventions to reduce 30-day HF

readmissions (Kripaini, Theobald, Anctil, & Vasilevskis, 2014). The statistics continue to reveal

a lack of knowledge to reducing 30-day readmission rates (Bowers, 2013). The literature review

implicates research to reducing 30-day HF readmissions is available; however, it appears that

strategies need to align with the patients’ needs to provide adequate continuity of care.

Theme 1: Single Interventions

Due to the rise in 30-day heart failure readmissions and the subsequent costs associated

with this disease, numerous interventions have been developed and implemented to reduce

readmission rates. However, there continues to be a significant variability in which single

interventions are most effective. The key to a successful HF program is in the coordination of the

patients care and incorporating those services/interventions to meet their needs (Kripaini et al.,

2014).

A post-discharge telephone contact is useful in transitioning the patient from hospital to

home. The phone call has many facets and intervention possibilities. Early patient education

during admission is important and needs to be frequently evaluated. The post-discharge phone

call can be used to assess the patient or responsible caregivers understanding (Inglis et al., 2010).

The phone call was also beneficial in evaluating progression of symptom improvement or quick

resolution of potential readmission (e.g., patient reports weight gain of 5 lbs. in past two days)

(Chaudhry et al., 2010). The HFS NP needs to determine a reason for weight gain; medication

noncompliance, misunderstanding in dosing, or not having the medication. Any of the three

reasons can be mitigated to prevent re-admission. Often, a post-discharge phone call can lead to

multiple follow-up phone calls within the same day or days to follow (Melton et al., 2012).

Heart failure education and post-discharge telephone contact within two weeks by a Nurse


Practitioner improved 30-day HF readmissions by 8.5% in this Florida Hospital in 2012

(Simpson, 2014). The Floridian Hospital continued this practice, and by 2013 the readmission

rate decreased another 4.5% to a 13% decrease of 30-day HF readmissions (Simpson, 2014). The

timing of the post-discharge telephone call revealed an efficient outcome by allowing for

evaluation of outpatient progress with a quick resolution of any issues that could lead to a

potential readmission (Melton et al., 2012). In comparison, studies on post-discharge phone calls

could not conclude telephone follow-up was an effective intervention within one month of

discharge (Mistiaen & Poot, 2008; Domingues et al., 2011).

The weakness in the telephone follow-up study indicated 21% of the final telephone

interventions were not completed due to patient lost in follow-up (Chaudhry et al., 2010). High

risk of bias was noted and determined unreliable blinding methods could lead to exaggerated

estimates of the telephone outreach (Inglis et al., 2010; Mistiaen & Poot, 2008). As well as, the

study trials included a small sample size which limits the study (Hernandez, 2013).

Telemonitoring has become an effective tool and alternative to frequent clinic visits. The

monitoring system is an electronic device set up in the patient’s home that allows for observation

of patients symptoms and physiologic data. Those post-acute patients with heart failure having

barriers in preventing frequent office visits (e.g., distance, cost, transportation) can receive close

monitoring at home with telemonitoring. Studies have shown effective telemonitoring

significantly reduces readmissions as well as death in patients with heart failure (Takeda, 2012:

Smith, 2013). A quality comparison study done over a four-month period looked at home

telehealth as an intervention for readmission reduction. The study indicated a significant

decrease in 30-day readmission rates in those patients receiving telemonitoring (William, 2016).


Early follow-up plays a vital role in reducing 30-day readmissions (Hernandez, 2013).

The definition of an early follow-up is a seven-day outpatient visit with the patient’s primary

care clinic (Hernandez, 2013). Timely outpatient follow-up is a key strategy in reducing 30-day

readmission rates (Jackson, Shahsahebi, Wedlake, & DuBard 2015). The Jencks et al. (2009)

study compared heart failure readmission rates to the actual time of the patients time of follow-

up and found the highest percentage of readmission were within ten days. The hospitals with

more efficient discharge planning could have better patient outcomes and less 30-day

readmissions (Hernandez, 2013).

Trends in early follow-up and the days directly following discharge are the most

vulnerable for the heart failure patient (Peikes, Chen, Schore, & Brown 2009: Lee et al., 2016).

The studies relative strength came from using a randomized design in each program, evaluating

15 separate interventions in varying facilities, and following their study subjects longer than past

research (Peikes et al., 2009). A nested matched case-control study focused on early outpatient

contact within seven days of discharge to patient contact between days 8 to day 30 after

discharge with readmissions. The study found a reduction in readmissions with a seven-day

follow-up appointment (Lee et al., 2016). The results implicated the earlier a patient is

readmitted post-discharge, the more likely that readmission could have been prevented (Lee et

al., 2016: Peikes et al., 2009). Centers for Medicare and Medicaid Services surmised from their

findings that 61% of those patients with heart failure were readmitted within 0-15 days after

discharge, due to re-accumulation of fluid (Dharmarajan et al., 2013).

In a large retrospective study done in all of North Carolina’s 100 counties, patients with

heart failure that had multiple comorbidities had less 30-day readmissions with a 7-day follow-

up. Several strengths were noted in the large demographic and diverse population and having


complete visibility to patient records including past medical history, diagnosis, procedure and

medication history (Jackson et al., 2015). Those weaknesses found in the study included results

based on a single state and limited to Medicaid patients. An observational study compared early

follow-up after discharge and improved patient outcomes (Hernandez, 2013). The researcher had

noted a trend in 30-day readmission prevention using a coordination of care approach when

preparing the patient with heart failure for discharge. A weakness in the study was unmeasured

confounding variables could not be ruled out because patients were not randomly assigned to

early follow-up (Hernandez, 2013). A limitation was caused by hospital discharge protocols not

being available for comparison. Also, the individual outpatient clinic visits were not compared in

their thoroughness or which professional; physician assistant, nurse practitioner or physician

examined the patient (Hernandez, 2013).

Theme 2: Multiple Interventions

A key strategy in the management of HF is finding an effective combination of

interventions that support successful patient outcomes (Frankenstein, Fröhlich & Cleland 2015).

Emerging patterns with inpatient education, post-discharge phone calls, one-week follow-up

visits, use of Home Based Primary Care (HBPC), and Care Coordination Home Telehealth

(CCHT), were noted within the trended data highlighting those interventions that provided

continuity of care and best practice outcomes.

An observational study looked at an APRN-led transitional strategy beginning within 72-

hours of hospital admission and extending to the 3rd month after hospital discharge.

Readmissions were reduced by 48% (Stauffer et al., 2011). Interventions led by a Case

Management HF specialist nurse had a reduction within six months (Takeda et al., 2012). In a

randomized control trial by compared standard follow-up care to a multidisciplinary specialized


outpatient heart failure clinic. Not only was there an 18% reduction (57% to 39%) in 30-day

readmissions, but the outpatient clinic reduced hospital stays and improved quality of life

(Ducharme, Doyon, & White, 2005).

A comprehensive hospital-based intervention using a transitional model in stand-alone

community hospitals found no significant difference in 30-day HF readmission rates (Linden &

Butterworth, 2014). This hospital-based study was conducted in a large sample size, and in a

non-academic, non-integrated health system, unlike the typical setting for most clinical trials,

which gave strength to the study. However, the study did not have access to outside hospital data

for 30-day readmissions and had to rely on self-reporting (Linden & Butterworth, 2014).

Home-based primary care (HBPC) has proven to be an effective intervention and is often

partnered with Telemonitoring. Home-based primary care is another alternative to frequent

clinic visits and allows for the patients with HF to have their needs met while at home. HBPC is

a home care program led by a primary care physician, nurse practitioners, nurses, nursing

assistants, pharmacists, social workers, and dietitians (Linden & Butterworth, 2014: Klein,

Hostetter, & McCarthy, 2017). Home-based primary care fills the gap for close HF management

when the patient is unable to be seen in the clinic (Klein et al., 2017: Peikes et al., 2009). Studies

have shown optimized care leading to improved patient outcomes, satisfaction from patients and

families, along with cost savings due to a prevention of readmissions once discharged home

(Klein et al., 2017).

A multi-intervention study included telephone calls, clinic visits, and home care

assistance over an average of 63 days with a significant increase in quality of care, patient

satisfaction and decreased healthcare costs (Cykert, 2012). The integration of residents into a HF

readmission reduction program was analyzed. The interventions included inpatient education,


home health services, and a one-week follow-up appointment. The readmission rate decreased

from 32% to 24% (Rabbat et al., 2012). A multidisciplinary approach focused on post-discharge

patients with HF. The interventions included a telephone nurse coordinator, HF nurse, HF

cardiologist, and a PCP. The study revealed a 25% reduction in the total number of HF

readmissions (Hines, Yu, & Randall, 2010). The next study looked at the association of long-

term outcomes of 30-day all-cause readmissions Medicare beneficiaries with heart failure. The

outcome revealed further research is needed on comprehensive approaches that integrate

outpatient and inpatient interventions to reduce heart failure admissions and ensuing

readmissions (Arundel et al., 2016). Bias was considered due to a possible imbalance of

unmeasured characteristics (Arundel et al., 2016).

Continuity of care is a core element in healthcare management. Continuity of care is a

process that involves total focus around a patient’s well-being. Continuity of care ensures that all

needs of a patient are met, monitored and evaluated (Hitch et al., 2016: Sharma et al., 2009).

The Institute of Medicine includes continuity of care as a leading attribute in defining primary

care (Sharma et al., 2009). The literature review discovered articles from 2009 to 2016,

discussing the gap in continuity of care within transitions. These transitions include inpatient to

outpatient settings, outpatient to inpatient and inpatient to outside facilities (Hernandez et al.,

2010; Sharma et al., 2009; Hitch et al., 2016). This discontinuity continues and leads to poor

patient outcomes, 30-day readmissions and increased cost of care (Hitch et al., 2016).

When continuity of care is in place the coordination of patient care can be ensured from

an inpatient to outpatient or inpatient to a skilled nursing facility. Continuity of care involves

those interventions needed so that patients’ needs are met, and best outcomes ensue (Hitch et al.,

2016: Sharma et al., 2009). Patients hospitalized with heart failure are highly vulnerable due to


the complexity of the disease, multiple comorbidities and are often in a higher age group. When

multiple clinicians are involved in their care, and length of stay is critical, transitioning of care is

often difficult to occur in a timely manner (Hernandez et al., 2010).

Studies show when continuity of care in transitioning is a team-based intervention,

hospital readmissions is significantly reduced. By improving the quality of transitional care, this

fragmented health care system can be resolved, and continuity of care will be sustainable and

occur across all settings (Hernandez et al., 2010; Sharma et al., 2009; Hitch et al., 2016).

Limitations noted by Hernandez et al. (2010) where the rates of physician one week follow-ups

at post-discharge were low and substantially varied among hospitals. As well as the researchers

were not aware of the hospitals discharge protocols. An effective discharge protocol could have

positive readmission outcomes and skew the results. In Sharma et al. (2009) the continuity of

care was based on database analysis and did not include physician notes that would have

mentioned additional interventions within the continuity of care. In Hitch et al. (2016) had a

considerable limitation in that the study was implemented in an outpatient primary care setting,

thus limiting effectiveness in other healthcare facilities.

Theme 3: Proactive Approach to Heart Health

Those diagnoses identified as avoidable hospitalizations are labeled as ambulatory care

sensitive conditions (ACSCS) by the federal government. The ACSCS is used as Preventive

Quality Indicators. Congestive heart failure (CHF) is an ACSCS. A study on preventable

hospitalizations analyzed CHF admissions during 1995-2009. The weighted number totaled

15,208,518 hospitalizations, an average of 1,013,901 each year (Will, Valderrama, & Yoon,

2012). Health care systems have an opportunity to reduce cost by reducing avoidable

readmissions, and in turn simultaneously improve patient’s quality of care and experience in a


proactive approach (Kripalani, Theobald, Anctil, & Vasilevskis, 2014). Patient-Centered

Outcomes Research (2014), found there is a lack of evidence for more direct and effective

patient-focused interventions (O’Connor et al., 2016). The attitude of hospitals and practitioners

should be one of continued care from the start of a heart failure diagnosis throughout the

patient’s lifespan. The Medical Care Research study found multiple reasons for HF

hospitalizations; no knowledge of their disease, no knowledge of low sodium diet, lack of a

regular source of care, no form of transportation, income level, personal health practices, and

non-use of health services (O’Connor et al., 2016).

A study done on establishing a baseline to monitor trend and disparities, found preventive

measures for HF exist and are in clinical guidelines for diagnosis and management. However,

clinical guidelines are infrequently adhered to by primary care teams (Will et al., 2012). Strength

in the study design was the large study population over a span of fifteen years, which established

a solid baseline for forthcoming monitoring of health disparities (Will et al., 2012). The patient

risk factors were not listed adding weakness to study results (O’Connor et al., 2016).

Theme 4: Evidence-based Research: from Practice to Policy Formation

It is evident from the following studies that the needs of patients diagnosed with heart

failure have not been addressed by a method of clear policy formation. When change is made at

the policy level, lives are saved (Heidenreich et al., 2013). Heart failure readmissions continue to

very state to state and standardization of HF interventions would reduce rehospitalization

(Balogun, Idowu, & Sarumi, 2016). Improving 30-day HF readmissions is possible and

standardizing HF interventions was suggested (Balogun et al., 2016). Studies have shown that

20-40% of HF readmissions occur in a different hospital within weeks of discharge from a

previous hospital causing lose to follow-up (Balogun et al., 2016). The American Heart


Association heart failure clinical guidelines recommend 7-10 day post-discharge follow-up. A

recent analysis revealed 52% of patients admitted for acute or chronic heart failure did not have

an outpatient follow-up visit (Driscoll, Meagher, Kennedy, & Patsamanis, 2016).

The efficient use of evidence-based resources is lacking, and policy initiatives for heart

failure management need to move to the front line, so all hospitals and clinics are operating at

high standards (Heidenreich et al., 2013). While continued clinical research looks at new

medication regimens and devices, heart failure management, protocols, policy, and procedures

need to be fully initiated. An expansion in health care policy on HF prevention and

improvement in HF management should be a national health care focus so that the US will be

prepared for the growing HF population and limited healthcare resources (Heidenreich et al.,

2013).

The Heart Failure Society of America (HFSA) Guidelines found many patients were

discharged too early and were still in decompensated heart failure at the time of discharge. These

findings urged HFSA to design a multidisciplinary HF Discharge Readiness Checklist to be

placed into their guidelines (Frederick et al., 2016). A retrospective study used the checklist for

18 months and revealed an 18% improvement. The checklist improved continuity of care

including quality of care, morbidity, patient and family satisfaction along with cost savings. A

study done on admission order sets based on clinical practice guidelines revealed a reduction in

30-day readmission rates and inpatient mortality (Ballard et al., 2010). However, an

overestimated effort to the order set intervention led to a selection bias (Ballard et al., 2010).

Better patient outcomes were related to adequate nursing staff. A recommendation for

further research is hospital administration needs to evaluate the monetary gain it receives based

on the reduction of HF readmissions. The study could recognize the reduction of readmissions is


directly correlated with adequate nursing staff. A larger nursing staff would have direct cost

savings, improve quality of care, and directly affect those quality improvement processes and

approaches hospitals need to battle this consequential epidemic (Giuliano et al., 2016). Inpatient

strategies that focused on continuity of care led to improved patient outcomes during

hospitalization and reduced 30-day readmission rates along with a reduction of inpatient

mortality. The evidence supports more extensive approaches to inpatient strategies to improve

continuity of care are needed for further improvement of patient care (Kim & Han, 2013).

The gaps are evident in the literature review and leave behind unanswered questions. The

challenge lies in the interpretation of evidence-based research into practice. This evidence-based

research is available, but unless it is put into practice, health care will never see these promising

results. As mentioned in the introduction, health care facilities need to realize the importance of

applying this found knowledge to practice, and researchers need to work alongside the policy-

makers to place evidence-based research into policy (Cowie et al., 2014).

Concepts and Definitions

The major concepts were taken from the purpose statement and will be explained and

defined in the list below.

30-day Heart Failure Readmissions

An unplanned readmission outcome of patients with heart failure within 30-days of their

discharge dates is labeled as a “30-day heart failure readmission.” This term is also a health care

delivery measure developed by the “Centers for Medicare and Medicaid Services (CMS) and the

Medicare Payment Advisory Commission (MedPAC).” The complete title of the measure is;

"Hospital 30-day, all-cause, risk-standardized readmission rate (RSRR) following heart failure


hospitalization." The goal is to improve patient outcomes from the incentives created by

readmission measures (U.S. Department of Health and Human Services, 2015).

Heart failure 30-day readmissions have become a public health problem posing an

economic burden with expected growth over the next 20 years in the United States (Lee et al.,

2016). The new cases reported for age 65 years and older reveal 10 per 1,000 people are

diagnosed with heart failure, with an estimate of 5.7 million Americans living with heart failure

over the age of sixty-five (Kim & Han, 2013).

A position taken by Centers for Medicare and Medical Services (CMS) looked at these

statistics as a reflection of “poor health care quality and efficiency.” The CMS stepped into

action by publicly posting “30-day risk-standardized readmission rates” not only on heart failure

but included myocardial infarctions and pneumonia. The CMS logic behind this public posting

was to bring incentives to improve patient care quality, which in turn would reduce those

preventable readmissions (Dharmarajan et al., 2013).

As previously mentioned the predictions are not only astounding but worrisome and are

adding increased pressure to health care systems. There remains to be a focus by researchers to

amend this issue of rising heart failure admissions. However, there persist to be insufficient

evidenced-based criteria for the redesign and creation of a smooth continuous conversion in the

coordination of care (Bowers, 2013).

Heart Failure Service

As our health care facilities are concerned with reducing HF readmissions, initiation of

heart failure programs could be the answer to reducing 30-day HF readmissions. The HFS is

staffed by the Cardiology Department at the VAMC. The service is responsible for following

patients admitted with acute or chronic decompensated heart failure exacerbation. The patients


are followed at the start of admission, through the hospital course, and after discharge for 30-

days. The HFS is guided by a NP and staffed by a Cardiologist. The NP works in close

collaboration with the admitting Cardiology Team or admitting Hospitalists. The length of stay

for a heart failure exacerbation is four days unless otherwise complicated with additional

diagnoses. Heart failure education is vital and allows the patient to understand the importance of

compliance and rationale behind the need for a 2000 mg sodium diet, 2000 cc fluid restriction,

weighing every morning, medication regimen, and close follow-up once discharged (White,

Kirschner, & Hamilton, 2014).

Quality Improvement Path

The scholarly project takes a practice change and utilizes a quality improvement path to

address the issue of 30-day heart failure readmissions. The effectiveness of quality improvement

measures is only as strong as the underlying evidence-based care we put into practice (Ellen,

2012). Healthcare systems are going through a critical reorganization to reduce their costs. A

focus on restructuring health care delivery for the betterment of performance and patient

outcomes should be the strategy in reducing 30-day HF readmissions. Quality improvement

measures cannot occur until those weaknesses in the system are identified. To determine those

deficiencies, significant data analysis must take place, so appropriate strategic quality measures

can be executed to ensure success (Ibrahim & Januzzi, 2016).

Theoretical Framework

The health care system lacks in the translation of knowledge into action. This failure is an

injustice to health care, a waste of researchers’ time, and very costly. This gap between evidence-

based research to what is practiced leads to poor patient outcomes. Health care research findings

point to the corrective and effective use of treatments resulting in this sustainability of patient


care that is much needed. This realization has brought knowledge transfer to the forefront of

academia and practice settings. The Knowledge Transfer Theory (KTT) is relevant to this project

because it relates the two populations, researchers and policy makers, and how the two

organizing frameworks can translate evidence into policy (White et al., 2016). The process of

knowledge transfer allows for integrating, synthesizing and implementation of research between

the two communities (Caplan, 1979).

Holzner and Marx (1979) viewed society’s knowledge system as complex and designed a

system that took a more perspective view. The authors formulated five components to organize

the KT process; production, organization, storage and retrieval, dissemination and

implementation. The KTT can be used as a catalyst between evidence-based researches to

improving outcomes for the patients with HF. The elements can be curtailed specifically for this

scholarly project.

The five KTT components and their relevance are as follows: 1) Production: prior

research concluded patients with heart failure needed closer follow-up once discharged. An NP

was hired to initiate a clinic with the objective of reducing 30-day HF readmissions, 2) Organize:

Developing the HFS and evaluating the facilities standard of care, 3) Storage and Retrieval:

Collection of data on patients with 30-day heart failure readmissions on pre and post Heart

Failure Service from 2013-2017, 4) Dissemination: Evidence-based research to practice

Implementation; Policy Formation (Holzner & Marx, 1979).

As previously discussed, the Affordable Care Act brought a surprising amount of

attention to healthcare facilities. High-quality patient care has become increasingly necessary and

placed in the forefront of all hospitals (Giuliano et al., 2016). This improved quality of care isn’t

a new wave that will eventually go out of style. On the contrary, when effective implementation


of evidence-based practice is consistent, healthcare facilities will see sustainability in patient’s

continuity of care (Cowie et al., 2014).

Practice guidelines are designed from proven treatments and need to be used to prevent

variations in practice. However, if researchers and policy makers are not working together, their

independent approach will continue to be unrecognized. Research on reducing 30-day

readmissions have been ongoing with no concrete foundation lain for best practices or

implementation of practice guidelines (Cowie et al., 2014). If the knowledge transfer theory is

used to assist policy formation, healthcare facilities will see an improved continuity of care in

clinical practice, quality of care and quality of life for all patients (Caplan, 1979).

The DNP-prepared nurse is equipped to lead this endeavor of closing the research to

practice gap. The practitioner-researcher can lay the groundwork of research-based evidence for

policy formation to take place (Vincent, Johnson, Velasquez, & Rigney, 2010). The research

results will bring value to the knowledge transfer theory. The DNP students’ goal is to work

alongside the policy makers at the VAMC to place this evidence-based research into policy.

Conclusion

The literature review leaves behind unanswered questions and despite these research

efforts and evidence-based recommendations, hospitals continue to struggle with preventing 30-

day readmissions. As previously mentioned, the people running the health care facilities need to

realize the importance of applying this found knowledge to practice and researchers need to work

alongside the policy makers to place this found evidence into policy. The gaps are between the

research evidence to the policy. The challenge lies in the interpretation of evidence into practice.

However, a more obvious disparity is apparent. The evidence is understood and being

practiced, but not as efficient as it should be. First, the knowledge gained from research to reduce


30-day readmissions needs to be integrated and developed into a more comprehensive approach.

Next, it needs to be made into policy so adherence can be facilitated and recognized by all

professional practicing facilities. When a policy is set in place, practice is standardized, and the

quality of patient care improves (Irving, 2014). This literature review reveals evident

inconsistencies of knowledge and allows the reader to pinpoint strengths and opportunities for

improvement.

The literature review emphasized multifactorial causes of 30-day readmissions and

analyzed numerous efficacious approaches to reduce those readmissions. The studies that

revealed the largest reduction of 30-day readmissions, decreased hospital stay, and an improved

quality of care included; inpatient education, medication reconciliation, discharge preparation,

early telephone contact at 24-48 hours, and an outpatient follow-up appointment within the first

seven days. Also, the primary care setting was discovered to be a central component of this

comprehensive approach. Furthermore, the most effective outcomes occur when a multi-

intervention approach is initiated at the onset of a hospital admission. Finally, a valuable

conclusion to note is an improved perspective is needed and should start with the prevention of

heart failure and the slowing of progression of those patients diagnosed with heart failure.


Chapter III

Methodology

The Maryville University Institutional Review Board (IRB) was approved on December

13, 2017 and the IRB of the single facility research site grant was approval on October 6, 2017.

The researcher used convenience sampling in a retrospective chart review design on all patients

with a primary diagnosis of heart failure or acute on chronic heart failure exacerbation. The

retrospective date range for the study was October 1, 2013, thru September 30, 2017.

The quantitative study will answer the following research questions.

1. Has the facility experienced a reduction in 30-day HF readmissions since the HFS began?

2. Has the facility experienced a reduction in HF admissions since the HFS began?

Needs Assessment

Heart failure 30-day readmissions have become a public health problem posing an

economic burden with expected growth over the next 20 years in the United States (Lee et al.,

2016). In the fall of 2016 Center of Medicare and Medicaid (CMS) announced their plans to

expand criteria readmission fines, starting in 2017. This expansion will cause record penalties

against hospitals (Whitman, 2016). Heart failure is the most expensive Medicare diagnosis in the

United States. The annual costs are estimated at 35.1 billion dollars a year with projected

increases over the next few years (American Heart Association, 2017). This exorbitant expense

to health care led to the Hospital Readmissions Reduction Program (HRRP) in 2012. The


program requires CMS to reduce reimbursements to hospitals with above expected 30-day HF

readmissions (Whitman, 2016). Research has shown the largest reduction in 30-day

readmissions is related to the combination and implementation of multiple single interventions

(Kripaini, Theobald, Anctil, & Vasilevskis, 2014).

The 30-day heart failure readmission rate continues to be a top priority for hospitals

(Whitman, 2016). The VAMC uses a performance improvement tool called Strategic Analytics

for Improvement and Learning (SAIL). There are a total of 26 quality measures which assess

death rate, complications, patient satisfaction and overall efficiency at individual VAMC

(Quality, 2017). The VAMC is working very hard to improve those quality performance

measures. The scholarly project describes the initial framework, multi-interventional approach,

and statistical analysis outcomes of the heart failure service and will be of benefit to the SAIL

committee. The stakeholders include the Hospital Director, Chief of Medicine, Head of

Cardiology, HFS Cardiologist and Nurse Practitioner, patients and their families.

Design

Setting

The setting was a single-center hospital facility. The Cardiology Department has a

flourishing heart failure clinic that closely follows the veterans with heart failure. However, due

to the clinic volume, post-discharge follow-ups are seen at three weeks to one month. Due to the

rising readmission rates, the solution was to open an additional heart failure clinic. The Heart

Failure Service (HFS) focuses on the heart failure patient during hospitalization and throughout

the first 30-days after discharge. Not every patient admitted and discharged with heart failure is

referred to the heart failure service. Those HF patients admitted to the cardiology service are

referred to the HFS, but not all Medicine teams refer their patients to the HFS. The VAMC is an


academic facility with a monthly rotation of medical staff. The HFS is growing in popularity, but

since it is a referral service the HF patients can be referred to their Patient Aligned Care Team

(PACT), their cardiologist or the HFS.

Sample

The participant group was a retrospective study population with a primary diagnosis of

heart failure or acute on chronic heart failure exacerbation that were readmitted within 30 days of

their discharge date from October 1, 2013-September 30, 2017. The HFS began in fall of 2015.

Choosing 2013 to 2017 includes 12 quarters or 4 years. Prior to starting the HFS, data were

reviewed and revealed HF 30-day readmission rates were high, and contributing to the VAs

overall poor performance ratings. The Cardiologist used the data to gain approval for an

additional NP to focus solely on reducing 30-day HF readmissions and seeing the patients much

earlier. The DNP student of this scholarly project is the NP that was hired to start the new HFS.

The inclusion criterion was primary diagnosis of heart failure, acute on chronic heart

failure exacerbation, and readmission within 30-days of their discharge date. The researcher did

not exclude any genders or races, and had a minimum age of 18 years. The exclusion criteria was

New York Heart Association Class IV (end-stage), Stage IV Chronic Kidney Disease on

hemodialysis, Stage IV Chronic Obstructive Pulmonary Disease, under hospice care, positive

urine drug screen for cocaine and death during readmission. Assuming a medium effect size, a

sample size of 126 was needed to produce a power of .80 for a Chi-Square Analysis.

Data Collection

Using convenience sampling, a retrospective chart review was conducted on all patients

with a primary diagnosis of heart failure or acute on chronic heart failure exacerbation. The

International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and


the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM)

codes were entered into the hospital database to identify the sample population by the facilities

analyst with the researcher’s assistance. The date range for the study was October 1, 2013 to

September 30, 2017 (Terry, 2014).

Data Collection Instruments

The hospital’s electronic database provided the needed statistical collection. The

researcher used an Excel spreadsheet to record the collected de-identified quantitative

information. The ICD-9-CM and ICD-10-CM codes generated all patients admitted with a

primary diagnosis of heart failure or acute on chronic heart failure exacerbation from October 1,

2013, thru September 30, 2017. The researcher transferred the de-identified evidence from the

excel spreadsheet to a Statistical Program of Social Sciences (SPSS) program for statistical

analysis. The data collected included patient’s demographic data, inclusion criteria, and patients

with a primary diagnosis of heart failure or an acute on chronic heart failure exacerbation, no

readmission within 30-days of discharge date (scored as 0) and readmissions within 30-days of

their discharge date (scored as 1).

The Excel spreadsheet with the collected electronic data was stored on non-work issued

p-drive. This folder was created after the Associate Chief of Staff for Research and Development

(ACOS for R&D) approved the study. Access to records was limited to approved research

administrative and study personnel only. The researchers PIV card was accessed with two

personal identification codes only known by the researcher.

Data Analysis Plan

The researcher used the SPSS input to perform a chi-square test to analyze the statistics

and determined the significance in the two conditions of the independent variable (IV). The IV


had two conditions; a standard follow-up and a HFS follow-up. The dependent variable (DV) is

30-day HF readmissions.

Conceptual and Operational Definitions

Definition of the independent variables’ two conditions: 1) Standard follow-up group:

patients admitted with a primary diagnosis of heart failure or acute on chronic heart failure

exacerbation and seen after two weeks of discharge, 2) HFS follow-up group: patients admitted

with a primary diagnosis of heart failure or acute on chronic heart failure exacerbation and

followed from the day of admission to discharge and seen within two weeks after discharge.

The data points were scored as follows; standard follow-up group is scored as 1, HFS

follow-up group is scored as 2, patients that were not readmitted within 30 days of discharge are

scored a 0 for no readmit, and for those patients that were readmitted within 30 days of discharge

are scored 1 for yes readmit. This assigned two numbers for each participant, 1 for the standard

follow-up group and 2 for the HFS follow-up group under the IV. For the DV assigned numbers

are 0 for no readmit and a 1 for yes readmit. The researcher examined the findings of each

quarter to detect any significant differences. If the quarterly data shows trends in 30-day

readmissions, these trends need to be investigated further. The trends could represent a change in

seasons or weather, holidays or paydays and could help the HFS understand further reasons for

30-day readmissions. The trends could represent the growth of the HFS, as the service added

single interventions, service of additional departments and the combination of multiple

intervention approaches. The trends could represent the proactive approach to heart health with

the addition of preventive measures to the PACTs. The trends could reveal results of those

patients coded as 1, on which standard of follow-up they had received either a PACT or

cardiology follow-up visit.


Resources

The researcher has been communicating with her chair from Maryville University, class

faculty NURS 705, and supporting faculty at the VAMC. The researcher worked with the VA

data analyst within the facility in retrieving the retrospective data from the medical records. The

retrieved data was be sent by secured email to the primary investigator/researcher.

Protecting Human Subjects

An application form for approval of research with human subjects was completed and

turned into the Maryville IRB along with the VAMC IRB. The researcher took into account

confidentiality and addressed ethical considerations for this scholarly project. The data was

retrospective and de-identified. The researcher took steps to guarantee patients privacy and

prevent a breach of confidentiality. No patient identifiers were used (Matt & Matthew, 2013).

To provide data security and privacy, no hardcopy data was generated or stored for this

study. The de-identified data was stored on an Excel spreadsheet and stored on a non-work

issued p-drive. A folder was created after the Associate Chief of Staff for Research and

Development (ACOS for R&D) approved the study. Access to records was limited to authorized

research administrative and study personnel only. The researcher’s personal identity verification

(PIV) card was accessed with two personal identification codes only known by researcher.

Access will be terminated for those that are no longer approved to be part of the research study.

Records will be maintained or destroyed in accordance with the VA Records Control Schedule

(RCS 10-1). Records will be retained for 5 years.

If it would have been discovered that study data had been lost, the investigators would

have immediately notified the Information Security Officer (ISO) and/or the Privacy Officer

(PO). If lost data contained individually identifiable information (III), the person who


discovered the loss would have ensured that the PO was notified immediately. Research

Administration, the IRB, the RCO, OHRP, ORO, and the VA Office of the Inspector General

(OIG) have access to the records for regulatory purposes.

The researcher completed the Human Research Curriculum Completion Report

(HRCCR) and the National Institute of Health (NIH) training course and received a certificate of

completion as a requirement of the VAMC. The researcher was obligated to protect the rights

and welfare of the subjects during the research process. The NIH course is in response to a

Federal mandate for the protection of human subjects in research (Research, 2016). The

researcher completed the Collaborative Institutional Training Initiative (CITI Program); required

by the Maryville University and the VAMC.


Chapter IV

The overall intent is for this scholarly project to produce data that can be translated into

evidence-based criteria and placed into practice to reduce 30-day readmission rates of all chronic

diseases. This new knowledge would not only improve outcomes for patients with HF but could

be used as a guide to reducing other chronic diseases with high 30-day readmission rates. This

quantitative study answered the following research questions, 1) Has the facility experienced a

reduction in 30-day HF readmissions since the HFS began?, 2) Has the facility experienced a

reduction in HF admissions since the HFS began?

Data Analysis

The chapter reveals the results from a convenience sampling of a retrospective chart

review design on all patients with a primary diagnosis of heart failure or acute on chronic heart

failure exacerbation that were readmitted within 30 days of their discharge date. Approval of the

Institutional Review Board of Maryville University and of the single center facility was obtained.

The primary investigator worked closely with the facilities data analyst in setting up the

appropriate date range and coding for the study. The retrospective date range for the study was

October 1, 2013-September 30, 2017. The International Classification of Diseases, Ninth and

Tenth Revision, Clinical Modification (ICD-9-CM, ICD-10-CM) codes were entered into the

hospital database to identify the population. The codes coincided with those diagnostic codes that

applied to those patients admitted with a primary diagnosis of heart failure, acute on chronic

heart failure exacerbation, and 30-day heart failure readmission, along with the date range. The


hospital’s electronic database was used to provide the needed statistical collection. The data

analyst ran the retrospective chart review through the electronic data base.

Data security and privacy was provided and no hardcopy data was generated or stored for

this study. The de-identified electronic data was collected and recorded on an Excel spreadsheet

and stored on the assigned public drive (p-drive). The p-drive is a secure site within the VA

computer system used by the VA research department. The researcher used the p-drive to store

all research information related to the study.

Sample

The researcher used a G*Power application to determine the appropriate sample size. By

assuming a medium effect size of.25, a sample size of 126 was needed to have a power of .80 or

higher. The standard heart failure service operated alone until August 2015. The new Heart

Failure Service (HFS) began a soft opening in August 2015 and an official start date of February

2016. The sample population (n=126) included all patients admitted with a primary diagnosis of

heart failure. The sample population (n=126) was broken down to (n=63) for the standard follow

up group and (n=63) for the HFS follow up group.

The time frame for this study occurred from January 2nd to February 7, 2018. The

researcher used a data collection tool. The data collection tool identified the patient by a number

assigned by the researcher. The data collection tool recorded the following confounding

variables: age, race, gender, diagnosis, NYHA class, independent variables (IV), standard follow

up, heart failure service follow up and dependent variables (DV). The variables were identified

and the data points were scored as follows; standard follow-up group was scored as 1, HFS

follow-up group was scored as 2, patients that were not readmitted within 30 days of discharge

were scored a 0 for no readmit, and for those patients that were readmitted within 30 days of

discharge were scored 1 for yes readmit. This assigned two numbers for each participant, 1 for


the standard follow-up group and 2 for the HFS follow-up group under the IV. For the DV

assigned numbers are 0 for no readmit and a 1 for yes readmit.

The researcher collected data for the standard follow up group and started on

retrospective date October 1, 2013. The researcher went through each chart excluding those

patients with New York Heart Association Class IV (end-stage), Stage IV Chronic Kidney

Disease on hemodialysis, Stage IV Chronic Obstructive Pulmonary Disease, noncompliance to

medical treatment, under hospice care, a positive urine drug screen for cocaine or death during

readmission. The researcher reviewed 104 charts before collecting 63 charts from the standard

follow up group. The researcher began collecting data for the heart failure service and started on

retrospective date July 1, 2016. The date was pertinent because the HFS started officially on

February 2016 and a 4 month leeway was given for working out the “kinks” that could have

developed while starting up the HFS. The researcher reviewed 175 charts before collecting 63

charts from the HFS follow up group.

Results

A post hoc analysis indicated that the results from the sample can be generalized to the

population from which the sample was drawn (Power (1-B = 1.000.) (Crosstabs & Chi-Square,

2018). The sample consisted of 126 charts representing 123 males and 3 females. The patient’s

race demographic included 63% African American and 37% Caucasian. The ages ranged from

39 to 95 years of age with a breakdown of 31% age 64 or less, 43% were age 65-75 and 26%

were age 76-95. The sample size showed 25% had a reduced ejection fraction of .20 with a close

second at 16 % having an ejection fraction of .25, and the next highest was at 11% having a

preserved ejection fraction of .65. The samples New York Heart Association classification was

6% Class I, 62% Class II, 32% Class III, and end stage Class IV was in the exclusion criteria.


Table 1.

RACE

Frequency Percent Valid PercentCumulative

PercentValid 1 79 62.7 62.7 62.7

2 47 37.3 37.3 100.0Total 126 100.0 100.0

Table 2.

GENDER


PercentValid 0 123 97.6 97.6 97.6

1 3 2.4 2.4 100.0Total 126 100.0 100.0

Table 3.

EJECTIONFX


PercentValid .10 7 5.6 5.6 5.6

.15 10 7.9 7.9 13.5

.20 27 21.4 21.4 34.9

.25 20 15.9 15.9 50.8

.30 9 7.1 7.1 57.9

.35 8 6.3 6.3 64.3

.40 6 4.8 4.8 69.0

.45 4 3.2 3.2 72.2

.50 6 4.8 4.8 77.0

.55 9 7.1 7.1 84.1

.60 5 4.0 4.0 88.1

.65 14 11.1 11.1 99.2

.70 1 .8 .8 100.0Total 126 100.0 100.0

Table 4.

NYHA


PercentValid 1 8 6.3 6.3 6.3


2 78 61.9 61.9 68.33 40 31.7 31.7 100.0Total 126 100.0 100.0

A chi-square was calculated comparing a standard heart failure follow up group to the

HFS follow up group. The statistical results showed a significant difference p =.001. This means

that under the old follow-up system (1) data revealed 43 non-readmits and 20 readmits, and

under the new HFS system (2) data revealed 58 non-readmits and only 5 readmits. The Chi

Square reported the Pearsons crosstabulation was p = .001, meaning the study found a significant

difference.

Table 5.

Follow-up Readmit Crosstabulation

Readmit 0 1 TotalFollow-up 1 43 20 63 2 58 5 63Total 101 25 126

Research Questions

1) Has the facility experienced a reduction in 30-day HF readmissions since the HFS

began? Yes, the use of the HFS system resulted in significantly fewer readmissions when

compared to the prior system. The 30-day readmission rate for the sample n=63 standard follow

group is 32% and for the HFS follow up group is 8%. The medicare national average for 30-day

HF readmissions is 22% (Medicare, 2016).

To answer the second research question, the researcher reviewed the retrieved data for the

total admissions of patients with a primary diagnosis of heart failure for each year from 2014 to

2017.


Table 6.

Year Total Admissions % Decrease in Primary Diagnosis HF admissions

2014 2792015 195 30%2016 205 27%2017 205 27%

2) Has the facility experienced a reduction in HF admissions since the HFS began? Yes,

admissions dropped on average by 24% from 2014 to 2017. The heart failure service began a

slow start in August 2015 and an official start February 2016.

Additional Findings

The researcher included chronic obstructive pulmonary disease (COPD) Stage IV in the

exclusion criteria. Chronic obstructive pulmonary disease is one of the highest hospitalizations of

chronic diseases and accounts for more than $6 billion in U.S. health care costs (Ford et al.,

2015). The researcher was concerned with the high readmission rate of COPD that the HF

patients with COPD St. IV would skew the results. A surprising but welcoming finding during

the data retrieval were those patients with COPD St. IV that were excluded from the study were

not readmitted. This finding is relevant because a goal of the scholarly project is to use the

template for other chronic diseases with high 30-day readmission rates. Those patients with a

primary diagnosis of heart failure and COPD St. IV were not readmitted because they were in the

HFS. The continuity of care by the HFS allowed for close observation of the patients COPD as

well.

The researcher noted while collecting data for the HFS, there were patients readmitted

within 30-days of their discharge date, had not been referred to the HFS. During the patient’s

readmission the HFS was consulted, and further 30-day readmissions were avoided. The

researcher also noted the patients referred to only one department as in Home Based Primary


Care or Home Telehealth or Pharmacy Post Hospital Discharge for their follow-up instead of the

HFS all experienced much higher 30-day readmission rates.

Chapter V

The leading cause of 30-day hospital readmissions is heart failure (HF) (American Heart

Association, 2017). Heart Failure continues to be on the rise among the population of 65 years

and older and forecasted to peak by 46% in 2030. The nation’s baby boomer insurgency will

increase from 600 million to 2 billion between the years 2000-2050 (Ellen, 2012). Our healthcare

system needs to prepare for this potential record breaking population of heart failure patients. A

solution is needed or healthcare will take a big step backwards by seeing longer lengths of stay, a

rise in 30-day readmissions, and severely under estimated healthcare costs.

Discussion

There have been no published studies revealing the effectiveness of combining individual

interventions to reduce 30-day HF readmissions (Kripaini, Theobald, Anctil, & Vasilevskis,

2014). The statistics continue to reveal a lack of knowledge to reducing 30-day readmission rates

(Bowers, 2013). Frederick et al. (2016) reported the Heart Failure Society of America (HFSA)

Guidelines found many patients were discharged too early and were still in decompensated heart

failure at the time of discharge.

In preparation for establishing the HFS in 2015, a chart review was done on those 30-day

heart failure readmissions from 2012-2014 at the VAMC. The HFS needed a starting point and

by finding out why the patients were readmitted was a good place to begin. The chart review

noted: 1) coding issues, 2) patients were still in decompensated HF when discharged, 3)


discharged home without their new medications, 4) not educated on low Na diet, fluid restriction,

medications, and to weigh every morning.

The HFS proved strategies need to align with the patients’ needs to provide adequate

continuity of care. The HFS follows the patients admitted with a primary diagnosis of HF from

admission to discharge and for the following 30-days. The HFS has incorporated multiple

interventions to assist in reducing 30-day HF readmissions. The interventions include: 1)

inpatient HF education from the HFS NP, 2) review of medications by the Pharm D, 3) solving

the barriers to care for discharge by the Social Worker, 4) a 24-hour follow-up phone call by the

PACT, 5) a 48-72 hour follow-up phone call by the HFS NP, 6) a one-week follow-up

appointment by the HFS NP, 7) after first-week follow-up either weekly phone calls or weekly

clinic visits to the HFS for 30-days. Strategies need to align with the patients’ needs and

continuity of care was the catalyst that has been missing.

The goal of this scholarly project was for the HFSs quality improvement path to lead to

statistical significance in 30-day HF readmissions. The goal was met and did show a significant

difference p = .001. This clinical significance of reducing 30-day heart failure readmissions is

valuable if it was just by 1%, but is was by 24%. According to McIlvennan, Eapen, & Allen

(2015), Medicare saves 1 billion dollars with a 10% reduction in 30-day readmissions. The

results of this study are the first steps in making the HFS the new standard of care. This

evidence-based research could now lead to a policy formation and provide a consistent and

sustainable solution to reducing 30-day heart failure readmissions. The HFS template could also

be used to reduce other chronic diseases with high 30-day readmission rates as in COPD.

Strengths


The precision and estimated effects generated strength. A post hoc analysis indicated the

results from the sample could be generalized to the population from which the sample size was

drawn. The G*Power app determined a sample size of 126 was needed to have a power of.80 or

higher (Crosstabs & Chi-Square, 2018). The input by the Maryville University

doctoral project chair, and Investigation Research Board (IRB) added

strengthen to the data collection tool design. The researcher used a Maryville

Universities Statistician. The statistician placed the collected data into SPSS and

performed the needed statistics. By utilizing the statistician, it mitigated any

research bias, ensured accurate statistical testing was completed and

minimized the chance of human error (Polit & Beck, 2004).

Limitations

Two limitations were noted. Neither of the barriers was related to the research questions.

The limitations of this study were the male to female ratio of 98% males to 2% females. Also,

the single center facility used for the research was a government-run hospital. This study could

have a broader outreach to a larger population of gender, ethnicities, and socioeconomic and

intellectual backgrounds in a larger privately run facility. The credibility of the evidence was not

affected by the limitations. This retrospective study compared the same patient population

demographics with different follow-up approaches. The researcher considered key threats to the

studies validity and possible biases. The researcher worked in the heart failure service and was

aware of the important exclusion criteria to include. But, any investigator would have learned of

these essential exclusions when reviewing the literature.

Application to Education


The study results add credible material to share and educate personnel of the Steering

Committees, and the Risk Management and Quality Improvement Departments and primary care

clinics. It is vital for patients with heart failure to be educated at time of their heart failure

diagnosis. The study revealed a 28% decrease in overall heart failure admissions. The HFS

visited the primary care clinic soon after opening and expressed to the staff; we need to focus on

prevention of heart failure and slowing the progression of those with heart failure.

Application to Research

The researcher is scheduled to meet with the head of Pulmonology to discuss the

scholarly project, its results, and ease of replication. The goal of the researcher is to have the

addition of a new Nurse Practitioner run Chronic Obstructive Pulmonary Disease (COPD) clinic

approved. The COPD clinic would follow the patients admitted with a primary diagnosis of

COPD from admission to discharge and for the following 30-days. The COPD NPs multi-

interventional approach will align with the patients’ needs to provide adequate continuity of care.

Application to Practice

The effectiveness of these quality improvement results is of little value unless they are

put into practice. The DNP can lead the promotion to an improved perspective towards these two

goals, that is to start with prevention of HF, and slow the progression of those patients diagnosed

with heart failure. By meeting with the department heads and sharing the evidence-based

research further promotion of controlling all chronic disease can be possible.

Application to DNP

The Knowledge Transfer Theory (KTT) is relevant to this project because it relates the

two populations, researchers and policymakers, and how the two organizing frameworks can


translate evidence into policy (White et al., 2016). The DNP-prepared nurse is equipped to lead

this endeavor of closing the research to practice gap. The practitioner-researcher can lay the

groundwork for research-based evidence for policy formation to take place (Vincent, Johnson,

Velasquez, & Rigney, 2010). The DNP students’ goal is to work alongside the policymakers at

the VAMC to place this evidence-based research into policy.

The researcher closed this research to practice gap by taking found knowledge from a

previous study and furthering the research on the same topic leading to a successful quality

improvement path. Research evolves by leading to further questioning. The scholarly project

allowed the DNP prepared nursing student to apply other research findings into a clinical setting

successfully and bring about new knowledge. By translating knowledge into practice, policies

can be set in place to prevent variations in practice for a more sustainable continuity of care.

Conclusion

The HFS multi-interventional approach provided a sustained continuity of care

and significantly reduced 30-day HF readmissions. The HFSs results are the first step in

establishing a foundation of best practices so consistent and sustainable continuity of care can

ensue. These research results will lead to further studies for patients with

chronic disease. This scholarly project highlighted how gaps between

research and application for practice can come together within a clinical

setting and provide improved patient outcomes. This collaboration of research to

practice promotes positive change and highlights contributions made by the doctoral nurse

practitioner. This research to practice pattern by DNPs could play a vital role in improving our

nation’s healthcare system.


References

American Heart Association (2017, February 1). Classes of heart failure. Retrieved March 24,

2017, from:

http://www.heart.org/HEARTORG/Conditions/HeartFailure/AboutHeartFailure/Classes-

of-Heart-Failure_UCM_306328_Article.jsp#.WVhS7ojys2w

American Heart Association (2017, February 1). Understand your risk for heart failure.

Retrieved March 24, 2017, from:

http://www.heart.org/HEARTORG/Conditions/HeartFailure/CausesAndRisksForHeartFa

ilure/Understand-Your-Risk-for-Heart-Failure_UCM_477645_Article.jsp#.WOWjrtIrI2w

Arundel, C., Lam, P., Khosla, R., Blackman, M., Fonarow, G., Morgan, C., Zeng, Q., Fletcher,

R., Butler, J., Wu, W., Deedwania, P., Love, T., White, M., Aronow, W., Anker, S.,

Allman, R., & Ahmed, A. (2016). Association of 30-day all-cause readmissions with

long-term outcomes in hospitalized older Medicare beneficiaries with heart failure. The

American Journal of Medicine, 129 (11), 1178-1184.

Ballard, D., Ogola, G., Fleming, N., Stauffer, B., Leonard, B., Khetan, R., Yancy, C. (2010).

http://www.heart.org/HEARTORG/Conditions/HeartFailure/AboutHeartFailure/Classes-


Impact of a standardized heart failure order set on mortality, readmission, and quality and

costs of care. International Journal for Quality Health Care, 22(6), 437–444.

Balogun, J., Idowu, P., Sarumi, A. (2016). Development of a web-based cardiovascular disease

risk monitoring system. Biomed Central Cardiovascular Disorders. Retrieved from:

file:///C:/Users/Scott/Downloads/Development%20of%20a%20Web-Based

%20Cardiovascular%20Disease%20Risk%20Monitoring%20System%20(1).pdf

Bowers, M. (2013). Managing patients with heart failure. The Journal for Nurse Practitioners,

9 (10), 634-642.

Caplan, N., (1979). The Two-Community Theory and knowledge utilization. Retrieved from;

https://deepblue.lib.umich.edu/bitstream/handle/

2027.42/66698/10.1177_000276427902200308.pdf?sequence=2

Chaudhry S., Mattera J., Curtis J., Spertus, J., Herrin, J., Lin, Z., Phillips, C., Hodshon, B.,

Cooper, L., Krumholz, H. (2010). Telemonitoring in patients with heart failure.

New England Journal of Medicine, 363(24), 2301–2309.

Cowie M., Anker S., Cleland J., Felker G., Filippatos G., Jaarsma T., Jourdain, P., Knight

E., Massie B., Ponikowski P., & López-Sendón J. (2014) Improving care for patients with

acute heart failure: before, during and after hospitalization. Heart Failure European

Society of Cardiology 1, 110–145, doi: 10.1002/ehf2.12021.

Cykert, S. (2012). Improving care transitions means more than reducing hospital readmissions.

North Carolina Institute of Medicine and the Duke Endowment, 73 (1)31-33.

Dharmarajan, K., Hsieh, A., Lin, Z., Bueno, H., Ross, J., Horwitz, l., Barreto-Filho, J., Kim,

N., Bernheim, S., Suter, L., Drye, E., & Krumholz, H. (2013). Diagnoses and timing of

30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or

https://deepblue.lib.umich.edu/bitstream/handle/2027.42/66698/10.1177_000276427902200308.pdf?sequence=2

https://deepblue.lib.umich.edu/bitstream/handle/2027.42/66698/10.1177_000276427902200308.pdf?sequence=2


pneumonia. The Journal of the American Medical Association, 309(4):355-363.

doi:10.1001/jama.2012.216476

http://jamanetwork.com/journals/jama/fullarticle/1558276

Domingues, F., Clausell, N., Aliti, G., Dominguez, D., & Rabelo, E. (2011). Education and

telephone monitoring by nurses of patients with heart failure: randomized clinical

trial. Arq. Bras. Cardiology 96 (3) http://dx.doi.org/10.1590/S0066-

782X2011005000014

Ducharme A, Doyon O, White M, Rouleau, J., & Brophy, J. (2005). Impact of care at a

multidisciplinary congestive heart failure clinic: a randomized trial. Canadian Medical

Association Journal 173(1) 40–45.

Ellen, M., (2012). Knowledge translation framework for ageing and health. Department of

Aging and Life-Course. World Health Organization. Retrieved by;

http://www.who.int/ageing/publications/knowledge_translation.pdf

Fleming, T. (2014). 30-day readmission rates for congestive heart failure.

Frankenstein, L., Fröhlich, H., & Cleland, J. (2015). Multidisciplinary approach for patients

hospitalized with heart failure. Revista Espanola De Cardiologia 68 (10) 885-891. DOI:

10.1016/j.rec.2015.05.008. Retrieved from;

http://www.revespcardiol.org/en/multidisciplinary-approach-for-patients-

Giuliano, K. K., Danesh, V., & Funk, M. (2016). The relationship between nurse staffing and

30-day readmission for adults with heart failure. The Journal of Nursing

Administration, 46 (1), 25–29. http://doi.org/10.1097/NNA.0000000000000289

Heidenreich, P., Albert, N., Allen, L., Bluemke, D., Butler, J., Fonarow, G., Ikonomidis, J.,


Khavjou, O., Konstam, M., Maddox, T., Nichol, G., Pham, I., & Trogdon, J. (2013).

Forecasting the impact of heart failure in the United States. Circulation: Heart Failure (6),

606-619. Retrieved from; https://doi.org/10.1161/HHF.0b013e318291329a

Hernandez, A. (2013). Preventing heart failure. The Journal of American Medical Association,

310 (1), 44-46.

Hernandez, A., Greiner, M., Fonarrow, G., Hammill, B., Heidenreich, P., Yaney, C., Peterson,

E., Curtis, L. (2010). Relationship between early physician follow-up and 30-day

readmission among Medicare beneficiaries hospitalized for heart failure. Journal of

American Medical Association, 303 (17), 1716-1711.

Hines, P., Yu, K., Randall, M. (2010). Preventing heart failure readmissions: Is your

organization prepared? Nursing Economics: The Journal for Health Care Leaders, 28

(2), 75-85.

Hitch, B., Parlier, A., Reed, L., Galvin, S., Fagan, B., & Wilson, C., (2016). Evaluation of a

team-based, transition-of-care management service on 30-day readmission rates. North

Carolina Medical Journal, 77 (2), 87-92.

Holzner, B. & Marx, J. (1979). The knowledge system in society. Boston: Allyn and Bacon.

Ibrahim, N., & Januzzi, J. (2016). The role of biomarkers in the diagnosis, risk

stratification, and disease management of heart failure. Cardiovascular Consults, 1(1), 9-

13.

Ibrahim, N., & Januzzi, J. (2016). The role of biomarkers in the diagnosis, risk stratification, and

disease management of heart failure. Cardiovascular Consults, 1(1), 9-13.

Inglis, S., Clark, R., McAlister, F., Ball, J., Lewinter, C., Cullington, D., Stewart, S., & Cleland,

J. (2010). Structured telephone support or telemonitoring programs for patients with


chronic heart failure. Cochrane Database of Systematic Reviews, 8, 1-144.

Irving, A. (2014, October, 13). Policies and Procedures for Healthcare Organizations: A Risk

Management Perspective. Patient safety and quality healthcare. Retrieved from;

https://www.psqh.com/analysis/policies-and-procedures-for-healthcare-organizations-a-

risk-management-perspective/

Jackson, C., Shahsahebi, M., Wedlake, T., & DuBard, C. A. (2015). Timeliness of Outpatient

Follow-up: An Evidence-Based Approach for Planning After Hospital Discharge. Annals

of Family Medicine, 13(2), 115–122. http://doi.org/10.1370/afm.1753

Kim, M., & Mallory, C. (2014). Statistics for evidence-based practice in nursing. Burlington,

MA: Jones & Bartlett Learning.

Kim, S., & Han, H. (2013). Evidence-based strategies to reduce readmission in patients with

heart failure. Journal for Nurse Practitioner, 9 (4), 224-232.

http://www.medscape.com/viewarticle/782534_2

Klein, S., Hostetter, M., McCarthy, D. (2017). An overview of home-based primary care;

learning from the field. The Commonwealth Fund.

Kripalani, S., Theobald, C. N., Anctil, B., & Vasilevskis, E. (2014). Reducing hospital

readmission: Current strategies and future directions. Annual Review of Medicine 65,

471–485. http://doi.org/10.1146/annurev-med-022613-090415

Lee, K., Jingrong, Y., Hernandez, A., Steimle, A., Go, A., & Yang, J (2016). Post-discharge

follow- up characteristics associated with 30-day readmissions after heart failure

hospitalization. Medical Care, 54(4), 365-372. doi:10.1097/MLR.0000000000000492

Lefcourt, H. M. (Ed.). (2014). Locus of control: Current trends in theory & research.

Psychology Press.

Linden, A., & Butterworth, S. (2014). A comprehensive hospital-based intervention to reduce


readmissions for chronically ill patients: A randomized controlled trial. The American

Journal of Managed Care, 20 (10), 783-792.

Matt, V., & Matthew, H. (2013). The retrospective chart review: Important methodological

considerations. Journal of Educational Evaluation for Health Professions. 10, 12.

http://doi.org/10.3352/jeehp.2013.10.12

McIlvennan, C., Eapen, Z., & Allen, L. (2015). Hospital readmissions reduction

program. Circulation, 131(20), 1796–1803. Retrieved from:

http://doi.org/10.1161/CIRCULATIONAHA.114.010270

Medicare.gov Readmissions and deaths-national. 2016. [Accessed May 16, 2016]. Available

from: https://data.medicare.gov/Hospital-Compare/Readmissions-and-Deaths-

National/qqw3-t4ie#.

Melton, L., Foreman, C., Scott, E., McGinnis, M., & Cousins, M. (2012). Prioritized post-

discharge telephonic outreach reduces hospital readmissions for select high-risk patient.

The American Journal of Managed Care (12), 838-44.

Mistiaen, P., & Poot, E. (2006). Telephone follow-up, initiated by a hospital-based health

professional, for post-discharge problems in patients discharged from hospital to

home. Cochrane Database Systematic Review. (4): CD004510.

O’Connor, M., Murtaugh, C. M., Shah, S., Barrón-Vaya, Y., Bowles, K., Peng, R., & Feldman,

H. (2016). Patient characteristics predicting readmission among individuals hospitalized

for heart failure. Medical Care Research and Review, 73 (1), 3–40. Retrieved from:

http://doi.org/10.1177/1077558715595156

Pazos-López, P., Peteiro-Vázquez, J., Carcía-Campos, A., García-Bueno, L., de Torres, J., &

https://data.medicare.gov/Hospital-Compare/Readmissions-and-Deaths-%09National/qqw3-t4ie

https://data.medicare.gov/Hospital-Compare/Readmissions-and-Deaths-%09National/qqw3-t4ie


Castro-Beiras, A. (2011). The causes, consequences, and treatment of left or right heart

failure. Vascular Health and Risk Management 7, 237-254. Retrieved from:

http://doi.org/10.2147/VHRM.S10669

Peikes, D., Chen, A., Schore, J., & Brown, R. (2009). Effects of care coordination on

hospitalization, quality of care, and health care expenditures among Medicare

beneficiaries 15 randomized trials. Journal of American Medical Association

301(6) 603-618. doi:10.1001/jama.2009.126

Quality Enhancement Research Initiative (QUERI), (2017). US Department of Veterans Affairs.

Retrieved from; http://www.queri.research.va.gov/about/default.cfm

Rabbat, J., Bashari, D. R., Khillan, R., Rai, M., Villamil, J., Pearson, J. M., & Saxena, A. (2012).

Implementation of a heart failure readmission reduction program: a role for medical

residents. Journal of Community Hospital Internal Medicine Perspectives, 2 (1),

10.3402/jchimp.v2i1.10674. http://doi.org/10.3402/jchimp.v2i1.10674

Research Involving Human Subjects. (2016, March 11). The National Institute of Health.

Retrieved from: https://phrp.nihtraining.com/users/overview.php

Segall, L., Nistor, I., and Covic, A., (May 15, 2014). Heart failure in patients with

chronic kidney disease: A Systematic Integrative Review. Bio Med Research

International. Retrieved from:

https://www.hindawi.com/journals/bmri/2014/937398/citations/

Sharma, G., Fletcher, K., Zhang, D., Kuo, Y., Freeman, J., & Goodwin, J. (2009). Continuity of

outpatient and inpatient care by primary care physicians for hospitalized older adults.

Journal of American Medical Association, 301 (16), 1671-1680.

Simpson, M. (2014). A quality improvement plan to reduce 30-day readmissions of heart

failure patients. Journal of Nursing Care Quality, 29 (3), 280–286.

https://www.hindawi.com/journals/bmri/2014/937398/citations/

http://doi.org/10.2147/VHRM.S10669


DOI: 10.1097/NCQ.0000000000000038

Smith, A. (2013). Effect of telemonitoring on re-admission in patients with congestion heart

failure. Medsurg Nursing, 22 (1), 39-42.

Stauffer, B., Fullerton, C., Fleming, N., Ogola, G., Herrin, Stafford, P., & Ballard, D. (2011).

Effectiveness and cost of a transitional care program for heart failure. Arch Internal

Medicine 171 (14), 1238-1242.

Takeda, A., Taylor, S., Taylor, R. Khan, F., Krum. H., & Underwood, M. (2012). Clinical

service organization for heart failure. Cochrane Database Systematic Review (9):

CD002752

Terry, A. (2014). Clinical research for the doctor of nursing practice. (2nd ed.). Sudbury, MA:

Jones & Bartlett Learning.

Titler, M., Jensen, G., Dochterman, J., Xie, X., Kanak, M., Reed, D., & Shever, L. (2008). Cost

of hospital care for older adults with heart failure: medical, pharmaceutical,

and nursing costs. Health Services Research, 43 (2), 635-655. Retrieved from:

http://doi.org/10.1111/j.1475-6773.2007.00789.x

U.S. Department of Health and Human Services, (2015). Heart failure (HF): hospital 30-day,

all-cause, unplanned risk-standardized readmission rate (RSRR) following HF

hospitalization (2015). Retrieved from;

https://www.qualitymeasures.ahrq.gov/summaries/summary/49196/heart-failure-hf-

hospital-30day-allcause-unplanned-riskstandardized-readmission-rate-rsrr-following-hf-

hospitalization

Vincent, D., Johnson, C., Velasquez, D., & Rigney, T. (2010). DNP-prepared nurses

practitioner-researchers; Closing the gap between research and practice.

Journal of the American of Nurse Practitioners, 14 (11/12), 28-34.

http://doi.org/10.1111/j.1475-6773.2007.00789.x


White, K., Dudley-Brown, S., & Terhaar, M. (2016). Translation of evidence into nursing

and health care (2nd Ed.). New York: Springer Publishing Company.

ISBN: 978-0826117847.

Whitman, E. (August 3, 2016). Hospitals face record penalties as CMS expands criteria for

readmissions fines. Modern Healthcare. Retrieved from;

http://www.modernhealthcare.com/article/20160803/NEWS/160809964

Will, J., Valderrama, A., & Yoon, P. (2012). Preventable hospitalizations for congestive heart

failure: establishing a baseline to monitor trends and disparities. Preventing Chronic

Disease 9:110260. DOI: http://dx.doi.org/10.5888/pcd9.110260

William, M. (2016). Decreasing congestive heart failure readmission rates within 30 days at the

Tampa VA. Nursing Administration Quarterly, 40 (2), 146-152


Appendix A


Appendix B


Date: December 13, 2017

To: Ms. Patricia Chafin – Doctoral Candidate, Nursing Practice

From: Dr. Robert Bertolino, Chair, Institutional Review BoardDr. Tammy M. Gocial, Integrity Officer for Institutional Review Board

RE: IRB Review of Protocol #17-45Title: "Impact of a Heart Failure Service: A Solution to Reducing 30-Day Failure

Readmissions"

CC: Dr. Jacqueline Saleeby – Associate Professor of Nursing

This is to inform you that your application to conduct research has been reviewed and accepted by the Maryville University Institutional Review Board. You are now authorized to begin the research as outlined in your proposal.

It is understood that this project will be conducted in full accordance with all applicable sections of the IRB guidelines as published by Maryville University. It is also understood that the IRB will be notified immediately of any proposed changes that may affect the status of your research proposal. As the principal investigator(s), you are required to notify the Maryville University IRB of any adverse reactions that may develop as a result of this study. Finally, when your research has concluded (or if you conclude the study sooner than anticipated), please complete the Protocol Closure Form. If informed consent processes were a part of your proposal, an approved, stamped version is attached to this document.

Good luck on your research.

Appendix C


DEPARTMENT OF VETERANS AFFAIRSINSTITUTIONAL REVIEW BOARD

Memphis Veterans Affairs Medical Center1030 Jefferson AvenueMemphis, TN 38104

DATE: October 6, 2017

TO: Patricia Chafin, MSN Principal Investigator

FROM: Timmye Edwards, Pharm.D. Memphis VAMC Institutional Review Board Chair

PROTOCOL TITLE: [1100240-1] Impact of a Heart Failure Service: A Solution to Reducing 30-dayHeart Failure Readmissions

SUBMISSION TYPE: New ProjectREVIEW TYPE: Expedited Review RISK DETERMINATION: Minimal Risk

ACTION: APPROVEDAPPROVAL DATE: October 3, 2017

Your response to contingencies for approval of the above named project were reviewed and approved bythe Memphis VAMC Institutional Review Board's designated reviewer on October 3, 2017 via expeditedreview procedures as authorized by 38 CFR 16.110(b) and 45 CFR 46.11(b) under category #5. Thisapproval will be reported to the committee during the next convened IRB meeting. Neither you nor any ofthe identified co-investigators participated in the review and decision-making.

The following documents were submitted for this contingency review:

• Application Form - IRBNetDocument (3).pdf (UPDATED: 09/27/2017)

• Conflict of Interest - Other - PI- Chafin FCOI (UPDATED: 07/20/2017)

• Conflict of Interest - Other - Fleming FCOI (UPDATED: 07/18/2017)

• Consent Waiver - IRBpatty2016 Request for Waiver with Regards to Informed Consent.docx (UPDATED: 07/17/2017)

• HIPAA Waiver - Request for HIPAA Waiver v 2.4 Feb 3-2017 (1).docx (UPDATED: 09/27/2017)

• Letter - approvalletter.docx (UPDATED: 07/17/2017)

• Memphis VA - IRB Application - Memphis VA - IRB Application (UPDATED: 09/27/2017)

• Memphis VA - IRB Application - Memphis VA - IRB Application (UPDATED: 07/18/2017)• Memphis VA - IRB Application - Memphis VA - IRB Application (UPDATED: 07/18/2017)

• Other - Checklist for Reviewing Privacy, Confidentiality and Information Security in Research - 2017.docx (UPDATED: 08/29/2017)


• Other - Research Data Inventory Tool (1).docx (UPDATED: 07/20/2017)

• Other - Basis for Expedited Review.docx (UPDATED: 07/20/2017)

• Protocol - Protocol Template Revised 3-30-2017.doc (UPDATED: 08/29/2017)

• VA - R&D Request to Review Research Proposal - VA - R&D Request to Review Research Proposal (UPDATED: 07/18/2017)

The following documents, available to support this contingency review through IRBNet, were reviewedon September 27, 2017.

• Application Form - IRBNetDocument (3).pdf (UPDATED: 09/27/2017)

• Conflict of Interest - Other - PI- Chafin FCOI (UPDATED: 07/20/2017)

• Conflict of Interest - Other - Fleming FCOI (UPDATED: 07/18/2017)

• Consent Waiver - IRBpatty2016 Request for Waiver with Regards to Informed Consent.docx (UPDATED: 07/17/2017)

• HIPAA Waiver - Request for HIPAA Waiver v 2.4 Feb 3-2017 (1).docx (UPDATED: 09/27/2017)

• Letter - approvalletter.docx (UPDATED: 07/17/2017)




• Other - Checklist for Reviewing Privacy, Confidentiality and Information Security in Research - 2017.docx (UPDATED: 08/29/2017)

• Other - Research Data Inventory Tool (1).docx (UPDATED: 07/20/2017)

• Other - Basis for Expedited Review.docx (UPDATED: 07/20/2017)

• Protocol - Protocol Template Revised 3-30-2017.doc (UPDATED: 08/29/2017)

• VA - R&D Request to Review Research Proposal - VA - R&D Request to Review Research Proposal (UPDATED: 07/18/2017)

Your requested Waiver of HIPAA Authorization has been granted in accordance with therequirements set forth in 45 CFR 164.512.

Your requested Waiver of Informed Consent/Alteration of the Informed Consent Process has beengranted in accordance with the requirements set forth in 38 CFR 16.116(d) and 45 CFR 46.116(d).

This IRB has determined that this study presents Minimal Risk to subjects.

This study will be subject to continuing review by the IRB. Approval for this study will expire on October2, 2018. You are required to submit a progress report to the IRB prior to the end of the current approvalperiod and with sufficient time to permit continuing review to take place before lapse of approval.

The Memphis VAMC Institutional Review Board reminds you of several important requirements:

1. The procedures and interventions must be those described in the approved protocol.

2. Any changes to, or deviations from, the protocol must be proposed to the IRB in writing as amodification to the approved project via IRBNet and must be approved before changes areimplemented.

3. You are required to maintain a current personnel log of all staff that interact with subjects or haveaccess to subject private, identifiable information. All study personnel must be credentialed,privileged, and current on required education


Please be reminded that you are not allowed to begin any research until the Memphis VAMCResearch and Development (R&D) Committee has approved your project.

If you have any questions, please contact the IRB Office at (901) 577-7267.

Timmye Edwards, Pharm.D.

This electronically generated document serves as official notice to sponsors and others of approval, disapproval or other IRB decisions. Only those individuals who have been granted authority by the institution to create letters on behalf of the IRB are able to do so. A copy of this document has been retained within Memphis VAMC IRBNet records. The IRBNet System is fully compliant with the technology requirements for Electronic Records per CFR 21, Part 11, Section 11.10 - Controls for Closed Systems, and the technology requirements for Electronic Signatures per CFR 21, Part 11 Subpart C - Electronic Signatures.

Appendix D


Pt AGE M/F RC PR DX HF/NYHA A HF/NYHA Ch HF/NYHA iv nRA 1 iv RA 2 std fu 1 HFS FU 2 dv nRA 0 dv RA 1

Patient- Pt AgeRace- RCMale/Female- M/F Primary diagnosis HF/NYHA classAcute heart failure/NYHA class Chronic heart failure/NYHA class independent variable not readmitted within 30-days- 1 independent variable readmitted within 30-days-2 Standard follow-up-1 Heart Failure Service follow-up-2 dependent variable not readmitted-0 dependent variable readmitted- 1

Appendix E

MARYVILLE UNIVERSITY INSTITUTIONAL REVIEW BOARD


Request to be EXEMPT from Full IRB ReviewPrincipal Investigator: Patricia Chafin

Project Title: Impact of a Heart Failure Service: A solution to 30-day heart failure readmissions_______________________________________________________________

Please review and identify all categories that apply to your research. Pay close attention to the special notations provided. Check each category that applies. NOTE: If your research does not fit into at least one of the categories listed below, it is NOT EXEMPT from a full IRB review.I. Exempt Category Designations

____ 1. Research conducted in established or commonly accepted educational settings, involving normal education practices, such as (i) research on regular and special education instructional strategies, or (ii) research on the effectiveness of, or the comparison among, instructional techniques, curricula, or classroom management methods.

NOTES: Research in this category may include minors. If the research introduces strategies thatare not commonly used or well accepted or adds assessment procedures that are not routinely used, it does not fit the category. Also, no written consent forms are necessary under this exemption category, although a letter informing participants of the purpose of the research is appropriate and should be attached to your proposal._____ 2. Research involving the use of educational tests (cognitive, diagnostic, aptitude, achievement), survey procedures, interview procedures, or observation of public behavior unless: (i) information obtained is recorded in such a manner that human subjects can be identified, directly or through identifiers linked to the subjects; and (ii) any disclosure of the human subjects’ response outside the research could reasonably place the subject at risk of criminal or civil liability or be damaging to the subjects’ financial standing, employability or reputation.NOTES: Surveys or interviews of children are never exempt. In addition, observations of the

public behavior of children are not exempt if the observer participates in the activities being observed. Furthermore, any procedures which involve video recording participants are not exempt. Audio recordings MAY be exempt if the recordings will be transcribed, the recordings serve only to document the accuracy of the conversation / data collected, and recordings will be deleted immediately following verification of transcripts. Consent forms are necessary under this exempt category.______3. Research involving the use of educational tests (cognitive, diagnostic, aptitude, achievement), survey procedures, interview procedures, or observation of public behavior that is not exempt under paragraph #2 of this section, is exempt if (i) the human subjects are elected or appointed public officials or candidates for public office; or (ii) Federal statute(s) require(s) without exception that the confidentiality of the personally identifiable information be maintained throughout the research and after. Consent forms are necessary under this exempt category.

___x__4. Research involving the collection or study of existing data, documents, records, or pathological specimens, or diagnostic specimens, if these sources are PUBLICLY available or if the information is recorded by the investigators in such a manner that subjects cannot be identified, either directly or through identifiers linked to the subjects.

NOTES: Please note that to qualify for this category all data, documents, records or specimens to be used in the research must be in existence at the time of IRB review and must have been collected for purposes other than the proposed research. Consent forms not required under this category, but please provide exact data on the source of existing data or records. HIPAA regulations require that ALL identifiers be removed prior to data being recorded for research purposes; otherwise a request for Waiver of Authorization is required.

II. Exemption from Review Checklist


Does your research include any procedures or activities that are not

included in the categories listed in Part I above? ____ yes ___x_ no

Does your research involve:1. Prisoners, pregnant women or vulnerable subjects? ____ yes __x__ no

2. Surveys or interview procedures with children? ____ yes __x__ no

3. Observations of children where the observer will

participate in the activities being observed? ____ yes __x__ no

4. Video recording of participants? ____ yes __x__ no

5. Audio recording of participants for reasons other than transcript accuracy? ____ yes __x__ no

6. Deception of participants? ____ yes __x__ no

7. Use of any materials that might be deemed offensive or threatening? ____ yes __x__ no

8. Any procedures that would expose participants to

stress or risks beyond what they encounter in everyday life? ____ yes __x__ no

9. Collection of personal, sensitive information through tests or surveys? ____ yes __x__ no

10. Use of archival data that includes identifying information or

codes that link an individual to the data? ____ yes __x__ no

11. Request for a Waiver of Authorization to release Protected Health

Information (PHI) as part of a medical records review? ____ yes __x__ no

If you answered YES to any of the questions in part II, your project is NOT EXEMPT from Full Board Review, although it could be eligible for Expedited Review. Stop and review the criteria for Expedited Review or submit your proposal for IRB Full Board Review.

One (1) copy of all materials [application cover sheet, request for exemption from full review checklist, IRB proposal, consent/assent forms, subject recruitment document(s), research instruments, etc.] must be submitted ELECTRONICALLY to the Administrator of the Institutional Review Board. No application will be reviewed unless a complete and signed proposal packet is submitted. In most cases, (summer being an exception), the review will occur in 1-2 weeks.

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