Congestive heart failure (CHF) is the leading cause of hospitalization among patients older than 65 year of age. Annually, greater than 1 million patients are hospitalized with a primary diagnosis of heart failure, accounting for a total Medicare expenditure exceeding $17 billion (Desai & Stevenson, 2012). Heart failure (HF) occurs when cardiac output is insufficient to provide adequate blood flow to meet metabolic and circulatory demands (Houston, Kalathiya, Kim, & Zakaria, 2015). Despite dramatic improvement in outcomes with medical therapy, admission rates following heart failure hospitalization remain high, with greater than or equal 50% patients readmitted to hospital within 6 months of discharge (Desai & Stevenson, 2012). Mortality in Heart Failure is high, approaching 20% at 1 year and 50% at 4 years (Rickenbacher et al., 2012). The purpose of this paper is to evaluate how the application of Roy’s theory of adaptation model can decrease hospital readmissions and mortality in patients with heart failure. The Roy adaptation model (RAM) is an appropriate guide when providing nursing practice care for patients with chronic diseases such as heart failure (Bakan & Akyol, 2007). The use of Roy’s theory can show interventions of how patients can adapt to their condition and how it can decrease hospital readmission and mortality in patients with heart failure. Therefore, the content of this paper will examine the application of RAM applied to heart failure patients.
State
In the UK, reports show that heart failure has been affecting up to 2% of the population, over 900,000 people are living with heart failure, with 63,000 new cases being diagnosed each year (BHF, 2015). It costs the NHS £625 million per year, as a result of the high portion of emergency admissions, readmission and long length of inpatient stay (NHS Improvement, 2010). DH (2000) confirmed that Heart failure accounts for all cardiac admissions and the readmission rate can be as high as 50% within 3 months; also, it further estimated 50% readmission might be preventable. Unfortunately, Heart Failure can’t be cured, but early
Individuals who have encountered an event of a heart attack, angina, heart failure, stroke, coronary artery bypass graft, or heart valve surgery experience multiple unfavourable healthcare outcomes. Cardiac health conditions are an enduring healthcare concern with alarming associated complications and risks. These lifelong chronic conditions affect both patient and family’s quality of life, ultimately, requiring ongoing management for cardiac patients to live longer and healthier lives. Cardiac rehabilitation programs reduce mortality and morbidity rates (Dalal, Doherty & Taylor, 2015). These programs are medically controlled cardiac programs which will modify a patient’s wellbeing and lifestyle, by implementing new lifestyle skills to
Heart Failure affects nearly 5.8 million people in the United States. The American Heart Association reports that the total economic cost of heart disease and stroke in 2011 was $320.1 billion. ("Efforts to Prevent Heart," 2015). More Medicare dollars are spent for the diagnosis and treatment of heart failure than for any other diagnosis (Schneider, O'Donnell, & Dean, 2011). Hospital admissions for heart failure are very common, especially among Medicare aged patients, and heart failure hospital readmissions are a major contributor to rising healthcare costs. Evidence suggests that factors influencing readmission rates for heart failure patients include knowledge deficits in nursing education, standardized patient education, and transitional
This study used a descriptive, correlational, comparative and quantitative design to determine the probable causes of heart failure readmissions (Anderson, 2014). Independent t tests were used to the characteristics between those individuals that were readmitted and those that were not. Correlation coefficients were examined using the Pearson product-moment and the Spearman ρ test to determine the indications for readmission. (Anderson, 2014). Once these were established the Hosmer and Lemeshow tests were used in binary logistical regression analysis to determine how well each predictor variable determined the probability of readmission. Using these tests, the results showed that P=0.599, indicating that the model adequately fits the data (Anderson, 2014). To add to this, further proving the study’s validity, a hierarchical approach was preferred because “entry of variables is based upon an evaluation of theoretic, clinical, and statistical considerations” (Anderson, 2014, p. 234). This allowed for the assessment of predictive ability. This study through multiple statistical tests proved strong validity in its data collection, research design, and measurement
When nursing any patient with heart failure it is important to have an understanding of how the heart should work to understand how it stops working correctly. This knowledge is important as writtler (2006) (cited in Jones) feels that district nurses have little knowledge when it comes to heart failure. Patient, Writler (2006) feels that by understanding how the heart works and how it is damaged we, as district nurses will be able to recognise the signs of heart failure earlier7a?.
Providing patients diagnosed with Congestive Heart Failure effective teaching can eliminate reoccurring hospitalizations. Patients are discharged with CHF and readmitted within 30 days. The information provided will examine the process of enhancing patient knowledge and provide additional resources essential for effective health care management. Research evidence provides data that proves patients who are diagnosed with CHF needs a variety of health care needs during admission and after discharge. The proposal will display an evaluation plan, implementation plan and a dissemination of the
This article sought to find an appropriate model to predict the risk of unplanned heart failure readmissions. The primary outcome from chart reviews also included death of heart failure patients within 30 days of discharge. The study looked at Centers for Medicaid and Medicare Services (CMS) models and the LACE+ index, to mention two of many
Each year the number of readmissions of the heart failure patient within 30 days of discharge has grown. The Medicare division in relation with the Affordable Care Act is reducing the amount of money they are willing to pay for readmissions to the hospital. Hospitals are now more than ever looking for ways to reduce the number of readmissions to the hospital for the heart failure patient. The purpose of this paper is take a look at a program designed with to reduce the readmission rates of one hospital to reduce the number of readmission through improved education and follow up of the heart failure patient.
Evaluation is the final and often the most critical step in evidence based research and practice. Evaluation of evidence based practice follows a pathway beginning with the selection of the area for improvement, synthesizing the research into a process improvement activity and evaluating both the implementation of the process improvement as well and the outcomes of the intervention (Titler, 2008). To measure the results of process change in the management of heart failure patients a retrospective analysis will be conducted comparing the readmission rates of a pilot and control population over a 6-month period. The pilot population will be evaluated with the LACE index readmission risk assessment upon admission and subsequently receive the recommended interventions based on the risk stratification. In comparison, the control group will receive the current process of telephonic contact only. The pilot group will include patients over the age of 18 residing in zip-codes 45402 and 45403,
According to the Centers for Disease Control and Prevention (CDC) there are an estimated 5.1 million adults suffering from heart failure (2013). As the prevalence of heart failure continues to rise, one out of every nine deaths occur as a result of this chronic condition. Studies conducted at Yale found in Medicare age patients with heart failure, there is a median 30-day mortality rate of 11.1% and 5-year rate of approximately 50% (Alspach, 2014). According to Desai & Stevenson (2012), rising costs of care are in direct correlation to the number of hospital admissions related to a primary diagnosis of heart failure especially among adults age 65 years or older. The national rate for readmissions within 30 days is approximately 24.7%, consequently having
In my current position, the Hospital Readmission Reduction program plays a pivotal role in my job. I am a part of a new initiative in conjunction with NexusMontgomery. “This program aims to provide care management intervention that will reduce overall hospital costs and reduce hospital admissions and readmissions in Montgomery county Maryland” (Regional Trans, 2015, p. 1). Funding is provided from The Center for Medicare and Medicaid Services. The program aims to significantly reduce the number of residents in Montgomery County with hospital admissions and readmissions. The targeted population are seniors 65 years and older. The client must have Medicare and reside in an eligible Montgomery county zip code. The program will reduce hospital
Congestive heart failure is a chronic condition that is responsible for the highest number of hospitalizations among adults. Readmission rates after hospitalization also remain high, with 50% of patients being readmitted within 6 months of discharge. (Desai & Stevenson, 2012). The Affordable Care Act penalizes hospitals with readmissions within 30 days after discharge, making readmissions a focus of hospitals nationwide. Several factors including discharge planning, patient education, diet restrictions, and early follow up appointments can help to reduce readmissions, but continuous monitoring is necessary to catch early signs of decompensation. (Desai & Stevenson, 2012).
Rising health care cost and stricter regulations for insurance reimbursement plans have pushed health care leaders to re-evaluate health care services. One focus is reducing hospital readmission rates for chronic disease process (Bos-Touwen et al, 2015). Congestive heart failure is one of the leading causes of hospital readmission (Cubbon et al, 2014). Fifteen million people worldwide have a diagnosis of CHF. In addition, 15-20% of those with the diagnosis of CHF are hospitalized yearly (Sahebi et al, 2015). In 2010, 40 billion dollars was spent on health care needs for CHF patients. Seventy percent of the resources were for hospital services (Siabani, Driscoll, Davidson, and Leeder, 2014). The need for streamline healthcare for CHF patients is imperative to improve overall patient outcomes and reduce the amount of hospital readmission rates.
A great amount of time, money and resource is devoted to improving the transition to home from hospital in the heart failure patient (Qaddoura, Ashoori, Kabali, Thabane, Haynes, Connolly & Spall, 2015). With extensive research available on heart failure and readmission, this study will focus on four main categories. This four category approach allows the clinician to best formulate and prepare for practice in the outpatient setting. The four categories will include various articles based upon evidenced based practice approaches with ultimate goal of reducing admission by implementing successful outpatient care. The four categories are as follows: Frequent monitoring or reporting to the PCP; Medication and Diet compliance; Predictors of
Congestive heart failure is a chronic disease that requires daily monitoring and life style management. Affecting the elderly, and their family the adjustment is a challenge. Daily life skills include the monitoring of daily weights, intake and output, and a low sodium diet. The person with congestive heart failure is generally admitted to the hospital for medication adjustments when their symptoms increase. The patient is often times short of breath, with a decrease in energy and an increase in their weight. The patients are generally elderly 60-65 years of age or older, and when comparing African Americans to Caucasians the African Americans have a 1.5 greater chance of developing heart failure ("Heart Failure," 2017). The