Interqual Criteria

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

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

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

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,

Congestive Heart Failure (CHF) patients and their consistent trending of hospital re-admissions continue to threaten quality care and patient quality of life. Considered a chronic condition, CHF is diagnosed in approximately 13% of patients 85 or older (Clarke, Shah & Sharma, 2011). Re-admissions have become so prevalent among the CHF populations, that Centers for Medicare has initiated a quality campaign and offers incentives when hospitals implement telemedicine programs and show reduction in CHF hospital admissions. In relation to CHF, Conway, Inglis, and Clark (2014) states that, “Telemedicine involves transmission of physiological data, such as weight, … from the measuring device to a central server via telephonic, satellite,

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

A resident at the time saw that although there is a hearty amount of evidence that illustrates that adhering to heart failure guidelines decreases the rate of mortality and morbidity, nationally there is modest adherence to heart failure practice guidelines. Doctors have voiced a multitude of reasons to this poor participation including but not limited to time constraints in a visit, inertia of patterns in practice, lack of awareness and lack of acceptance are a few. This new web-based tool, the “Smart” Heart failure sheet is designed to help connect previously compartmentalized information. It seeks to link guidelines to their patients’ clinical and laboratory characteristics and systematize adherence to heart failure guidelines. It accomplishes this by uploading pertinent patient-specific data, including laboratory and imaging results, procedure reports and relevant medications. Additionally it also provides tools, such as a flow chart for diuretic dosage and weights. Overall this tool is useful to help physicians identify patients who may benefit from a treatment. From there it provides support tools that alert the physician to a personalized medical treatment. The “Smart” Heart Failure Sheet acts as a registry for scholarly research and also provides educational resources to expand providers’ knowledge, thereby improving patient care (Battaglia,

Approximately 5.3 million Americans have heart failure and account for more hospital admissions than any other diagnosis in patients over 65

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.

As one of the most frequent hospital discharge diagnosis in the elderly, the cost of heart failure on Medicare expenditures toped over $39 billion in 2010 (Warden, Freels, Furuno, & Mackay, 2014). For over 25 years, there have been studies looking at the number of readmissions of geriatric heart failure

Heart failure (HF) is one of the leading causes of hospital admissions and readmissions in the United States (Desai & Stevenson, 2012; Gheorghiade, Vaduganathan, Fonarow, & Bonow, 2013). It is a condition that accounts for a very high morbidity and mortality (Bakal, McAlister, Liu, & Ezekowitz, 2014). Every hospital admission for heart failure patients results in disease progression and poor prognosis. For chronic HF patients, a hospitalization is one of the strongest prognostic predictors for increased mortality (Gheorghiade et al., 2013). Factoring in re-hospitalizations, especially at 30-day to 90-day mark, it is increasingly detrimental to patient prognosis.

Healthcare in the United States is changing which has given rise to new hurdles that must be overcome. One of the issues that we are currently facing in many tertiary facilities is the need for set criteria involving intensive care unit admissions and discharges. Throughout the country the total number of intensive care unit (ICU) beds are on the rise, but the current supply still outnumbers the demand (Cognet & Coyer, 2014). The cost of staying in an ICU is continuing to increase with technology, and there are limitations that insurance companies and the government have set forth to the number of days a patient can reside there dependent upon his diagnosis and condition. Intensive care units will continue to undergo strain due to high census, and decisions to discharge patients will be effected (Wagner, Gabler, Ratcliffe, Brown, Strom, & Halpern, 2013). Typically, the decision to have a patient occupy an ICU bed is based upon whether or not they are sick enough to be there or if they are well enough to be discharged to a progressive care unit (PCU) or medical surgical unit (Meyer, 2003). A progressive care unit is a step down from an ICU, but has stricter criteria for admission than a medical surgical unit based upon the patients medical status. Not all facilities offer a PCU, but the need for this level of care is continuing to rise with the number of ICU admissions increasing. Standardized guidelines for patient placement in