Class of 2013 Abstract / Specific Aims: The purpose of this study was to determine what characteristics are most often associated with patients who are readmitted to a hospital for care within a 30-day time period for one of the five applicable conditions listed in the Hospital Readmissions Reduction Program, including heart failure, pneumonia, myocardial infarct, vascular procedures, and chronic obstructive pulmonary disease. Methods: This study was a retrospective chart review of patients who had a 30-day inpatient hospital readmission to a tertiary referral teaching hospital in Tucson, Arizona during the period from January 1, 2012 to June 30, 2012. Patient demographics and other characteristics thought to influence readmission were collected, including sex, age, race, type of insurance, number of applicable diagnoses at first admission, and number of medications prescribed at first discharge. “Applicable diagnoses” included: congestive heart failure (CHF); pneumonia (PN); myocardial infarct (MI); vascular procedures (VP); and chronic obstructive pulmonary disease (COPD). Main Results: Of the 1,102 patients included in this study, only 5% were readmitted for one of the five applicable conditions. The largest proportion of patients who were readmitted for the same diagnosis were in the 21 to 40 year old category, whereas the largest proportion of patients who were readmitted for different diagnoses were in the greater than 40 year-old category. The results of the multiple regression analysis showed that none of the independent variables predicted 30-day readmissions with the exception of Asian race (p=0.008, n=8) and other race (p=0.012, n=57). In addition, the only significant predictor of 30-day readmission was the diagnosis at initial admission (p<0.05). Conclusion: In our sample, only 5% of patients readmitted at 30-days were readmitted for an applicable condition. This means the majority of readmissions include diagnoses that are not currently affected by the changes to Medicare reimbursement, though other diagnoses are likely to be added to the list in the coming years. Our study provides evidence that specific patient demographic characteristics are not closely linked to 30-day readmissions. Therefore, it may be necessary to turn the focus away from targeting specific patient populations and towards improving efforts in the areas of discharge planning and quality of care for all patients.

Background Syncope accounts for 0.6% to 1.5% of hospitalizations in the United States. We sought to determine the causes and predictors of 30‐day readmission in patients with syncope. Methods and Results We identified 323 250 encounters with a primary diagnosis of syncope/collapse in the 2013-2014 Nationwide Readmissions Database. We excluded patients younger than 18 years, those discharged in December, those who died during hospitalization, hospital transfers, and those whose length of stay was missing. We used multivariable logistic regression analysis to evaluate the association between baseline characteristics and 30‐day readmission. A total of 282 311 syncope admissions were included. The median age was 72 years (interquartile range, 58-83), 53.9% were women, and 9.3% had 30‐day readmission. The most common cause of 30‐day readmissions was syncope/collapse, followed by cardiac, neurological, and infectious causes. Characteristics associated with 30‐day readmissions were age 65 years and older (odds ratio [OR], 0.7; 95% confidence interval [CI], 0.6-0.7), female sex (OR, 0.9; 95% CI, 0.8-0.9), congestive heart failure (OR, 1.5; 95% CI, 1.2-1.9), atrial fibrillation/flutter (OR, 1.3; 95% CI, 1.3-1.4), diabetes mellitus (OR, 1.2; 95% CI, 1.2-1.3), coronary artery disease (OR, 1.2; 95% CI, 1.2-1.3), anemia (OR, 1.4; 95% CI, 1.4-1.5), chronic obstructive pulmonary disease (OR, 1.4; 95% CI, 1.3-1.4), home with home healthcare disposition (OR, 1.5; 95% CI, 1.5-1.6), leaving against medical advice (OR, 1.7; 95% CI, 1.6-1.9), length of stay of 3 to 5 days (OR, 1.5; 95% CI, 1.4-1.6) or >5 days (OR, 2; 95% CI, 1.8-2), and having private insurance (OR, 0.6; 95% CI, 0.6-0.7). Conclusions The 30‐day readmission rate after syncope/collapse was 9.3%. We identified causes and risk factors associated with readmission. Future prospective studies are needed to derive risk‐stratification models to reduce the high burden of readmissions. / Revisión por pares

Class of 2016 Abstract and Report / Objectives: An estimated 5.7 million Americans had heart failure (HF) in 2012 with an economic cost of $30.7 billion. By 2030 the prevalence of the disease is expected to increase by 46%. Centers for Medicare and Medicaid Services penalizes hospitals for 30-day readmissions. This study evaluated the effect of our multidisciplinary HF intervention on readmissions. Methods: This is a retrospective cohort study. Patients were identified from electronic inpatient admission records from January 1 to December 31, 2014. Patients who received any component of intervention were compared to patients who did not receive any intervention. Intervention included student pharmacist medication counselling, HF education, and post-discharge phone calls with Modified Morisky questionnaire. Age, sex, admission/discharge dates, readmission diagnosis, smoking status, ejection fraction, medications, and Charlson Comorbidity Index (CCI) conditions were collected. Results: A total of 221 patients with 249 discrete admissions were identified. No difference in age (p=0.42), sex (p=0.48), smoking status (p=0.10) existed between the groups. No difference in readmissions was found between patients receiving complete intervention and control (p=0.41) or patients receiving 1 or 2 intervention components and control (p=0.41). Patients with CCI score≥ 8 had greater risk of readmission compared to CCI scores 0-2 (OR 7.7, 95% CI 1.6-36.3, p=0.01). Conclusions: This analysis did not identify an intervention impact on 30-day readmissions in patients with HF; high CCI scores were associated with increased readmission risk. The intervention may be best targeted towards patients with high CCI scores as they have the highest readmission rate.

Each year in the United States, thousands of people are readmitted within 30 days of being discharged from a hospital. Current research indicates that at least one-third of these rehospitalizations are preventable. The purpose of this project was to examine patient and environmental characteristics of those who were readmitted within 30 days of discharge for commonalities that may explain the gap in practice for a specific health care organization. The project was undertaken in response to the organization's need to improve a 50th-percentile ranking with the goal of reaching the top 10th percentile. A plan-do study-act framework was used as a guide to ensure no steps in the process were missed and the logical progression of the project was clear. Three fiscal quarters of data, including 515 readmissions, were examined. A data analytics cube on hospital-wide readmissions provided patient and environmental characteristics that were charted using common language for sorting purposes. Data analysis revealed that 77% of patients were admitted within 30 days of discharge with a diagnosis that differed significantly from the index admission. Potential gaps in practice identified were a need for more patient and family engagement and education by nursing during the inpatient stay in regard to the primary admitting condition, the management of comorbidities, and potential posthospital complications. Need exists for more intense whole-patient monitoring, communication, and education following the transition from hospital to home. A reduction in 30-day readmissions can reduce the psychological and physical burden on patients and families, on health care resources that could be used for other purposes, and on society in the form of financial costs that continue to rise.

Information from anecdotal interviews at a practicum site indicated a lack of training for advanced practice providers (APPs) in core competencies critical for effective practice in a heart failure (HF) unit. The goal of this project was to assess the APPs' verbal reports and develop HF unit-specific training for APPs. The practice-focused question examined whether unit-specific training for HF APPs improved knowledge and skills in HF management. The Johns Hopkins nursing evidence-based practice model and Knowles's adult learning theory were used to create a survey, a focus group, and a pre/posttest assessment of knowledge and skills gap. Descriptive and inferential statistics could be used to analyze pre/post survey data, and thematic analysis could be used to analyze focus group data. Assessment data could be used to develop a targeted HF program based on identified skill deficiencies. The implications of this project related to social change are the potential to increase APPs' knowledge, job engagement, and retention. The program could affect length of stay and 30-day readmission of patients in the HF unit.

U.S. healthcare consumers have access to various provider ratings from several organizations that are meant to assist in selecting their healthcare providers. Leapfrog Hospital Safety Grades is one such rating system that professes to allow consumers the ability to select the best hospital for their care. However, since consumers ranking mortality risk as their most important concern, it is essential to determine if Leapfrog grades align with consumer expectations. Andersen's Phase-4 behavioral model of healthcare utilization was used as the foundation for understanding healthcare consumer preferences. This study was designed to determine if Leapfrog grades are predictive of CMS 30-day mortality rates for pneumonia, chronic heart failure, and acute myocardial infarction data, while also adjusting for selected organizational descriptors: state of residency, Medicare expansion, safety-net status, ownership type, teaching classification, and number of licensed beds. Linear regression demonstrated that Leapfrog grades are not reliable predictors of the 3 inpatient mortality rates analyzed. The study demonstrated that ownership type was a significant predictor for 2 of the 3 dependent variables. Furthermore, most of the covariates also provided some predictive value for at least 1 of the included outcomes; however, in most cases, the effect (β) was small. This study can help provide positive social change by elucidating that Leapfrog grades are not reliable predictors of patient outcomes for consumers, while also demonstrating that efforts to reduce 30-day mortality rates, especially for pneumonia, can be targeted by selected states, ownership type, and teaching status.

Heart failure is a complex heart disease that incapacitates more than 5 million people, is associated with increasing healthcare cost, and remains the leading cause of admission in the United States. As the United States faces increasing financial burden related to readmission of heart failure patients within 30 days of discharge, many healthcare institutions are evaluating interventions to determine the most effective opportunities to improve systems, including nursing practice. The purpose of this doctoral project was to improve readmission rates within 30 days of discharge from an acute care facility through the development and implementation of a standardized, evidence-based, patient-centered discharge education toolkit using the Teach-Back method. Orem's self-care theory and the situation-specific theory of heart failure self-care were utilized as a theoretical framework to inform this doctoral project. The sources of evidence were obtained from the Get With The Guidelines-Heart Failure database and through a review of nursing and health-related databases. Descriptive statistics were used to compare the pre- and posteducation session readmission rates. The rate of readmissions occurring within thirty days of discharge pre- and post-educational session retrieved from the GWTG-Heart Failure database were 9.4% and 0.0% respectively. These results showed that this discharge toolkit reduced heart failure 30-days readmission rates. The limitations and strengths of this project will be used to guide further research on heart failure readmission and self-care management. This DNP project will promote positive social change for clinicians, who can use this discharge toolkit to improve self-management in adults with heart failure and thus decrease the costs related to readmission.

Early avoidable 30-day post discharge readmission among patients diagnosed with chronic obstructive pulmonary disease (COPD) is associated with poor transition care processes. The purpose of this project was to analyze organizational system processes for admission and discharge transition care of patients diagnosed with COPD to identify key intervention strategies that could decrease the rate of 30-day post-discharge readmission by 1%. The project used the transitional care model as the framework to target specific care transition needs and create patient-centered, supportive, evidence-based relationships among the patient, the providers, the community, and the health care system to identify key intervention strategies for implementation. A retrospective chart review was conducted of transitional care management and care coordination practices of providers of patients diagnosed with COPD. Analysis of the data revealed that the local regional organization used a single, generic, computerized discharge planning and care transition process for patients diagnosed with COPD. As a result, missed opportunities to target a patient's specific care needs led to higher rates of readmission. The implications of the findings of this project for social change include identification of evidence-based recommendations and practices that could influence clinician practices and improve patient outcomes and the quality of health care delivery.

Heart failure (HF) is a serious public health problem associated with high mortality rates, hospital readmissions, and health care costs. Transitional care has emerged as a disease management model used to reduce readmissions for hospital-discharged patients with HF. However, the efficacy of an advanced practice nurse (APN)-led transitional care program (TCP) in readmission reduction is under debate. The practice question for this project examined the extent to which an APN-led TCP was effective in reducing 30-day all-cause readmissions for hospital-discharged HF patients. The logic model was the framework guiding this program evaluation. An analysis of quality improvement HF data from September 2015 to August 2016 was reviewed for one hospital in southern California. The APN-led TCP included 47 patients and had 7 patients with 30-day readmissions. The physicians' group included 298 patients and had 53 patients with 30-day readmissions. The results of chi-square analysis revealed a nonsignificant association between 30-day readmissions and post-discharge care providers [Ï? 2 (1, N = 345) = 0.236, p = 0.627], and the HF 30-day readmission rates were the same between two groups. The APN-led TCP served a large proportion of Medi-Cal patients (48.94%) who had less primary care access, while the majority of patients in the physicians' group were Medicare (51%) who had primary care providers. This project highlights the positive social changes that advanced practice nurses affect via their critical leadership and clinical roles in increasing care access for the low-income population. Further studies on payer sources and readmissions are recommended on the efficacy of APN-led TCP in readmission reduction.

In a stroke-certified 500-bed acute care hospital, the 30-day readmission rates for patients discharged to rehabilitation centers or skilled nursing facilities were higher than the rates for patients discharged to home. A review of data by the stroke team showed 44 patients readmitted within 30 days of initial stroke discharge between October 2016 and January 2017. The rate of re-admission for those discharged home was 41% (18 patients), whereas the rate for those discharged to acute inpatient rehabilitation, long-term acute care, or skilled nursing facilities was 59% (26 patients). The practice-focused question for this project assessed whether using a re-admission risk-assessment tool and implementing interventions during the initial acute-care admission, would help to identify and improve risk for 30-day re-admissions for patients diagnosed with stroke. The goal of this research project was to adopt, test, and recommend the implementation of a readmission risk assessment tool to enable discharge planners to identify stroke patients at risk for readmission and implement interventions to help reduce this risk. Lewin’s theory of change was used to inform the project. A stroke re-admission risk-assessment tool in use at a similar hospital was adopted and tested for 1 week on the hospital’s 28-bed stroke unit by nurse case managers. The test was conducted among 5 patients with confirmed diagnosis of stroke. A re-admission data review was performed 30 days after their discharge, which showed no readmissions for the 5 patients involved in the trial. The tool helped to improve case manager awareness of increased risk for readmissions, guide interventions, and improve patient transition and outcomes. The implications of this project for positive change include the potential to improve risk for patients with stroke in the acute-care facility.