Patients who have chronic diseases are often readmitted to the hospital within 30 days of being discharged. In the United States preventable hospital readmissions cost approximately $12-$17.4 billion annually. The Institute of Healthcare Improvement [IHI] has identified one key measure for reducing preventable readmissions and that is a timely post hospital follow-up visit. Although this seems to be a simple task, studies have revealed that as many as one-third of patients discharged from the hospital are not following up with their primary care provider. In North Dakota the percentages of patients with chronic diseases such as heart failure, chronic obstructive pulmonary disease, type 2 diabetes, and pneumonia have steadily increased over the last several years. A North Dakota critical access hospital report revealed a high percentage of patients with a chronic disease are being readmitted within 30 days. Identifying barriers to care in North Dakota can help to reduce the rate of readmission within the state. This study seeks to identify perceived barriers as observed by primary care nurse practitioners to improve patient outcomes and reduce hospital readmission rates.

Heart failure (HF) is a clinical syndrome associated with high morbidity and mortality with a large economic burden, and is the leading cause of hospitalizations among Medicare beneficiaries in the United States. Healthcare reform has focused on strategies to reduce HF readmissions, including outpatient HF clinics. Purpose: The purpose of this DNP Project was to answer the following question: In adult patients diagnosed with HF, how does enrollment in the HF clinic, compared to non-enrollment affect hospital admission and readmission rates? Methods: A retrospective analysis of 767 unique patients and their 1,014 respective admissions and readmissions was conducted. Continuous and categorical data was analyzed and presented as a mean (M), standard deviation (SD), absolute number (N) and percentage (%). A Pearson Chi Square test was used for categorical variables and Analysis of Variance was used for age and ejection fraction (EF). Results: Study sample demographics (N=767); age (M=79.72, SD=7.48); gender (57.6 % male) and EF (M=0.43, SD=0.16) were evaluated. The No HF clinic (No HFC) and HF clinic (HFC) enrollment groups (N=573) were compared for age (M=79.49, SD=7.65) (M=80.39, SD=6.94), male gender (54.6%, 66.5%) and EF (M= 0.44, SD=0.17) (M=0.42, SD=0.15), respectively. Each sample patient had at least one admission for HF during 2015; of which 573 (46.2%) were in the No HFC group and 194 (8.4%) were in the HFC group (p<0.001). There was no difference in all-cause readmissions between the No HFC group [n=95(14.5%)] and the HFC group [n=37(16.2%)] (p=0.534) and no difference in HF-related readmissions between the No HFC group [n=72(11.0%)] and the HFC group [n=23(10.0%)] (p=0.700). Conclusions: This DNP project demonstrated a significant difference in HF admission rates in favor of the HFC group. While no differences were found in all-cause or HF-related readmission rates in No HFC and HFC groups, the rates are less than the national average. Unintended findings were that datasets can be very poorly constructed and populated, resulting in large amounts of unusable data. Recommendations are for more rigor in the organization of datasets to assure accurate comparisons between admission and readmission rates based on enrollment in HF clinics.

Heart Failure readmissions (HFR) significantly contribute to all cause hospital readmissions rates. Current evidence on the effectiveness of interventions for reduction of HFR is inconclusive. Recent research suggests that nurses’ emotional intelligence (EI) may be associated with better patient outcomes. The purpose of this study was to examine if nurses’ EI is significantly related to HFR and if that relationship is mediated through patient satisfaction with care. One hundred and thirty six Registered Nurses were recruited from 11 in-patient units at a large teaching hospital in the south eastern United States. Two surveys were mailed to eligible participants; the Bar-On Emotional Quotient Inventory 2.0 and a demographic survey. Patient satisfaction was measured with the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. The unit of observation for the analysis of the current study was the individual nursing unit with monthly measures for 14 months. Nurses EI was assessed at a single point in time and served as the basis for the data collected. Results of one-way ANOVA showed a non-significant small trend of higher total EI being associated with lower rates of HFR. The generalized estimating equation model was used to account for correlated observations and revealed a greater non-significant likelihood for higher total EI to translate to no HFR. Results of Pearson’s correlations found non-significant positive correlations between nurses total EI and the patient satisfaction items of rate hospital, nurses’ courtesy and respect, nurse listening, nurse explaining, and nurse communication. The linear mixed model to account for correlated observations showed small non-significant trends for total nurse EI and all patient satisfaction items. Results of one-way ANOVA showed no association between patient satisfaction and HFR. When accounting for correlated observations, increases in total nurse EI were not significantly associated with the predicted odds of no HFR. In conclusion, the examination of the aims in this study demonstrated results that were in the expected direction but not at the level expected. The findings of this study indicate that there is a need to further examine how nurses’ EI may influence patient outcomes.

INTRODUCTION: While transitions of care (TOC) programs are known to decrease readmissions for heart failure (HF), significant policy and resource challenges inhibit the implementation of hospital based TOC programs, thus novel models of TOC are urgently needed. The purpose of this study is to evaluate the need and readiness of a private practice based TOC program led by DNP-prepared nurse practitioners. METHODS: In this descriptive study, cardiology providers from a private practice in the Southwest (N=14) participated in a survey on HF TOC. The practice’s electronic medical records (EMR) database was queried for patient demographic data along with other HF measures (N=3175). RESULTS: There were 1,827 females (57.5%) and 1,348 males (42.5%) with the mean age being 75.1 years +/-11.1. The 70-79 year age bracket represented 41.0% of all HF patients. The most common ICD-10 code for HF was [I50.32] Chronic Diastolic Congestive Heart Failure (N=986), which translates into 31.0% of the total HF population. Almost 30% of the providers (N=4) acknowledge that they never document their HF readmissions in the practice’s EMR. Nearly 65% percent of respondents “strongly agree,” that HF patients discharged from the hospital require a specific plan of care, while 86% of providers (N=12) either “somewhat agree” to “strongly agree” in the need for a TOC program for HF patients within their cardiology practice. Over 71% (N=10) of the providers “strongly agree” with a DNP-led TOC program for HF. CONCLUSION: This study provides encouraging results for the future implementation of a cutting edge private cardiology practice based TOC program for HF in Tucson, AZ. The study results clearly indicate the need and readiness for the Tucson-based private practice TOC program for HF. The DNP prepared nurse practitioner is thoroughly prepared to take the lead in designing, implementing and evaluating such a program and this unique role was supported by the practice. Importantly, the results of this study may provide the foundation for future studies examining the effects of private practice based TOC programs for HF.

No description available.

Thesis (M.S.)--Boston University

The current fragmented delivery of health care has contributed to unplanned hospital readmissions as a leading problem in the United States. Reducing readmissions to urban teaching hospitals is difficult. Many patients living in urban communities face social, economic, language, and transportation barriers to maintaining their health. Both the patient and the medical center experience the burden of readmission and are challenged with addressing SDoH and social injustices at several levels. Medicare views hospital readmissions as a marker representing lower quality of health care delivery to penalize hospitals providing care to the poor. This thesis addresses multiple social and economic factors associated with hospital readmissions, explores the interrelated components of readmissions at the personal and hospital system level, and delves into the interactions of bioethical principles associated with urban living. Hospital readmissions remain a serious issue nationwide and in order to reduce the rates of re-hospitalization the social and economic inequalities contributing to hospital readmissions are significant and must be addressed. / Urban Bioethics

In the United States, congestive heart failure (CHF) is a cardiac condition with increasing hospitalization and rehospitalization burden to patients, families, and the healthcare system. This chronic condition is expected to affect more than 8 million people by 2030; however, not much is known about the relationship between risk factors and hospital readmissions once CHF patients are discharged to a skilled nursing facility (SNF). Applying a systems theory unbounded systems thinking, coupled with a systems-thinking approach the purpose of this quantitative, retrospective cohort study was to examine CHF hospital readmissions from SNFs within a 90-day period using a secondary data set of gender, age, race, SNF geographic location, length of SNF stay, and home health use risk factors. A binary logistic regression analysis revealed that out of 238 episodes, 99 patients were readmitted; however, no statistically significant relationship between the risk factors and readmission was found. Findings suggest that CHF readmissions from the SNF are not attributed to only quantifiable risk factors. Based on these findings, further research can support social change through multifaceted quantitative and qualitative systemic analyses to identify and inform how healthcare organizations can better assist the elderly population with CHF and improve future post-acute community-based health education and prevention programs.

Healthcare costs have risen from 13.8% in 2000 to 17.9% in 2009 (Gordon, Leiman, Deland, & Pardes, 2014). Poor transitional care has been identified as a cause of the high healthcare costs (Naylor et al., 2013; Obama, 2013). In 2009, the Department of Veterans Health Administration (VHA) implemented a national reform of outpatient care to create Patient-Aligned Care Teams (PACTs) with a goal to improve transitional care and reintegration into outpatient care through registered nurse case managers conducting discharge telephone follow-up calls. However, discharge telephone follow-up calls have not been explored within the VHA. This study explored the relationships among discharge telephone follow-up calls, selected Veteran characteristics including the length of index hospital stay, and 30-day all cause hospital readmissions between fiscal years 2011 and 2013. Hospital readmissions were explored in parallel time periods to the timing of the discharge telephone follow-up calls. Study data were collected retrospectively from VHA inpatient and outpatient records. Descriptive statistics, measures of central tendency, bivariate statistics, and logistic regression were used to analyze the data. The study found 124,069 Veterans were discharged from the VHA from 2011 to 2013. Of those discharges, 15,954 (12.86%) were readmitted to the hospital within 30 days and 35.06% of the readmissions occurred within the first seven days after discharge. Discharge telephone follow-up calls increased from 312 in 2011 to 26,549 in 2013. Increasing Veteran age, number of comorbidities, length of index hospital stay, and being identified as frequently hospitalized in the previous year were significantly related to hospital readmissions at each of the hospital readmission time frames (within two days, between three and seven days, and between eight and thirty days after hospital discharge). This study identified a relationship between discharge telephone follow-up calls and the parallel hospital readmission time period. However, only discharge telephone follow-up calls within two days were found to decrease the likelihood of hospital readmissions and only hospital readmissions within two days after discharge (OR=0.595). The relationships between discharge telephone follow-up calls and hospital readmissions potentially explains previously mixed results and suggests two potential explanations. One, discharge telephone follow-up calls have a limited relationship to hospital readmissions and a short duration of protective effects preventing hospital readmissions. The second explanation is self-selection bias confounds the relationship between discharge telephone follow-up calls and hospital readmissions. Both explanations suggest future research and clinical practice should focus on exploring bundled transitional care interventions as a method to reduce hospital readmissions.

Objective: The purpose of this study was to investigate pneumonia readmissions of older adults with dementia. Readmission rates and predictive factors of older adults with and without dementia were compared in this study. Subjects: A nationally representative sample of 389,198 discharge records, representing 370,003 patients, was extracted from the 2013 Nationwide Readmission Database. Methods: Descriptive statistics were utilized to describe the demographics of the sample population. Differences between groups were analyzed using chi-square or t test statistics as appropriate. A generalized linear model was used to examine predictive factors for pneumonia readmissions. Results: Older adults with dementia had a readmission rate of 23.52% and were 2.9 times more likely to experience a pneumonia readmission than older adults without dementia. Significant differences in characteristics were found when comparing (a) older adults with and without dementia, (b) older adults with and without dementia who were readmitted, and (c) older adults with dementia who were and were not readmitted. Factors that significantly interacted with dementia included (a) discharge disposition, (b) number of chronic conditions, (c) risk of mortality, and (d) median household income. Conclusions: Classifying older adults with dementia as a high-risk group for pneumonia readmissions is supported by the findings of this study. More over, dementia diagnoses significantly affect discharge disposition, there are characteristic differences among older adults with dementia, and comorbidities and risk of mortality significantly affect pneumonia readmissions. Development of strategies to reduce pneumonia readmissions that are tailored to individuals with dementia should be considered.