Improving Postdischarge Outcomes in Acute Heart Failure

The global burden that acute heart failure (AHF) carries has remained unchanged over the past several decades (1). European registries (2–5) showed that 1-year outcome rates remain unacceptably high (Table 1) and confirm that hospitalization for AHF represents a change in the natural history of the disease process(6). As patients hospitalized for HF have a bad prognosis, it is crucial to utilize hospitalization as an opportunity to: 1) assess the individual components of the cardiac substrate; 2) identify and treat comorbidities; 3) identify early, safe endpoints of therapy to facilitate timely hospital discharge and outpatient follow-up; and 4) implement and begin optimization guideline-directed medical therapies (GDMTs). As outcomes are influenced by many factors, many of which are incompletely understood, a systematic approach is proposed that should start with admission and continues through post-discharge (7)

A Quality Initiative to Reduce Pneumonia Readmissions and Mortality in Older Adults

The United States (U.S.) healthcare system journey for making improvements in the quality and value of healthcare continues. Hospital organizations are required to compose and make publically available their health quality outcome data. The publication transparency and increased availability of local, regional and national health quality metrics, including readmission and mortality rates, to governmental agencies, health plans, investors, other hospitals, providers and potential patient and families’ knowledge, creates a competitive pressure for a hospital to assure their quality outcomes data are the best. Despite breakthrough improvements using innovative care models that target vulnerable and potentially high cost of care areas such as individuals with chronic illnesses, complex health and social needs, children, and frail elders, have been seen, there remains a need for quality improvement (QI) initiatives to reduce particularly avoidable hospital readmissions and mortality. A Midwest hospital system identified that their 30-day pneumonia (PNA) readmission rate for FY2017 was higher than the national median and the peer hospitals Centers for Medicare and Medicaid Services (CMS) benchmark percentage. The assumption was if there are more programs and resources available to the PNA patient then there should be better health outcomes. This project evaluated the differences in the PNA patient outcomes, mortality and readmission rates based on the number of hospital readmission reduction strategies (RRS) identified and available for the PNA Medicare patients among three of the Midwest hospital system acute care facilities. The results of the Chi-square test of independence performed to examine differences between the total number of RRS in FY 2018 and FY 2019 and readmission and mortality rates was significant for readmissions, χ2 (3, N= 107) = 25.15, p \u3c .001, and mortality χ2 (3, N= 58) = 34.93, p

Hospitalization for Heart Failure in the United States, UK, Taiwan, and Japan: An International Comparison of Administrative Health Records on 413,385 Individual Patients

BACKGROUND: Registries show international variations in the characteristics and outcome of patients with heart failure (HF) but national samples are rarely large, and case-selection may be biased due to enrolment in academic centres. National administrative datasets provide large samples with a low risk of bias. In this study, we compared the characteristics, healthcare resource utilization (HRU) and outcomes of patients with primary HF hospitalizations (HFH) using electronic health records (EHR) from four high-income countries (USA, UK, Taiwan, Japan) on three continents. METHODS AND RESULTS: We used EHR to identify unplanned HFH between 2012-2014. We identified 231,512, 10,991, 36,900 and 133,982 patients with a primary HFH from USA, UK, Taiwan and Japan, respectively. HFH per 100,000 population was highest in USA and lowest in Taiwan. Patients in Taiwan and Japan were older but fewer were obese or had chronic kidney disease. LOHS was shortest in USA (median 4 days) and longer in UK, Taiwan and Japan (medians 7, 9 and 17 days, respectively). HRU during hospitalization was highest in Japan and lowest in UK. Crude and direct standardized in-hospital mortality was lowest in USA (direct standardized rates: 1.8 [95%CI:1.7-1.9]%)and progressively higher in Taiwan (direct standardized rates: 3.9 [95%CI:3.8-4.1]%), UK (direct standardized rates: 6.4 [95%CI:6.1-6.7]%) and Japan (direct standardized rates: 6.7 [95%CI:6.6-6.8]%). 30-day all-cause (25.8%) and HF (7.2%) readmissions were highest in USA and lowest in Japan (11.9% and 5.1% respectively). CONCLUSION: Marked international variations in patient characteristics, HRU and clinical outcome exist; understanding them might inform health care policy and international trial design

Assessing Prevalence of Known Risk Factors in a Regional Central Kentucky Medical Center Heart Failure Population as an Approach to Assessment of Needs for Development of a Program to Provide Targeted Services to Reduce 30 Day Readmissions

Abstract Objectives: Determine demographic, physiologic, and laboratory characteristics at time of admission of the heart failure (HF) population in a regional acute care facility in Central Kentucky through review of patient electronic medical records. Determine which HF population characteristics are significantly associated with readmissions to the hospital. Provide identification of the statistically significant common characteristics of the HF population to this facility so that they may work towards development of an electronic risk for readmission predictive instrument. Design: Retrospective chart review. Setting: Regional acute care facility in Central Kentucky. Participants: All patients (n = 175) with a diagnosis or history of HF (to include diagnosis related group (DRG) codes 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, 428.1, 428.41, 428.23, 428.43, 428.31, 428.33, 428.1, 428.20, 428.22, 428.30, 428.32, 428.40, 428.40, 428.42, 428.0, and 428.9; The Joint Commission, 2013) admitted to the acute care setting of a regional hospital in the Central Kentucky area between the dates of January 1, 2013 and July 31, 2013. Eligible participants were identified via an electronic discharge report listing all patients discharged during the study time period with a HF code. Main Outcome Measure: A chart review was performed to define the HF population within the regional acute care facility. Abstracted information was collected on data instruments (Appendices A,B, and C) and analyzed to define the overall HF population (n = 175). The data was then analyzed to determine significance between patient characteristics (demographic, physiologic, and laboratory) and 30 day readmissions. The data was examined both on the individual patient level and independent of patient level looking at each admission independently. Results: An in depth description of the HF patient population in this facility was obtained. Several patient characteristics including a history of anemia, COPD, ischemic heart disease, diabetes, and the laboratory values creatinine and BNP outside of the reference range were found to have a significant association with 30 day readmissions. Discharge to a skilled nursing facility (SNF) was also found to be a significant predictor of 30 day readmissions. Some social variables such as marital status were not found to have a significant relationship to 30 day readmissions. Conclusion: This investigation is a stepping stone to creating an electronic tool designed to reflect the characteristics of HF population admitted to a single facility and predict risk of HF readmissions within 30 days at the time of admission. Implementation of a plan of care designed to meet the needs of this HF population as well as identify those patients at high risk for will allow for provision of a comprehensive and timely individualized plan of care to reduce the incidence of 30 day readmissions

Unplanned readmission rates, length of hospital stay, mortality, and medical costs of ten common medical conditions: a retrospective analysis of Hong Kong hospital data

<p>Abstract</p> <p>Background</p> <p>Studies on readmissions attributed to particular medical conditions, especially heart failure, have generally not addressed the factors associated with readmissions and the implications for health outcomes and costs. This study aimed to investigate the factors associated with 30-day unplanned readmission for 10 common conditions and to determine the cost implications.</p> <p>Methods</p> <p>This population-based retrospective cohort study included patients admitted to all public hospitals in Hong Kong in 2007. The sample consisted of 337,694 hospitalizations in Internal Medicine. The disease-specific risk-adjusted odd ratio (OR), length of stay (LOS), mortality and attributable medical costs for the year were examined for unplanned readmissions for 10 medical conditions, namely malignant neoplasms, heart diseases, cerebrovascular diseases, pneumonia, injury and poisoning, nephritis and nephrosis, diabetes mellitus, chronic liver disease and cirrhosis, septicaemia, and aortic aneurysm.</p> <p>Results</p> <p>The overall unplanned readmission rate was 16.7%. Chronic liver disease and cirrhosis had the highest OR (1.62, 95% confidence interval (CI) 1.39-1.87). Patients with cerebrovascular disease had the longest LOS, with mean acute and rehabilitation stays of 6.9 and 3.0 days, respectively. Malignant neoplasms had the highest mortality rate (30.8%) followed by aortic aneurysm and pneumonia. The attributed medical cost of readmission was highest for heart disease (US$3 199 418, 95$2 579 443-803 393).</p> <p>Conclusions</p> <p>Our findings showed variations in readmission rates and mortality for different medical conditions which may suggest differences in the quality of care provided for various medical conditions. In-hospital care, comprehensive discharge planning, and post-discharge community support for patients need to be reviewed to improve the quality of care and patient health outcomes.</p

Prediction Screening to Identify Heart Failure Patients at High Risk for Readmission

Background: There is an increased need to identify factors associated with higher risk for excessive HF re-hospitalizations due to hospitals receiving financial penalties related to these re-hospitalizations and poorer patient outcomes. Identifying HF patients at highest risk for re-hospitalization with a screening instrument upon admission to the hospital would allow for early implementation of interventions tailored around reducing risk factors for re-hospitalization. Objectives: The specific aims of this study were to 1) identify characteristics that were predictive of HF re-hospitalization; and 2) use those characteristics to create a screening instrument. Methods: A total of 158 patients (age=63±13; 50.6% female; 73.4% Caucasian; 63.3% NYHA class III/IV) admitted with a primary or secondary diagnosis of HF were included in this study. Patient’s knowledge of HF symptoms, along with socio-demographic, biophysical, and cognitive information was assessed by data collected with validated instruments as well as the electronic medical record. Chi square tests and independent t-tests were used to examine bivariate differences in the readmitted and the non readmitted groups. Cox proportional hazards modeling was used to predict the outcome, or time to hospitalization, based on the predictor variables. Results: The mean time to re-hospitalization was 68 days. Only 8 patients were re-hospitalized within the first 30 days. Depressive symptoms scores was the only variable identified as being significantly different (p Conclusions: Screening HF patients at highest risk for re-hospitalization and those with depressive symptoms will allow healthcare providers to individualize interventions to improve HF patient outcomes and reduce costly hospital re-hospitalizations