Robb D. Kociol

Effect of Nesiritide in Patients with Acute Decompensated Heart Failure

BACKGROUND Nesiritide is approved in the United States for early relief of dyspnea in patients with acute heart failure. Previous meta-analyses have raised questions regarding renal toxicity and the mortality associated with this agent. METHODS We randomly assigned 7141 patients who were hospitalized with acute heart failure to receive either nesiritide or placebo for 24 to 168 hours in addition to standard care. Coprimary end points were the change in dyspnea at 6 and 24 hours, as measured on a 7-point Likert scale, and the composite end point of rehospitalization for heart failure or death within 30 days. RESULTS Patients randomly assigned to nesiritide, as compared with those assigned to placebo, more frequently reported markedly or moderately improved dyspnea at 6 hours (44.5% vs. 42.1%, P=0.03) and 24 hours (68.2% vs. 66.1%, P=0.007), but the prespecified level for significance (P≤0.005 for both assessments or P≤0.0025 for either) was not met. The rate of rehospitalization for heart failure or death from any cause within 30 days was 9.4% in the nesiritide group versus 10.1% in the placebo group (absolute difference, -0.7 percentage points; 95% confidence interval [CI], -2.1 to 0.7; P=0.31). There were no significant differences in rates of death from any cause at 30 days (3.6% with nesiritide vs. 4.0% with placebo; absolute difference, -0.4 percentage points; 95% CI, -1.3 to 0.5) or rates of worsening renal function, defined by more than a 25% decrease in the estimated glomerular filtration rate (31.4% vs. 29.5%; odds ratio, 1.09; 95% CI, 0.98 to 1.21; P=0.11). CONCLUSIONS Nesiritide was not associated with an increase or a decrease in the rate of death and rehospitalization and had a small, nonsignificant effect on dyspnea when used in combination with other therapies. It was not associated with a worsening of renal function, but it was associated with an increase in rates of hypotension. On the basis of these results, nesiritide cannot be recommended for routine use in the broad population of patients with acute heart failure. (Funded by Scios; ClinicalTrials.gov number, NCT00475852.).

Troponin Elevation in Heart Failure: Prevalence, Mechanisms, and Clinical Implications

Circulating biomarkers have become increasingly important in diagnosing and risk stratifying patients with heart failure (HF). While the natriuretic peptides have received much focus, there is increasing interest in the role of circulating cardiac troponin (cTn) in detecting myocardial injury (often subclinical) in those with HF. Accumulating evidence suggests that patients with chronic and acute HF may have measurable levels of circulating cTn, whose detection and magnitude may have prognostic implications. Furthermore, as new, more sensitive cTn assays are being developed, larger numbers of HF patients are found to have detectable cTn with a persistent relationship between magnitude and outcome. This knowledge improves our ability to understand the mechanism of worsening HF, improve risk stratification, and detect potential injury related to new therapeutics in HF. As investigators begin to understand the relationship of detectable cTn to HF outcomes, as well as temporal changes in its magnitude, and its relationship to other circulating biomarkers, more insight may be gained into the progressive nature of cardiac dysfunction and the transition from chronic compensated to acute decompensated HF. Ultimately, this information might allow physicians to guide therapy, choose appropriate therapeutics, and improve HF outcomes.

Admission, Discharge, or Change in B-Type Natriuretic Peptide and Long-Term Outcomes Data From Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients With Heart Failure (OPTIMIZE-HF) Linked to Medicare Claims

Background— B-type natriuretic peptide (BNP) has been associated with short- and long-term postdischarge prognosis among hospitalized patients with heart failure. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results— We linked patients ≥65 years of age from hospitals in Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio for log transformation, 1.34; 95% confidence interval, 1.28 to 1.40) and 1-year death or rehospitalization (hazard ratio, 1.15; 95% confidence interval, 1.12 to 1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI, 5.5%, P <0.0001; IDI, 0.023, P <0.0001; 1-year mortality or rehospitalization: NRI, 4.2%, P <0.0001; IDI, 0.010, P <0.0001). Conclusions— Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with heart failure. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.Background— B-type natriuretic peptide (BNP) has been associated with short- and long-term postdischarge prognosis among hospitalized patients with heart failure. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results— We linked patients ≥65 years of age from hospitals in Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio for log transformation, 1.34; 95% confidence interval, 1.28 to 1.40) and 1-year death or rehospitalization (hazard ratio, 1.15; 95% confidence interval, 1.12 to 1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI, 5.5%, P<0.0001; IDI, 0.023, P<0.0001; 1-year mortality or rehospitalization: NRI, 4.2%, P<0.0001; IDI, 0.010, P<0.0001). Conclusions— Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with heart failure. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.Background —B-type natriuretic peptide (BNP) has been associated with short- and long-term post-discharge prognosis among hospitalized heart failure (HF) patients. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results —We linked patients ≥65 years from hospitals in OPTIMIZE-HF to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio [HR] for log transformation 1.34; 95% CI 1.28-1.40) and 1-year death or rehospitalization (HR 1.15; 95% CI 1.12-1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI 5.5%, P<0.0001; IDI 0.023, P<0.0001; 1-year mortality or rehospitalization: NRI 4.2%, P<0.0001; IDI 0.010, P<0.0001). Conclusions —Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with HF. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.

Patient characteristics from a regional multicenter database of acute decompensated heart failure in Asia Pacific (ADHERE International-Asia Pacific).

BACKGROUND Heart failure (HF) is a leading cause of hospitalization. Although a number of multicenter international HF hospital registries have been published, there are limited data for the Asia Pacific region. METHODS ADHERE (ie, Acute Decompensated Heart Failure Registry) International-Asia Pacific is an electronic web-based observational database of 10,171 patients hospitalized with a principal diagnosis of HF from 8 Asia-Pacific countries between January 2006 and December 2008. RESULTS The median age (67 years) varied by more than 2 decades across the region. Fifty-seven percent of patients were male. Ninety percent of patients were Asian and 8.4% were white. Dyspnea was the presenting symptom in 95%, with 80% having documented rales. During the index hospitalization, left ventricular function was assessed in 50%, and intravenous therapies included diuretics (85%), vasodilators (14%), and positive inotropes (15%). In-hospital mortality was 4.8%. Discharge medications included angiotensin-converting enzyme inhibitors and/or angiotensin receptor blockers (63%), β-blockers (41%), and aldosterone antagonists (31%). CONCLUSIONS Compared with other multicenter registries, patients hospitalized with acute HF in the Asia Pacific region tend to present with more severe clinical symptoms and signs and are younger, especially in countries at an earlier stage in their epidemiological transition. Echocardiography and disease-modifying medications are used less often, highlighting potential opportunities to improve outcomes.

International variation in and factors associated with hospital readmission after myocardial infarction.

CONTEXT ST-segment elevation myocardial infarction (STEMI) treatment has improved outcomes and shortened hospital stay. Recently, 30-day readmission rates have been proposed as a metric for care of patients with STEMI. However, international rates and predictors of 30-day readmission after STEMI have not been studied. OBJECTIVE To determine international variation in and predictors of 30-day readmission rates after STEMI and country-level care patterns. DESIGN, SETTING, AND PATIENTS Post hoc analysis of the Assessment of Pexelizumab in Acute Myocardial Infarction trial that enrolled 5745 patients with STEMI at 296 sites in the United States, Canada, Australia, New Zealand, and 13 European countries from July 13, 2004, to May 11, 2006. Multivariable logistic regression analysis was used to identify independent predictors of all-cause and nonelective 30-day postdischarge readmission. MAIN OUTCOME MEASURES Predictors of 30-day postdischarge all-cause and nonelective readmissions. RESULTS Of 5571 patients with STEMI who survived to hospital discharge, 631 (11.3%) were readmitted within 30 days. Thirty-day readmission rates were higher for the United States than other countries (14.5% vs 9.9%; P < .001). Median length of stay was shortest for US patients (3 days; interquartile range, 2-4 days) and longest for Germany (8 days; interquartile range, 6-11 days). In multivariable regression, the predictors of 30-day readmission included multivessel disease (odds ratio [OR], 1.97; 95% CI, 1.65-2.35) and US location (OR, 1.68; 95% CI, 1.37-2.07). Excluding elective readmission for revascularization, US enrollment was still an independent predictor of readmission (OR, 1.53; 95% CI, 1.20-1.96). After adjustment of the models for country-level median length of stay, US location was no longer an independent predictor of 30-day all-cause or nonelective readmission. Location in the United States was not a predictor of in-hospital death (OR, 0.88; 95% CI, 0.60-1.30) or 30-day postadmission death (OR, 1.0; 95% CI, 0.72-1.39). CONCLUSIONS In this multinational study, there was variation across countries in 30-day readmission rates after STEMI, with readmission rates higher in the United States than in other countries. However, this difference was greatly attenuated after adjustment for length of stay.

Admission, Discharge, or Change in B-Type Natriuretic Peptide and Long-Term OutcomesClinical Perspective

Background— B-type natriuretic peptide (BNP) has been associated with short- and long-term postdischarge prognosis among hospitalized patients with heart failure. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results— We linked patients ≥65 years of age from hospitals in Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio for log transformation, 1.34; 95% confidence interval, 1.28 to 1.40) and 1-year death or rehospitalization (hazard ratio, 1.15; 95% confidence interval, 1.12 to 1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI, 5.5%, P <0.0001; IDI, 0.023, P <0.0001; 1-year mortality or rehospitalization: NRI, 4.2%, P <0.0001; IDI, 0.010, P <0.0001). Conclusions— Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with heart failure. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.Background— B-type natriuretic peptide (BNP) has been associated with short- and long-term postdischarge prognosis among hospitalized patients with heart failure. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results— We linked patients ≥65 years of age from hospitals in Organized Program to Initiate Lifesaving Treatment in Hospitalized Patients with Heart Failure (OPTIMIZE-HF) to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio for log transformation, 1.34; 95% confidence interval, 1.28 to 1.40) and 1-year death or rehospitalization (hazard ratio, 1.15; 95% confidence interval, 1.12 to 1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI, 5.5%, P<0.0001; IDI, 0.023, P<0.0001; 1-year mortality or rehospitalization: NRI, 4.2%, P<0.0001; IDI, 0.010, P<0.0001). Conclusions— Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with heart failure. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.Background —B-type natriuretic peptide (BNP) has been associated with short- and long-term post-discharge prognosis among hospitalized heart failure (HF) patients. It is unknown if admission, discharge, or change from admission to discharge BNP measure is the most important predictor of long-term outcomes. Methods and Results —We linked patients ≥65 years from hospitals in OPTIMIZE-HF to Medicare claims. Among patients with recorded admission and discharge BNP, we compared Cox models predicting 1-year mortality and/or rehospitalization, including clinical variables and clinical variables plus BNP. We calculated the net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for the best-fit model for each outcome versus the model with clinical variables alone. Among 7039 patients in 220 hospitals, median (25th, 75th) admission and discharge BNP were 832 pg/mL (451, 1660) and 534 pg/mL (281, 1111). Observed 1-year mortality and 1-year mortality or rehospitalization rates were 35.2% and 79.4%. The discharge BNP model had the best performance and was the most important characteristic for predicting 1-year mortality (hazard ratio [HR] for log transformation 1.34; 95% CI 1.28-1.40) and 1-year death or rehospitalization (HR 1.15; 95% CI 1.12-1.18). Compared with a clinical variables only model, the discharge BNP model improved risk reclassification and discrimination in predicting each outcome (1-year mortality: NRI 5.5%, P<0.0001; IDI 0.023, P<0.0001; 1-year mortality or rehospitalization: NRI 4.2%, P<0.0001; IDI 0.010, P<0.0001). Conclusions —Discharge BNP best predicts 1-year mortality and/or rehospitalization among older patients hospitalized with HF. Discharge BNP plus clinical variables modestly improves risk classification and model discrimination for long-term outcomes.

National survey of hospital strategies to reduce heart failure readmissions findings from the get with the guidelines-heart failure registry

Background— Reducing 30-day heart failure readmission rates is a national priority. Yet, little is known about how hospitals address the problem and whether hospital-based processes of care are associated with reductions in readmission rates. Methods and Results— We surveyed 100 randomly selected hospitals participating in the Get With the Guidelines-Heart Failure quality improvement program regarding common processes of care aimed at reducing readmissions. We grouped processes into 3 domains (ie, inpatient care, discharge and transitional care, and general quality improvement) and scored hospitals on the basis of survey responses using processes selected a priori. We used linear regression to examine associations between these domain scores and 30-day risk-standardized readmission rates. Of the 100 participating sites, 28% were academic centers and 64% were community hospitals. The median readmission rate among participating sites (24.0%; 95% CI, 22.6%–25.7%) was comparable with the national average (24.6%; 23.5–25.9). Sites varied substantially in care processes used for inpatient care, education, discharge process, care transitions, and quality improvement. Overall, neither inpatient care nor general quality improvement domains were associated with 30-day readmission rates. Hospitals in the lowest readmission rate quartile had modestly higher discharge and transitional care domain scores ( P =0.03). Conclusions— A variety of strategies are used by hospitals in an attempt to improve 30-day readmission rates for patients hospitalized with heart failure. Although more complete discharge and transitional care processes may be modestly associated with lower 30-day readmission rates, most current strategies are not associated with lower readmission rates.Background—Reducing 30-day heart failure readmission rates is a national priority. Yet, little is known about how hospitals address the problem and whether hospital-based processes of care are associated with reductions in readmission rates. Methods and Results—We surveyed 100 randomly selected hospitals participating in the Get With the Guidelines-Heart Failure quality improvement program regarding common processes of care aimed at reducing readmissions. We grouped processes into 3 domains (ie, inpatient care, discharge and transitional care, and general quality improvement) and scored hospitals on the basis of survey responses using processes selected a priori. We used linear regression to examine associations between these domain scores and 30-day risk-standardized readmission rates. Of the 100 participating sites, 28% were academic centers and 64% were community hospitals. The median readmission rate among participating sites (24.0%; 95% CI, 22.6%–25.7%) was comparable with the national average (24.6%; 23.5–25.9). Sites varied substantially in care processes used for inpatient care, education, discharge process, care transitions, and quality improvement. Overall, neither inpatient care nor general quality improvement domains were associated with 30-day readmission rates. Hospitals in the lowest readmission rate quartile had modestly higher discharge and transitional care domain scores (P=0.03). Conclusions—A variety of strategies are used by hospitals in an attempt to improve 30-day readmission rates for patients hospitalized with heart failure. Although more complete discharge and transitional care processes may be modestly associated with lower 30-day readmission rates, most current strategies are not associated with lower readmission rates.

Markers of Decongestion, Dyspnea Relief, and Clinical Outcomes Among Patients Hospitalized With Acute Heart Failure

Background—Congestion is a primary driver of symptoms in patients with acute heart failure, and relief of congestion is a critical goal of therapy. Monitoring of response to therapy through the assessment of daily weights and net fluid loss is the current standard of care, yet the relationship between commonly used markers of decongestion and both patient reported symptom relief and clinical outcomes are unknown. Methods and Results—We performed a retrospective analysis of the randomized clinical trial, Diuretic Optimization Strategy Evaluation in Acute Heart Failure (DOSE-AHF), enrolling patients hospitalized with a diagnosis of acute decompensated heart failure. We assessed the relationship among 3 markers of decongestion at 72 hours—weight loss, net fluid loss, and percent reduction in serum N terminal B-type natriuretic peptide (NT-proBNP) level—and relief of symptoms as defined by the dyspnea visual analog scale area under the curve. We also determined the relationship between each marker of decongestion and 60-day clinical outcomes defined as time to death, first rehospitalization or emergency department visit. Mean age was 66 years, mean ejection fraction was 35%, and 27% had ejection fraction ≥50%. Of the 3 measures of decongestion assessed, only percent reduction in NT-proBNP was significantly associated with symptom relief (r=0.13; P=0.04). There was no correlation between either weight loss or net fluid loss and symptom relief, (r=0.04; P=0.54 and r=0.07; P=0.27, respectively). Favorable changes in each of the 3 markers of decongestion were associated with improvement in time to death, rehospitalization, or emergency department visit at 60 days (weight: hazard ratio, 0.91; 95% confidence interval, 0.85–0.97 per 4 lbs; weight lost; fluid hazard ratio, 0.94; 95% confidence interval, 0.90–0.99 per 1000 mL fluid loss; NT-proBNP hazard ratio, 0.95; 95% confidence interval, 0.91–0.99 per 10% reduction). These associations were unchanged after multivariable adjustment with the exception that percent reduction in NT-proBNP was no longer a significant predictor (hazard ratio, 0.97; 95% confidence interval, 0.93–1.02). The rates of death, HF hospitalization, or emergency department visit at 60 days for patients with 0, 1, 2, and 3 markers of decongestion (above the median) were 67%, 64%, 46%, and 38%, respectively (log rank P value=0.05).Figure. Relationship between number of markers of decongestion above median* and time to 60-day risk of emergency department (ED) visit, rehospitalization, or death. *Median net fluid loss, 3.8 L; median net weight loss, 6.5 lbs; median percent reduction in N terminal B-type natriuretic peptide 24.3%. Conclusions—Weight loss, fluid loss, and NT-proBNP reduction at 72 hours are poorly correlated with dyspnea relief. However, favorable improvements in each of the 3 markers were associated with improved clinical outcomes at 60 days. These data suggest the need for ongoing research to understand the relationships among symptom relief, congestion, and outcomes in patients with acute decompensated heart failure. Clinical Trial Registration—URL: http://www.clinicaltrials.gov. Unique identifier: NCT00577135.

Generalizability and longitudinal outcomes of a national heart failure clinical registry: Comparison of Acute Decompensated Heart Failure National Registry (ADHERE) and non-ADHERE Medicare beneficiaries

BACKGROUND Clinical registries are used increasingly to analyze quality and outcomes, but the generalizability of findings from registries is unclear. METHODS We linked data from the Acute Decompensated Heart Failure National Registry (ADHERE) to 100% fee-for-service Medicare claims data. We compared patient characteristics and inpatient mortality of linked and unlinked ADHERE hospitalizations; patient characteristics, readmission, and postdischarge mortality of linked ADHERE patients to a random 20% sample of Medicare beneficiaries hospitalized for heart failure; and characteristics of Medicare sites participating and not participating in ADHERE. RESULTS Among 135,667 ADHERE records for eligible patients ≥ 65 years, we matched 104,808 (77.3%) records to fee-for-service Medicare claims, representing 82,074 patients. Linked hospitalizations were more likely than unlinked hospitalizations to involve women and white patients; there were no meaningful differences in other patient characteristics. In-hospital mortality was identical for linked and unlinked hospitalizations. In Medicare, ADHERE patients had slightly lower unadjusted mortality (4.4% vs 4.9% in-hospital, 11.2% vs 12.2% at 30 days, 36.0% vs 38.3% at 1 year [P < .001]) and all-cause readmission (22.1% vs 23.7% at 30 days, 65.8% vs 67.9% at 1 year [P < .001]). After risk adjustment, modest but statistically significant differences remained. ADHERE hospitals were more likely than non-ADHERE hospitals to be teaching hospitals, have higher volumes of heart failure discharges, and offer advanced cardiac services. CONCLUSION Elderly patients in ADHERE are similar to Medicare beneficiaries hospitalized with heart failure. Differences related to selective enrollment in ADHERE hospitals and self-selection of participating hospitals are modest.

Transitions of Care in Heart Failure A Scientific Statement From the American Heart Association

In patients with heart failure (HF), use of 30-day rehospitalization as a healthcare metric and increased pressure to provide value-based care compel healthcare providers to improve efficiency and to use an integrated care approach. Transition programs are being used to achieve goals. Transition of care in the context of HF management refers to individual interventions and programs with multiple activities that are designed to improve shifts or transitions from one setting to the next, most often from hospital to home. As transitional care programs become the new normal for patients with chronic HF, it is important to understand the current state of the science of transitional care, as discussed in the available research literature. Of transitional care reports, there was much heterogeneity in research designs, methods, study aims, and program targets, or they were not well described. Often, programs used bundled interventions, making it difficult to discuss the efficiency and effectiveness of specific interventions. Thus, further HF transition care research is needed to ensure best practices related to economically and clinically effective and feasible transition interventions that can be broadly applicable. This statement provides an overview of the complexity of HF management and includes patient, hospital, and healthcare provider barriers to understanding end points that best reflect clinical benefits and to achieving optimal clinical outcomes. The statement describes transitional care interventions and outcomes and discusses implications and recommendations for research and clinical practice to enhance patient-centered outcomes.