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Background Despite improvements on individual process of care measures for acute myocardial infarction (AMI), little is known about performance on a composite measure of AMI care that assesses the delivery of many components of high-quality AMI care. We sought to examine trends in patient- and hospital-level performance on a composite defect-free care measure, identify disparities in the performance across sociodemographic groups, and identify opportunities to further improve quality and outcomes. Methods and Results We calculated the proportion of patients in the National Cardiovascular Data Registry-Acute Coronary Treatment and Intervention Outcomes Network Registry-Get With The Guidelines (now known as the Chest Pain - Myocardial Infarction Registry) between January 1, 2010, and December 31, 2017, receiving defect-free AMI care including guideline-recommended pharmacotherapy, timely provision of medical and reperfusion therapy, assessment of ventricular function, referral to cardiac rehabilitation, and smoking cessation counseling for patients with AMI. A total of 522 800 patients at 222 hospitals were included. Overall, the proportion of patients receiving defect-free care significantly increased from 66.0% in 2010 to 77.1% in 2017 ( P0.001). Improvements in performance were observed across all sociodemographic subgroups, with the greatest absolute improvement observed for black and Hispanic patients ( P0.001). However, absolute performance was consistently lower among older patients, women, black and Hispanic patients, and those with government insurance in 2017 ( P0.001 for all). Improvements in care and reduced variation in performance were observed at the hospital level overall (2010, median [IQR] 67.2% [40.7%-76.3%]; 2017, median [IQR] 80.7% [73.1%-88.1%]; P0.001) as well as across region, safety net status, teaching status, and proportion of patients who are nonwhite and have Medicaid insurance coverage ( P0.001 for all). Conclusions Despite improvements in the proportion of patients with AMI receiving defect-free care overall and across sociodemographic groups, nearly 1 in 4 patients in 2017 still did not receive optimal care and absolute performance was consistently lower among older patients, women, black, and Hispanic patients. Composite measures of cardiovascular care, which assess the delivery of several evidence-based processes of care, can illuminate opportunities to improve the quality of care beyond that provided by conventional process measures.

Background— The current ability to predict readmissions in patients with heart failure is modest at best. It is unclear whether machine learning techniques that address higher dimensional, nonlinear relationships among variables would enhance prediction. We sought to compare the effectiveness of several machine learning algorithms for predicting readmissions. Methods and Results— Using data from the Telemonitoring to Improve Heart Failure Outcomes trial, we compared the effectiveness of random forests, boosting, random forests combined hierarchically with support vector machines or logistic regression (LR), and Poisson regression against traditional LR to predict 30- and 180-day all-cause readmissions and readmissions because of heart failure. We randomly selected 50% of patients for a derivation set, and a validation set comprised the remaining patients, validated using 100 bootstrapped iterations. We compared C statistics for discrimination and distributions of observed outcomes in risk deciles for predictive range. In 30-day all-cause readmission prediction, the best performing machine learning model, random forests, provided a 17.8% improvement over LR (mean C statistics, 0.628 and 0.533, respectively). For readmissions because of heart failure, boosting improved the C statistic by 24.9% over LR (mean C statistic 0.678 and 0.543, respectively). For 30-day all-cause readmission, the observed readmission rates in the lowest and highest deciles of predicted risk with random forests (7.8% and 26.2%, respectively) showed a much wider separation than LR (14.2% and 16.4%, respectively). Conclusions— Machine learning methods improved the prediction of readmission after hospitalization for heart failure compared with LR and provided the greatest predictive range in observed readmission rates.

Each year in the United States, approximately 800 000 men and women are affected by stroke, which equates to one incident of stroke every 40 seconds.1 Stroke is the fourth leading cause of death nationally and is one of the foremost contributors to functional disability.2 The cost to the US healthcare system is substantial. Specifically, in 2010 medical treatment for stroke cost approximately $54 billion and is expected to exceed $1 trillion by 2050.3 The burden of stroke is not limited to US alone; mortality from stroke is responsible for ~9% of all deaths worldwide and is the second most common cause of death following ischemic heart disease.4 While the overall risk of stroke has declined by 25% in the last decade,5 disability from stroke is now emerging as a major public health problem, particularly in the elderly, as we observe an increase in aging of the population. Accordingly, in this month’s topic review in Circulation: Cardiovascular Quality and Outcomes , we concentrate on contemporary issues around stroke and transient ischemic attack (TIA). Significant knowledge and practice gaps continue to exist across the continuum of stroke care. First, risk factor modification for stoke remains suboptimal. The most important modifiable risk factor for prevention of stroke is hypertension (HTN), with the lowering of blood pressure associated with a more than 25% reduction in the relative risk (RR) of stroke.6,7 Modification of other risk factors such as diabetes, hypercholesterolemia, smoking cessation and atrial fibrillation (AF),8 have also been shown to reduce the incidence of stroke.9 However, appropriate identification of patients at risk and ensuring adherence to prevention strategies presents many challenges. For example, numerous patients with HTN are not on therapy and many of those who are treated have suboptimal blood pressure …

The following are highlights from the new series, Circulation: Cardiovascular Quality and Outcomes Topic Review. This series will summarize the most important manuscripts, as selected by the Editor, that have been published in the Circulation portfolio. The objective of this series is to provide our readership with a timely, comprehensive selection of important papers that are relevant to the quality and outcomes, and general cardiology audience. The studies included in this article represent the most significant research related to treatment of stable coronary artery disease (CAD).

The following are highlights from the new series, Circulation: Cardiovascular Quality and Outcomes Topic Reviews. This series will summarize the most important manuscripts, as selected by the Editor, which have been published in the Circulation portfolio. The objective of this new series is to provide our readership with a timely, comprehensive selection of important papers that are relevant to the quality and outcomes as well as general cardiology audience. The studies included in this article represent the most significant research in the area of valvular heart disease. ( Circ Cardiovasc Quality and Outcomes . 2012;5:-e103.) In recent years, no field of clinical cardiology has experienced a great influx of transformational therapeutic options as has the area of valvular heart disease. Treatment of severe aortic stenosis (AS) has been revolutionized by transcatheter aortic valve replacement (TAVR), which has been shown to improve life expectancy and functional outcomes in patients with inoperable AS1,2 and to have short-term outcomes comparable to surgical aortic valve replacement (AVR) in patients at high perioperative risk.3,4 Analogously, mitral valve disease has been amenable to percutaneous valve replacement,5,6 as well as clipping procedures7 that can substantively reduce severe mitral regurgitation (MR) and improve functional outcomes. Even right-sided heart disease involving valves in pulmonary8,9 and tricuspid10 positions has been treated successfully with endovascular techniques. Yet, even with this growing focus on percutaneous valvular interventions, open surgical techniques remain the dominant treatment strategies and standard of care for most advanced lesions. Surgical valve repair and replacement account for 10% to 20% of all cardiac surgical procedures,11–13 approximately two thirds of which are for AS.11–13 For patients undergoing surgery, there remains considerable debate about risk stratification,14 intraoperative technique,15 and postoperative …

The following are highlights from the new series, Circulation: Cardiovascular Quality and Outcomes Topic Review. This series will summarize the most important manuscripts, as selected by the Editor, that have been published in the Circulation portfolio. The objective of this new series is to provide our readership with a timely, comprehensive selection of important papers that are relevant to the quality and outcomes, and general cardiology audience. The studies included in this article represent the most significant research in the area of anticoagulation for cardiovascular disease.