IMPORTANCE Among adults with chronic illness, 30% to 50% of medications are not taken as prescribed. In the United States, it is estimated that medication nonadherence is associated with 125 000 deaths, 10% of hospitalizations, and $100 billion in health care services annually.

This study evaluates contemporary trends in the use and outcomes of adult patients undergoing extracorporeal membrane oxygenation (ECMO) in U.S. hospitals. All adult discharges in the Nationwide Inpatient Sample database during the years 2002-2012 that included ECMO were used to estimate the total number of U.S. ECMO hospitalizations (n = 12,407). Diagnostic codes were used to group patients by indication for ECMO use into postcardiotomy, heart transplant, lung transplant, cardiogenic shock, respiratory failure, and cardiopulmonary failure. A Mann-Kendall test was used to examine trends over time using standard statistical techniques for survey data. We found that ECMO use increased significantly from 2002-2012 (P = 0.003), whereas in-hospital mortality rate fluctuated without a significant difference in trend over time. No significant trend was observed in overall ECMO use from 2002-2007, but the use did demonstrate a statistically significant increase from 2007-2012 (P = 0.0028). The highest in-hospital mortality rates were found in the postcardiotomy (57.2%) and respiratory failure (59.2%) groups. Lung and heart transplant groups had the lowest in-hospital mortality rates (44.10% and 45.31%, respectively). The proportion of ECMO use for postcardiotomy decreased from 56.9% in 2002 to 37.9% in 2012 (P = 0.026) and increased for cardiopulmonary failure from 3.9% to 11.1% (P = 0.026). We concluded that ECMO use in the United States increased between 2002 and 2012, driven primarily by increase in national ECMO use beginning in 2007. Mortality rates remained high but stable during this time period. Though there were shifts in relative ECMO use among patient groups, absolute ECMO use increased for all indications over the study period. ECMO Use and Mortality for 2002-2012.

Objectives This study sought to determine how often patients with primary prevention implantable cardioverter-defibrillators (ICDs) meet guideline-derived indications at the time of generator replacement. Background Professional societies have developed guideline criteria for the appropriate implantation of an ICD for the primary prevention of sudden cardiac death. It is unknown whether patients continue to meet criteria when their devices need replacement for battery depletion. Methods We performed a retrospective chart review of patients undergoing replacement of primary prevention ICDs at 2 tertiary Veterans Affairs Medical Centers. Indications for continued ICD therapy at the time of generator replacement included a left ventricular ejection fraction (LVEF) ≤35% or receipt of appropriate device therapy. Results In our cohort of 231 patients, 59 (26%) no longer met guideline-driven indications for an ICD at the time of generator replacement. An additional 79 patients (34%) had not received any appropriate ICD therapies and had not undergone reassessment of their LVEF. Patients with an initial LVEF of 30% to 35% were less likely to meet indications for ICD therapy at the time of replacement (odds ratio: 0.52; 95% confidence interval: 0.30 to 0.88; p = 0.01). Patients without ICD indications subsequently received appropriate ICD therapies at a significantly lower rate than patients with indications (2.8% vs. 10.7% annually, p < 0.001). If ICD generator explantations were performed instead of replacements in the patients without ICD indications, the cost savings would be $1.6 million. Conclusions Approximately 25% of patients who receive primary prevention ICDs may no longer meet guideline indications for ICD use at the time of generator replacement, and these patients receive subsequent ICD therapies at a significantly lower rate.

Cardiovascular disease is the leading cause of death globally. While pharmacological advancements have improved the morbidity and mortality associated with cardiovascular disease, non-adherence to prescribed treatment remains a significant barrier to improved patient outcomes. A variety of strategies to improve medication adherence have been tested in clinical trials, and include the following categories: improving patient education, implementing medication reminders, testing cognitive behavioral interventions, reducing medication costs, utilizing healthcare team members, and streamlining medication dosing regimens. In this review, we describe specific trials within each of these categories and highlight the impact of each on medication adherence. We also examine ongoing trials and future lines of inquiry for improving medication adherence in patients with cardiovascular diseases.

Background: To improve value in the care of patients with acute myocardial infarction (AMI), payment models increasingly hold providers accountable for costs. As such, providers need tools to predict length of stay (LOS) during hospitalization and the likelihood of needing post-acute care facilities after discharge for AMI patients. We developed models to estimate risk for prolonged LOS and post-acute care for AMI patients at time of hospital admission to facilitate coordinated care planning. Methods and Results: We identified patients in the NCDR ACTION registry who were discharged alive after hospitalization for AMI between July 1, 2008 and March 31, 2017. Within a 70% random sample (Training cohort) we developed hierarchical, proportional odds models to predict length of stay and hierarchical logistic regression models to predict discharge to a skilled nursing facility. Models were validated in the remaining 30%. Of 633,737 patients in the training cohort, 16.8% had a prolonged LOS (7+ days) and 7.8% were discharged to a post-acute facility (extended care, a transitional care unit, or rehabilitation). Model discrimination was moderate in the validation dataset for predicting LOS (C statistic = 0.640) and strong for predicting discharge to a skilled nursing facility (C statistic = 0.827). For both models, discrimination was similar in STEMI and NSTEMI subgroups and calibration was excellent. Conclusions: These models developed in a national registry can be used at the time of initial hospitalization to predict LOS and discharge to post-acute facilities. Prospective testing of these models is needed to establish how they can improve care coordination and lower costs.