Ventricular Assist Device (VAD) Infection Prevention Survey

Annually, more than 250,000 patients in the U.S. with end-stage heart failure stand to benefit from ventricular assist device (VAD) therapy. 60% of patients develop a healthcare-associated infection (HAI) within 90-days of implantation. The investigators long term goal is to develop and subsequently promote wide-scale adoption of evidence-based HAI prevention practices following durable VAD implantation. This will be done by addressing the following aims: Aim 1. Identify determinants of center-level variability in HAI rates. Aim 2. Develop a comprehensive understanding of barriers and facilitators for achieving low center HAI rates. Aim 3. Develop, iteratively enhance, and disseminate a best practices toolkit for preventing HAIs that accommodates various center contexts. The investigators will use a focused survey of U.S. VAD centers to identify determinants of center variation in 90-day HAI rates: * Process Factors (e.g., intranasal mupirocin), * Provider Factors (e.g., surgeon technique), * Device Factors (e.g., centrifugal vs. axial), * Center Factors (e.g., provider communication). Understanding the barriers and facilitators within individual centers for maximizing adoption of prevention measures would serve as the foundation for targeted improvement strategies. Without this knowledge, evidence-based, action-oriented recommendations will have limited local adoption and ultimately effectiveness in preventing HAIs after VAD implantation.

Annually, more than 250,000 patients in the U.S. with end-stage heart failure stand to benefit from ventricular assist device (VAD) therapy. Despite VADs providing long-term "durable" support, this therapy is associated with substantial risk (50% mortality at 4 years) and expense ($179,000 for inpatient services). Additionally, 60% of patients develop a healthcare-associated infection (HAI) within 90-days of implantation. Broad adoption of durable VAD therapy is hindered in part by HAIs, given associated sequelae (6-fold increased risk of 1-year mortality) and costs ($264,000 - $869,000 per patient). It is critical to determine how best to prevent HAIs in order to maximize the benefit of VAD therapy. While several studies have reported variation in HAI rates across centers after complex cardiac surgery, less is known in the setting of durable VADs. The average 90-day HAI rate after VAD implantation is as high as 19 events per 100 patient-months and varies (25th - 75th percentile, 9-23) across centers. While some argue that centers with lower HAI rates select healthier patients, others counter that improved practices (e.g., standardizing empirical and targeted antimicrobial therapy) or enhanced provider teamwork are more predictive of improved outcomes. While evidence-based HAI prevention guidelines and implementation tools (e.g., checklists) exist, these approaches are not comprehensive (e.g., neglecting device-specific determinants) or customizable to local context, thus limiting usability, adoption, and likelihood of significant effectiveness for preventing HAIs. Understanding the barriers and facilitators within individual centers for maximizing adoption of prevention measures would serve as the foundation for targeted improvement strategies. Without this knowledge, evidence-based, action-oriented recommendations will have limited local adoption and ultimately effectiveness in preventing HAIs after VAD implantation. The investigators long-term goal is to develop and subsequently promote wide-scale adoption of evidence-based HAI prevention practices following durable VAD implantation. The objective of this proposal is to identify prevention recommendations for the most significant HAIs after VAD implantation. To achieve this objective, the investigators will undertake a mixed methods study of adult patients receiving VADs in the U.S. from 2009 - 2017 and develop a modular toolkit of evidence-based recommendations. To determine best practices for preventing HAIs, the investigators will examine center-level differences in HAI rates to identify strategies used by centers with low rates, and potential barriers among centers with high rates.