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Guidelines recommend statin therapy for all patients with peripheral artery disease (PAD) due to the increased risk of adverse cardiovascular events. A lack of adherence to these guidelines was identified at a vascular clinic located in the southeastern United States. The aim of this nurse practitioner–led quality improvement project was to increase the percentage of patients with lower extremity PAD who were prescribed a statin medication at this clinic. Baseline data were obtained via a chart review. Using the Plan-Do-Study-Act (PDSA) model, a paper tool depicting an evidence-based algorithm was implemented in the clinic for 6 weeks to increase awareness of guidelines (PDSA cycle 1). Next, an electronic pop-up reminder was implemented in the electronic health record for the following 6 weeks (PDSA cycle 2). Data were collected throughout the process and analyzed to determine if either intervention increased the number of patients with PAD who were prescribed a statin medication. Baseline data revealed only 54.16% of patients were on a statin medication. After PDSA cycle 1, an average of 70.8% of patients were on a statin medication. PDSA cycle 2 revealed an average of 73.3% of patients were taking a statin medication. ANOVA was conducted and showed statistical significance between the groups (P = .003). There was statistical significance between baseline and implementation of the algorithm and baseline and implementation of the pop-up, but not between the 2 interventions. These findings are consistent with research suggesting algorithms and electronic reminders may increase medical staff awareness of guidelines. Standardization of these interventions enhanced provider adherence to guidelines and ultimately improved patient outcomes.

The Cancer Genomics Hub (CGHub) is the online repository of the sequencing programs of the National Cancer Institute (NCI), including The Cancer Genomics Atlas (TCGA), the Cancer Cell Line Encyclopedia (CCLE) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) projects, with data from 25 different types of cancer. The CGHub currently contains >1.4 PB of data, has grown at an average rate of 50 TB a month and serves >100 TB per week. The architecture of CGHub is designed to support bulk searching and downloading through a Web-accessible application programming interface, enforce patient genome confidentiality in data storage and transmission and optimize for efficiency in access and transfer. In this article, we describe the design of these three components, present performance results for our transfer protocol, GeneTorrent, and finally report on the growth of the system in terms of data stored and transferred, including estimated limits on the current architecture. Our experienced-based estimates suggest that centralizing storage and computational resources is more efficient than wide distribution across many satellite labs. Database URL: https://cghub.ucsc.edu.