The J. Lampe Lab at Fred Hutchinson Cancer Research Center currently uses a manual organizational model to manage thousands of samples that is prone to data loss and human errors. The lab is a part of the cancer prevention program and conducts multi-million dollar research studies that evaluate changes in human gut microbial composition from variations in diet or disease states. These studies necessitate an effective system that supports the tracking of these samples through various stages of analyses. We created the MED Project to address these limitations and provide complementary features that will increase process efficiency, in addition to retaining data integrity. The solution integrates an adaptive database system with a user interface designed for lab technicians to intuitively record and retrieve sample metrics. The database incorporates statistical automation, quality controls, and analytical reporting, while the front-end structures forms for accessible data input and manipulation. The implementation of this product provides the lab with a system that centralizes all studies and associated samples, accurately monitors assay processing, and automates time consuming, repetitive tasks.

Every year in the United States, an estimated 20-30% of patients with potentially fatal diseases are misdiagnosed. At the same time, integrating existing electronic medical records systems to gain a comprehensive understanding of patient medical trends is often complicated and time-consuming at best, delaying critical decisions necessary to patient care. Finally, in many cases patient clinical data continue to be entered and stored in error-prone spreadsheets. The Neutropenia Clinical Dashboard was developed to provide clinicians and staff at the Severe Chronic Neutropenia International Registry at UW Medicine the tools to accurately and efficiently analyze patient bone marrow, physical development, clinical event, and medication data, and in the process improve patient diagnosis and care.