Northwest Kidney Centers (NWK) is one of the nation’s leading nonprofit dialysis providers, serving thousands of patients and maintaining decades of clinical data. Despite the richness of this data, it remains siloed, inconsistently formatted, and difficult to leverage for continuous quality improvement (QI).

Currently, NWK tracks multiple quality indicators—such as infection rates, hospitalizations, transfusions, vaccinations, and anemia—but the organization lacks a repeatable process for integrating, analyzing, and reporting on these metrics. This hampers the ability of clinical and operational teams to proactively identify trends, intervene early, and measure the effectiveness of corrective actions over time.

This project offers students the opportunity to build a foundational, scalable analytics framework to transform NWK’s quality data into actionable insights. By cleaning and modeling decades of historical data, centralizing it in a usable database, and building predictive reporting workflows, students will help NWK shift from retrospective reporting to proactive quality management. The outcome will be a critical tool that strengthens clinical decision-making, improves patient outcomes, and supports NWK’s mission to deliver exceptional kidney care.

Audit Current Data Ecosystem

Design Data Architecture & Pipeline

Develop Predictive and Descriptive Analytics

Build Reporting Framework

Document Processes and Train Staff

Establish a centralized, clean, and validated dataset covering at least 10 years of historical quality data by the end of the first semester.

Achieve >90% accuracy in predictive models when back-tested on historical data by mid-project.

Deliver an automated, repeatable monthly reporting system to NWK’s leadership by project conclusion.

Enable real-time access to visualized trends and forecasts through user-friendly dashboards.

Produce a fully documented analytics pipeline and SOPs that NWK can maintain and scale internally.