- National Institutes of Health/National Center for Advancing Translational Sciences (NIH/NCATS)
- 5/1/2024
- Primary: Goal 2. Data Standards and Linkages for Longitudinal Research
- Secondary: Goal 4. Person-Centeredness, Inclusion, and Equity
STATUS: Active Project
BACKGROUND
Chronic kidney disease (CKD) affects more than 1 in 7 Americans, and more than 800,000 Americans are either on dialysis or have a kidney transplant. There are significant disparities in the prevalence of progression to end stage renal disease (ESRD) as Black people are nearly 4 times more likely to develop ESRD, and Hispanic and Native American people are more than twice as likely to progress to ESRD compared to White people. There are also disparities in treatment and outcomes and receipt of kidney transplantation with White people being more likely to receive a transplant by 5 years (63.2%), compared to Black, Hispanic, and Asian people (around 50%) and Native American people (around 40%).
Collaboration across HHS agencies is therefore critical for building comprehensive, high-quality data resources that capture patient trajectories from later stage (Stage 4,5) CKD and ESRD to renal transplantation. Previous efforts with Medicare and Medicaid data have been limited to claims data and costs of care; adding electronic health record (EHR) and registry data will capture many more events and enable better longitudinal tracking of individuals to support research, including comparative effectiveness research (CER) of CKD and ESRD treatments and patient-centered outcomes research (PCOR) studies; inform decision making; and improve patient outcomes for CKD, ESRD, and kidney transplantation.
The National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH) created the National COVID Cohort Collaborative (N3C), the nation’s largest open-science resource of real-world data (RWD) for COVID-19. Building on the success of N3C, NCATS initiated a series of pilots to assess the feasibility of leveraging the N3C infrastructure for other clinical disorders using a “tenant” model that is responsive to concerns that limit data aggregation and sharing within HHS agencies, including control of data, operation and maintenance of analytic environments, security and privacy issues, and cost control. This project leverages the findings from the N3C renal tenant pilot to develop and evaluate the N3C Renal Freeport. Freeport enclaves are virtual temporary analytic environments that can be deployed when needed to generate real world evidence (RWE) to address important clinical and policy questions; they provide a model for ensuring reliable and safe data sharing between agencies (as no single entity can capture all data) and stewardship of limited public health resources (e.g., avoiding duplicative efforts).