Translating Data Into Action
The DCRI pushes beyond what’s most apparent. By tapping the experience of Duke faculty statisticians and the real-world insights of practicing physicians, we find the question that most effectively probes the challenge in your research and the fullest potential in data it generates. The result: meaningful decisions reached more quickly and efficiently, evidence that has more immediate impact on patient care and datasets with value beyond the immediate analyses.
View Insights from the Team
Where Do We Go From Here?
Utilizing rigorous, best-in-class tools and mathematical algorithms, our renowned biostatisticians and data scientists can tailor methods to the question. We find patterns within datasets that lead to stronger and more actionable insights. This approach of framing the right question to provide context and focus and applying optimal methods marks our work in:
- Clinical trial design and risk-based monitoring
- Independent data monitoring support
- Clinical trial statistics
- O2E: Program for Outcomes, Endpoints, and Estimands
- Comparative Effectiveness Research
- Center for Predictive Medicine
- Data sharing
Our Partners
Duke Margolis Center
Duke-Margolis brings together capabilities that generate and analyze evidence across the spectrum of policy to practice, supporting the triple aim of health care – improving the experience of care, the health of populations and reducing the per capita cost.
Duke Department of Population Health Sciences
The Duke Department of Population Health Sciences engages faculty members from a variety of disciplines — including epidemiology, health services research and policy, health economics, health measurement and behavior, and implementation science — who work to answer complex questions about the drivers of health in large populations.
Duke AI Health
Duke AI Health is Duke University’s center for artificial intelligence health research. Based at the Duke University School of Medicine, the center performs cutting-edge quantitative research, including foundational research, application development, technology infrastructure, and model assessment methodology.