Using advanced methods to analyze patient data while protecting privacy
Decentralized differentially-private methods for dynamic data release and analysis
This study is working on new ways for hospitals to use patient data to better understand and treat chronic diseases while keeping your personal information safe and private.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project ID | NIH-11003369 on NIH RePORTER |
What this research studies
This research focuses on developing innovative algorithms that allow healthcare institutions to analyze large datasets without compromising patient privacy. By keeping data at each healthcare center and using decentralized methods, the project aims to enhance the accuracy of predictive analytics tools for chronic diseases. Patients' data will be utilized to improve understanding and treatment of conditions while ensuring their information remains secure and confidential. The approach addresses concerns about data sharing and consent, making it easier for institutions to contribute valuable insights.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals with chronic diseases who are receiving care at participating healthcare institutions.
Not a fit: Patients with acute conditions or those not receiving care at the participating institutions may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved predictive tools that enhance patient care and outcomes for chronic diseases.
How similar studies have performed: Previous research has shown promise in using decentralized methods for data analysis, indicating potential for success in this approach.
Where this research is happening
New Haven, United States
- Yale University — New Haven, United States (Active)
Researchers
- Principal investigator: Ohno-Machado, Lucila — Yale University
- Study coordinator: Ohno-Machado, Lucila
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.