Bunny
Bunny is an application developed by the University of Nottingham that enables privacy-preserving cohort discovery across federated health data networks. It is designed to work with OMOP Common Data Model (CDM) databases and is deployed at partner institutions as a secure, read-only query agent.
The code for Bunny is open source, and can be found on Github.
Core Functionality
Bunny processes two main types of cohort discovery queries:
- Availability: Answers the question “how many patients meet certain criteria?” without revealing individual-level data.
- Distribution: Returns de-identified aggregate statistics (e.g. age, sex, diagnosis counts) for a cohort of interest.
These queries are designed to protect privacy through configurable obfuscation techniques such as rounding and low-count suppression.
Use in Federated Research
Bunny is built to support federated research networks, where each site runs its own copy of Bunny locally. It polls a central Task API (such as Relay or RQUEST) to retrieve incoming tasks, processes them against the site’s OMOP database, and returns anonymized, aggregate results.
This model allows institutions to collaborate on large-scale health research without sharing raw patient-level data, maintaining data sovereignty and privacy.
Integration and Extensibility
Bunny integrates easily with orchestration platforms like RQUEST, allowing coordinated Availability and Distribution querying across multiple nodes. It’s well-suited for privacy-preserving record linkage and multi-site feasibility analysis.
Ideal Use Cases
- Cohort discovery for clinical trials or observational studies
- Feasibility assessments before launching multi-center research
Bunny is open-source, lightweight, and security-conscious, enabling ethical, scalable health research without compromising data control at the institutional level.