Brian Rasquinha
Associate Director, Solution Architecture, Privacy Analytics
Pragmatic Statistical De-Identification
Date of Event: May 7, 2025
Location: Washington, D.C.
Brian Rasquinha, Associate Director, Solution Architecture at Privacy Analytics, will be moderating a panel discussion on Pragmatic Statistical De-Identification. Guest panelists: Lauren Groebe, Associate General Counsel – Privacy, Cybersecurity & Digital, Baxter International, and John House, Executive Director, Science and Technology, Premier Applied Sciences.
Statistical approaches to de-identifying data, whether HIPAA’s Expert Determination method or other statistical assessments of identifiability, often form the core of an effort to manage identifiability. However, building a project, program, or business function around de-identification isn’t always straightforward. In this panel discussion, we’ll discuss experiences and lessons from standing up data de-identification initiatives from the contrasting perspectives of in-house legal, business leadership, and external privacy solution provider.
Discussion topics will include:
Brian draws on his expertise in privacy regulation and anonymization to determine what combination of Privacy Analytics’ services and software will best support the immediate and long-term needs of each of our clients. Successful implementation is Brian’s key focus, whether the client’s goal is to use sensitive data to improve service delivery, drive product development or grow revenue.
Brian Rasquinha
Associate Director, Solution Architecture, Privacy Analytics
Situation: California’s Consumer Privacy Act inspired Comcast to evolve the way in which they protect the privacy of customers who consent to share personal information with them.
Situation: Integrate.ai’s AI-powered tech helps clients improve their online experience by sharing signals about website visitor intent. They wanted to ensure privacy remained fully protected within the machine learning / AI context that produces these signals.
Situation: Novartis’ digital transformation in drug R&D drives their need to maximize value from vast stores of clinical study data for critical internal research enabled by their data42 platform.
Situation: CancerLinQ™, a subsidiary of American Society of Clinical Oncology, is a rapid learning healthcare system that helps oncologists aggregate and analyze data on cancer patients to improve care. To achieve this goal, they must de-identify patient data provided by subscribing practices across the U.S.
Situation: Needed to ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR.
Situation: Needed to enable AI-driven product innovation with a defensible governance program for the safe and responsible use
of voice-to-text data under Shrems II.
This course runs on the 2nd Wednesday of every month, at 11 a.m. ET (45 mins). Click the button to register and select the date that works best for you.