Brian Rasquinha
Associate Director, Solution Architecture, Privacy Analytics
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10 Best Practices for ROI on HIPAA Expert Determination
Healthcare organizations leverage HIPAA Expert Determinations to enable secondary uses of their patient-derived data. This helps them maximize the flexibility of their approach as well as the utility of their de-identified data. While much focus is placed on the specific statistical methods used, several non-technical factors can also impact the success of a data privacy initiative.
In this webinar, we’ll explore 10 non-technical best practices for HIPAA Expert Determination aimed at reducing timelines, rework, and costs while maximizing the organizational benefit from the data de-identification project. The right approach can ensure an Expert Determination is conducted smoothly and can best accommodate your organization’s evolving needs.
Join Brian Rasquinha, Associate Director of Solution Architecture at Privacy Analytics, for this discussion on approaches to help your organization learn how to get more out of their Expert Determination processes.
Key learnings:
Healthcare organizations leverage HIPAA Expert Determinations to enable secondary uses of their patient-derived data. This helps them maximize the flexibility of their approach as well as the utility of their de-identified data. While much focus is placed on the specific statistical methods used, several non-technical factors can also impact the success of a data privacy initiative.
In this webinar, we’ll explore 10 non-technical best practices for HIPAA Expert Determination aimed at reducing timelines, rework, and costs while maximizing the organizational benefit from the data de-identification project. The right approach can ensure an Expert Determination is conducted smoothly and can best accommodate your organization’s evolving needs.
Join Brian Rasquinha, Associate Director of Solution Architecture at Privacy Analytics, for this discussion on approaches to help your organization learn how to get more out of their Expert Determination processes.
Key learnings:
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.