Meysam Safari

Meysam Safari,

Data Scientist

Meysam Safari works with Privacy Analytics’ clients to carry out risk analysis and develop risk measurement models for the anonymization of their datasets. He is part of a team of data scientists who specialize in privacy issues and topics to ensure our methodology and tools continue to lead the industry.

During his career, Meysam has dealt with a variety of datasets in healthcare as well as financial services, with clients from all over the world. Within healthcare, his experience has included insurance claim data, hospital records, longitudinal pharmacy records, EMR data from specialists, specialized pharmacy data and medical device data.

Meysam’s work has involved many complex projects that required linkage of data from multiple sources. He had to analyze re-identification risk and develop an anonymization strategy that was acceptable to all stakeholders.

Communication is key to execute on projects of this scale and complexity. Meysam always communicates closely with clients, to ensure he has a deep understanding of what utility their anonymized data must have. This is essential to strike that delicate balance between retaining as much analytical value as possible without compromising patient privacy.

Meysam has also worked on a number of projects that required a highly customized anonymization strategy. For example, he recently anonymized a dataset that included all Medicaid-related medical/dental records for the entire population of a U.S. state. The strategy adopted reflected the client’s analytical priorities and data utility needs.

“Among the fascinating things that I see at Privacy Analytics is its collegial culture of debate and discussion on methodology, tools and approaches,” Meysam says.  “This has led to continuous improvements in our methodology, tools, execution and deliverables.”

Archiving / Destroying

Are you unleashing the full value of data you retain?

Your Challenges

Do you need help...

OUR SOLUTION

Value Retention

Client Success

Client: Comcast

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.

Evaluating

Are you achieving intended outcomes from data?

Your Challenge

Do you need help...

OUR SOLUTION

Unbiased Results

Client Success

Client: Integrate.ai

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.

Accessing

Do the right people have the right data?

Your Challenges

Do you need help...

OUR SOLUTION

Usable and Reusable Data

Client Success

Client: Novartis

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.

 

Maintaining

Are you empowering people to safely leverage trusted data?

Your Challenges

Do you need help...

OUR SOLUTION

Security / compliance efficiency

CLIENT SUCCESS

Client: ASCO’s CancerLinQ

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.

 

Acquiring / Collecting

Are you acquiring the right data? Do you have appropriate consent?

Your Challenge

Do you need help...

OUR SOLUTIONS

Consent / Contracting strategy

Client Success

Client: IQVIA

Situation: Needed to ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR. 

 

Planning

Are You Effectively Planning for Success?

Your Challenges

Do you need help...

OUR SOLUTION

Build privacy in by design

Client Success

Client: Nuance

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.

 

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