Strata Rx 2013: Khaled El Emam: Facilitating Analytics while Protecting Individual Privacy using Data De-identification

Thursday, September 26, 2013

Facilitating Analytics while Protecting Individual Privacy using Data De-identification

Join Khaled El Emam, a world-renowned expert in statistical de-identification and re-identification risk, and one of only a handful of individual experts in North America known to be qualified to certify the anonymization of Protected Health Information (PHI) under the HIPAA Privacy Rule.

In this session Khaled will present two case studies where he conducted an analysis of the privacy implications associated with sharing health data. In the case of Mount Sinai the information is to be shared with other analysts, and in the case of the State of Louisiana with the public.

Khaled will discuss the methodology used to de-identify this health data in a defensible way according to HIPAA standards, and produce the high utility data that can accelerate research to provide open, de-identified data for innovation.

State of Louisiana Case Study

It is no secret that the State of Louisiana has some of the worst health outcomes in the United States since United Health Foundation started ranking states in 1990 in its America’s Health Rankings list.

Recognizing that the health of its citizens is of paramount concern, and that poor health outcomes have an adverse impact on virtually every aspect of life in the State, Louisiana has set a target to raise its health ranking to thirty-fifth within the next ten years.

One of the most important factors in being able to meet this aggressive target is the State’s decision to leverage available innovative technology solutions and analytics. An example of the State’s novel approach was its participation in Cajun Code Fest 2013, which focused on de-identified Medicaid claims and Immunization registries.

The Cajun Code Fest is the signature event for the Center for Business & Information Technologies (CBIT) at the University of Louisiana at Lafayette (UL Lafayette). The event focused on a 27-hour coding competition that provided participants with the opportunity to transform “data” into healthcare solutions.

This year, the data released was used to create solutions that encourage patients to “Own Your Own Health,” and to make knowledgeable and informed decisions about their healthcare. Having access to realistic, yet de-identified data, was the only way this competition could be successful.

Mount Sinai School of Medicine Department of Preventive Medicine: The World Trade Center First Responder Registry Case Study

The World Trade Center Health Program, Clinical Center of Excellence (WTCHP), is a registry that was established to collect health and social information about more than 27,000 of the 9/11 first responders. It has been operating now for more than a decade.

This is highly sensitive and valuable information, and can be used to understand the longitudinal physical and mental health, as well as social effects, experienced by first responders on and after 9/11.

The ability to rapidly analyze this data can help identify important interventions of value to these individuals.

From this talk you will:

  • Understand what the HIPAA Privacy Rule de-identification standards are and how they can be operationalized.
  • Learn through case studies how data sets can be de-identified and disclosed, while retaining significant utility.
  • Develop a critical understanding of the different approaches to de-identification.
  • Learn about the specific risk assessment and de-identification techniques that were used on the first responder registry, and the de-identification of data sets used in preparation of the Cajun Code Fest 2013 coding competition.


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