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Best Practices for Mining Big Data: Legal, Regulatory and Ethical Considerations
 
Best Practices for Mining Big Data: Legal, Regulatory and Ethical Considerations
A myriad of legal, regulatory and ethical considerations must be addressed in order for healthcare stakeholders to properly leverage Big Data in healthcare, and adopt best practices in data mining.

Big Data involves powerful and often surprisingly granular information that can be assembled about individuals based on analysis of enormous databases, and typically refers to the application of emerging techniques in data analytics, such as machine learning and other artificial intelligence tools, to those enormous databases of personal information. Sources of Big Data often include smartphone GPS data; web browsing data; social networking activity and biometric data.

Projects using Big Data can transform healthcare delivery, because providers are better able to assess acute cases in an entire population. As well, they can develop new ways to identify and prevent illness. But peril looms. Retail Big Data analysis, doesn’t usually have to be conducted within the parameters of rigorous industry-specific privacy laws and regulations. Not so with healthcare, which must operate under the Health Insurance Portability and Accountability Act, among other statutes. And in fact, key principles of privacy regulations are ill-suited to Big Data.

Please Join Morgan Lewis's Reece Hirsch on Wednesday, October 7th, 2015 from 1PM until 2PM Eastern, during this HealthcareWebSummit event as he discusses Best Practices for Mining Big Data: Legal, Regulatory and Ethical Considerations.  Click here for detailed information and to register or call 209.577.4888.

Package Registration: $295. Register for this event, and the October 13th event,
Consumer Lifestyle and Behavioral Analytics: Leveraging Supplemental Data for Risk Intervention and More, and receive a package registration price of $295 for both events combined - with a savings of $95 (about 25%).
 
Register Now
 

  

  

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