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Schedule: Data Liquidity sessions

A look at activities that increase the availability and flow of patient data, including the role of foundations, governments, and NGOs in spurring data collection and sharing; data-driven population health, public health, and epidemiology; and the impact of HIPAA and patient privacy in the age of Facebook.

Salon G
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
Nathalie Holmes (Privacy Analytics, Inc.), Khaled El Emam (Children's Hospital of Eastern Ontario - Research Institute & University of Ottawa)
Average rating: ****.
(4.20, 5 ratings)
This session will look at the risks and opportunities facing organizations in this "Big Data" age. It will also discuss the requirements for protecting privacy, identify a de-identification maturity model that can be used to assist organizations in the process of either evaluating a new de-identification methodology or their existing methodology. Read more.
Salon H-K
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
Bob Evans (Google Inc)
Average rating: ****.
(4.75, 4 ratings)
Where is the app to track how often you eat homemade peanut butter cookies and correlates that with your sense of wellbeing? There will never be an app for that. There are a million things that quantified self-ers and behavioral scientists want to know about behavior. There is an app for that! Learn to quickly build your own mobile health experiments using Paco an opensource platform. Read more.
Salon G
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
Janos Hajagos (Stony Brook School of Medicine), Fred Trotter (FredTrotter.com)
Average rating: ***..
(3.50, 2 ratings)
It is assumed that social network analysis in healthcare is difficult. This assumption is wrong with the right tool and the DocGraph dataset. The goal of this tutorial is to allow participants to perform basic graph analysis of a healthcare dataset. After the tutorial participants should be able to use Gephi to generate novel hypotheses about the delivery of healthcare in Medicare. Read more.
Salon H-K
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
Ida Jooste (Internews)
Average rating: ***..
(3.75, 4 ratings)
Government and open data advocates expected the Kenya Open Data Initiative to jump-start a data-driven health policy debate. But the data dump didn’t account for the skills needed to catalyze the transformation of data into useful information. Explore how the database can be a robust public health tool with accelerated contribution, data literacy education and data-driven storytelling. Read more.
Salon F
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
John McDaniel (NetApp)
Average rating: **...
(2.40, 5 ratings)
The presentation will address big data, the next stage of meaningful use and its impending impacts on healthcare organizations. The ROI and promise big data represents, combined with the onset of a transformational shift in how care is administered across the healthcare delivery system, is forcing the healthcare industry to define big data and actualize its promise to improve patient outcomes. Read more.
Salon H-K
Workshop Please note: to attend, your registration must include Workshops on Wednesday.
Ann Waldo (Wittie, Letsche & Waldo, LLP), Roger Magoulas (O'Reilly Media)
Average rating: ****.
(4.40, 5 ratings)
Good news - The 563-page HITECH Final Rule liberalizes some research requirements. Bad news - the Rule also imposes new restrictions that will pose barriers to data-intensive research. No time to study it? Come to this session to learn about the practical effects of the new Rule on research and access to data. Read more.
Salon F
David Harlow (The Harlow Group LLC)
Average rating: **...
(2.50, 2 ratings)
Insights derived from "Big Data" analytics are based on the notion that a large store of patient data may be assembled and analyzed. Obtaining patient consent for such analysis can be cumbersome. In this session we will explore the range of rights ordinarily obtained by researchers, and the means of obtaining them. New approaches to patient consent will be considered as well. Read more.
Salon F
Craig Lipset (Pfizer)
The successful execution of a clinical trial requires collection of a significant amount of clinical data from research participants. At study end, little information is shared back with those participants. We will discuss the emergence of a new collaborative data sharing ecosystem with patients, beginning with research sponsors sharing results and data with the patients who enabled the study. Read more.
Salon H-K
Jeff Hammerbacher (Assistant Professor | Mount Sinai)
Average rating: **...
(2.50, 2 ratings)
Jeff will discuss how data is being used at the Icahn School of Medicine at Mount Sinai Read more.
Salon F
Khaled El Emam (Children's Hospital of Eastern Ontario - Research Institute & University of Ottawa)
Average rating: *****
(5.00, 1 rating)
We will present two case studies where we conducted an analysis of the privacy implications associated with sharing health data. We will look at the State of Louisiana and Mount Sinai School of Medicine Department of Preventative Medicine’s World Trade Center First Responder Registry how the de-identified data can be used to accelerate research and to provide open data for innovation. Read more.
Salon F
Richard Elmore (Allscripts)
Average rating: ****.
(4.00, 1 rating)
Barriers to exchange of personal health information create impediments to effective access and use of big data. Instead of compiling large datasets across health systems, what if population questions could be sent to the data? Read more.
Salon F
Peter Speyer (IHME)
Average rating: *****
(5.00, 1 rating)
The session will feature insights from an innovative study in Global Health that estimates the burden caused by 291 diseases and injuries globally and by country, age and gender. The session will make use of innovative interactive visualization tools to show study design and results. Read more.
Salon H-K
Our NIH-funded study hypothesizes that a new method of EHR data capture using Natural Language Processing (“NLP”) would improve EHR usability and documentation quality. With test subjects from various specialties, we compared the NLP-Based method against the standard EHR data capture method. Learn the surprising results of our study. Read more.
Provincetown
Marc Garrett (Intridea)
Quantify and visualize your team's health and productivity with R. Read more.
Salon F
Rachel Kalmar (Sensored)
Average rating: *****
(5.00, 4 ratings)
Health sensors are becoming ubiquitous, health tracking is in vogue, and given the rise of the maker, hardware, and crowdfunding movements, it is becoming increasingly easy to build a health sensor device. After focusing on the hardware, what do you need to know about handling data? This session will discuss issues about making data available, and why you should care. Read more.

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