Data and Analytics

Location: Plaza Room A
Shahid Shah (Netspective)
Average rating: ****.
(4.67, 6 ratings)
We all intuitively understand that the usage of data in healthcare should improve quality, reduce cost, and hopefully affect outcomes of research and end end in better care. However, many of our best sources of data like EHRs and other health IT systems do a poor job of data integration. This talk will outline the reasons for poor integration today and what we can do about it. Read more.
Location: Plaza Room A
Moderated by:
Darren Hite (Aberdare Ventures)
Panelists:
Kuang Chen (Captricity), Mohit Kaushal (West Health), Kyna Fong (ElationEMR), Geoffrey Nudd (ClearCare)
Average rating: *....
(1.00, 3 ratings)
The goal of this panel is to bring health and tech perspectives together for a deep dive into the ever-present problem of data stuck on paper forms. We’ll hear four panelists, representing payers, strategists, healthcare technology VCs, and health-oriented startups, give their perspectives on the persistence of paper and the value of extracting health data from paper forms. Read more.
Location: Grand Ballroom B
Niall Brennan (Center for Strategic Planning, Centers for Medicare and Medicaid Services)
Average rating: ***..
(3.00, 1 rating)
Session by Niall Brennan, Director for the Policy and Data Analysis Group, Center for Strategic Planning at the Centers for Medicare and Medicaid Services. Read more.
Location: Plaza Room A
Brian Bot (Sage Bionetworks), Erich Huang (Sage Bionetworks)
Average rating: *****
(5.00, 1 rating)
Data-intensive scientific communication is broken. Ironically, the components necessary for open and executable science exist in isolation. clearScience is a pilot at Sage Bionetworks to assemble these components—data, code, and compute infrastructure into a stack that not only facilitates effective reporting of science, but delivery of the science itself. Read more.
Location: Grand Ballroom B
Pek Lum (Ayasdi)
Gleaning insights from massive and complex datasets from clinical trials can be challenging. You usually have to know the right questions to ask before you can begin to find answers. With Ayasdi’s Iris solution, you can visualize entire datasets and unearth powerful insights in seconds--answering the questions that you didn’t know to ask. Read more.
Location: Plaza Room A
Christos Tryfonas (VMware), Karthik Kannan (Cetas by VMware)
Average rating: **...
(2.00, 1 rating)
Hospitals, healthcare providers & insurance companies have traditionally been using standard statistical & Bayesian approaches for data modeling and predictive analytics. But these approaches fall short in the light of the very large volume, variety and velocity of Big Data. In this session, we talk about machine learning & combinatorial algorithms that can enable personalized recommendations. Read more.
Location: Plaza Room A
Ari Gesher (Palantir Technologies), Lauren Chaparro (Palantir Technologies)
Average rating: *****
(5.00, 2 ratings)
As healthcare organizations gain access to more data, they rely increasingly on complex systems and predictive tools. This has led to a divide between technical analysts and decision-makers. We will live demo a system that bridges this gap using an integrated set of big-data technologies mated with an interactive GUI. This demo uses 10 years of Medicare claims consisting of 1.2 billion records. Read more.
Location: Plaza Room A
Allen Kamer (Humedica)
This talk will discuss the use of aggregated, longitudinal EHR databases, predictive data analytics and data visualization as a key success factor in the transformation of healthcare and the ACO strategic initiative. Read more.
Location: Grand Ballroom B
Moderated by:
Roger Magoulas (O'Reilly Media)
Panelists:
Jacomo Corbo (QuantumBlack), Colin Hill (GNS Healthcare), Nathan Wolfe (Metabiota, Global Viral)
Average rating: ***..
(3.50, 4 ratings)
A discussion of how leading health researchers analyze various kinds of health data to affect real-world outcomes - from hunting for new virus strains in remote areas of Africa, to using advanced machine learning to determine treatment efficacy and build predictive models. Read more.
Location: Plaza Room A
Scott Nicholson (on the loose)
Average rating: ****.
(4.00, 1 rating)
It is clear that data are core to solving big problems in health care, and data science is the skill set needed to extract insights and make them actionable. Using lessons from experience from LinkedIn & online advertising and a large dataset of clinical and claims data, we will discuss results from efforts to increase the quality of care, decrease cost, and increase hospital efficiency. Read more.
Location: Plaza Room A
Bruce Church (GNS Healthcare), Greg Steinberg (Aetna)
Metabolic Syndrome, MetS, is a huge and growing health burden, whether we’re talking about burdens that are clinical or economic, societal or individual. GNS and Aetna have partnered to develop Big Data analytics solutions to identify and characterize both those with MetS and at risk for MetS. We will share results and discuss insights and challenges in working with real-world data. Read more.
Location: Plaza Room B
John Kansky (Indiana Health Information Exchange, Inc.)
Average rating: *****
(5.00, 1 rating)
Health Information Exchanges are already helping to make a difference in the healthcare delivery system, however the best is yet to come. The next generation of Health Information Exchange innovations will dramatically improve the quality, efficiency and cost of healthcare around the country. Read more.

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