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.
Optum Labs was established with Mayo Clinic to enable cross-industry collaborative research and innovation to improve patient care. With other partners from across healthcare, Optum Labs will be a unique environment with the data, tools, and infrastructure necessary for leading scientists and innovators to tackle the thorniest problems in healthcare and to bridge this research into the clinic.
Necessity is the mother of invention. This keynote will describe an example of how some of the founding members of Aetna Innovation Labs were able to weave together clinical insights and ideas from the future with both existing and emerging technologies, accelerate ideas into reality, and hopefully share some inspiration for doctors, patients, and the health data & innovation community.
SAP in collaboration with leading medical research institutions in genomics, cancer research centers and care providers has achieved breakthrough results in healthcare data processing using SAP HANA.
This session will provide you with the basic knowledge required to navigate through the sea of jargon that is “Big Data”. We'll survey the technologies used in the space and show examples that will illustrate how these technologies can solve real world healthcare problems. At the end of this session you will be able to “talk the talk” that is Big Data.
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.
In Blind Spot, Carol will talk about what’s the most important data in a Big Data world, why it’s not what we think, and give an example of how we’re still blind to ways it can make a real difference in people’s health.
Over the past three years the health data ecosystem has grown at an unprecedented rate. Bryan Sivak, Chief Technology Officer and Entrepreneur in Residence at the Department of Health and Human Services, will discuss how we got to this point, what steps the federal government is taking to incentivize the utilization of health data, and upcoming opportunities for...
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.
DrBonnie360 will lead a discussion of how new digital tools using data, social media, mobility and games can help patients change behavior. She will introduce the emerging ecosystem of companies across the disease spectrum in the mobile/social/data arena. 3 panelists will provide patient stories, statistics and professional experience describing what works and what doesn’t.
Data relevant to health are now increasingly found outside of traditional health care settings. Examples include the troves of data gathered by members of the Quantified Self movement to transactional data for health-related consumer goods and services. This presentation will introduce a new Robert Wood Johnson Foundation initiative to open up these data to researchers to gain new insights on...
At Pivotal, it is the goal of our data science practice to demonstrate the capabilities of the technologies we offer. In our talk we will focus on a use case in pharmaceutical manufacturing, wherein we created a predictive model to produce more consistent, high-quality products and drive decisions to abandon lots with expected poor outcomes.
Learn how Emdeon and Atigeo collaborated to create a patient health record composed of historical medical, pharmacy and e-prescription information across healthcare providers (using tens-of-terabytes of claims data). See how they developed and trained a data driven statistical model for assessing and lowering the risk of hospital readmission at the point of check-in and each day after discharge.
As we move to a more accountable model of care, can we aim our sights even higher than the promise of reduced cost, improved patient experience of care, and improved health of populations, and deliver a more dignified experience for patients, caregivers, doctors, nurse practitioners, administrators, and everyone who wants to help humans feel well?
Adindu Uzoma, CEO, FlowLogic
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.
In health care data driven results are all the rage. The most innovative companies today use data to effect outcomes and simplify systems. But patient focus has largely been left out of the equation. This is about emotional design and how to create patient focused healthcare platforms where data is not the driver of decision, but a validator of emotional decisions that have already been made.
Khaled El Emam
(Children's Hospital of Eastern Ontario - Research Institute & University of Ottawa)
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.
Join Aneesh Chopra, first CTO of the United States, and John Halamka, Harvard Medical School Professor and CIO of Beth Isreal Deaconess Medical Center for a fireside chat.
Developers struggle to integrate clinical apps with today's EHR systems. SMART Platforms has built an open-source tool that exposes a lightweight RESTful API on top of Meaningful Use standards. In this session we'll dig into the challenges of working with patient-level health data, framing solutions with a case study (and live demo) of SMART's Pediatric Growth Chart app.
This presentation will discuss a real life case study and data using large scale graph analysis. The example uses 4 billion relationships between 270 million identities and looks at the social spread of prescription drug abuse and the insights that are gained from this perspective. We will show how those insights are leveraged to disrupt social crime networks and affect health outcomes.
In this presentation, Tom Davenport will discuss both the need for integration and some of the most feasible approaches to achieving it. He'll provide examples--a few, anyway--of how integration has already allowed some providers and payers to achieve substantial value.
EHR and gene sequencing solutions are generating massive volumes of data, creating new opportunities for innovative analytics and global collaboration. High-performance and cloud computing platforms are accelerating sophisticated genomic data analysis in the first FDA-approved personalized medicine clinical trial for pediatric cancer, and reducing the compute time from several days to a few hours.
This session will provide an overview and discussion for developers of how to adhere to HIPAA guidelines while building a cloud-based application that handles Protected Health Information. There are very few publicly available resources for developers of cloud-based healthcare apps, so we will directly tackle the issues developers encounter when trying to launch an application in the cloud.
This workshop is designed for managers and leaders working in healthcare (HC) interested in demystifying the big data and analytics hype to discover how data can drive real and meaningful organizational changes. Participants will learn how to prioritize objectives and use a project-based approach to achieve real success in manageable increments.
(Brigham and Women’s Hospital, Division of Pharmacoepidemiology and Pharmacoeconomics )
Dr. Sebastian Schneeweiss, Harvard Medical School and Brigham and Women’s Hospital, will discuss how analytic capabilities for big data, based on principles of causal inference, are currently being used in his organization to make a big impact in drug safety and effectiveness. He is also Co-chair of the FDA’s Mini-Sentinel methods program, a post-market medical product safety assessment program.
Fred Trotter, Data Journalist, DocGraph.org and FredTrotter.com.
Opening remarks by Strata Rx program chairs, Julie Steele of O'Reilly Media, Inc. and Colin Hill of GNS Healthcare.
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.
(Office of the National Coordinator for Health IT)
More than 80 million Americans can now "blue button" their digital health data. This figure will expand rapidly in 2014 as every certified health record system--and every provider and hospital participating in meaningful use--will give patients the ability to view, download and share their own machine-grade health information. Data liquidity for patients will create new.....
The quantified self and mHealth movements are inadequate to serve the population of individuals who require medically supervised help to improve their health. Farsite and Ohio State University are developing data-driven behavioral interventions that draw upon the patient’s existing social network in order to improve adherence to cardiac rehabilitation programs and decrease hospital re-admissions.
Better outcomes and cost-containment are two urgent public health concerns and unified information is the Rx.Explore how some are transforming the healthcare industry as they unify everything from doctors’ scribbles, providers’ claims and patient charts onto one platform. What are the challenges of interoperability, the benefits of adding intelligence, the distinctions between search and querying.
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?
The modern web is built on service-oriented architecture and web-oriented architecture. However, our data architectures haven't kept up and are still very application oriented and monolithic in nature. Join IT expert Shahid Shah talk about how to create service oriented databases for healthcare, patient engagement, and biomedical purposes.
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.
The winners of the Strata Rx Startup Showcase are announced.
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.
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.
McKinsey and BeyondCore analyzed 30M+ claims lives to predict the patients most likely to experience increases in healthcare costs. Best predictors of increases involve multiple variables such as: 50 year old patients with depression who have been discharged from a heart procedure. We used Big Data analytics to automatically evaluate a million variable combinations to reveal actionable patterns.
A plea to break down data siloes and create a truly open market for health information exchange.
There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations have been well described. The nascent field of translational bioinformatics may help, especially powered by public big data.