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  • admin 9:52 am on July 1, 2016 Permalink
    Tags: , , , , , , Patients,   

    Roche: Doing Now What Patients Need Next with Data & Analytics 

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  • admin 9:54 am on June 29, 2016 Permalink
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    Roche Doing Now What Patients Need Next with Data and Analytics 

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  • admin 9:52 am on May 1, 2016 Permalink
    Tags: aider, entreprises, évaluer, , liés, mieux, Patients, , risques, s'associent, santé, secteur,   

    Teradata et Knowledgent s’associent pour aider les entreprises du secteur de la santé à mieux évaluer les risques liés aux patients 

    Teradata et Knowledgent s'associent pour aider les entreprises du secteur de la santé à mieux évaluer les risques liés aux patients



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  • admin 10:02 am on January 6, 2015 Permalink
    Tags: Clinic, , , Mayo, , , Patients, ,   

    Mayo Clinic Uses Big Data To Help More Patients, Save $Millions 

    As 2015 begins, we’re several weeks removed from the Teradata Partners Conference in Nashville, which has given me some time to digest all the great speakers and customer stories I encountered at the show. While there were lots of highlights, my favorite thing about Partners was simple: There were insightful sessions about big data for industries across the spectrum … yet you could learn something from each one regardless of your industry.

    A prime example was a session called “Innovating with Big Data to Improve Clinical Insight at Mayo Clinic,” which featured Nathan Spillers, data warehouse architect at Mayo Clinic, and Teradata’s big data architect Altan Khendup. It was one of the first sessions about big data for industries that I attended at the conference, and it definitely stuck with me afterwards.

    Spillers told a great story about how his team partnered with Teradata and Hortonworks to stand up a big data platform using a Teradata Appliance for Hadoop and develop an application with real, tangible impact on the Mayo Clinic’s operations … all in a mere six months.

    Let’s take a look at a few great lessons he touched on in his story — lessons about big data for industries like healthcare and beyond.

    1. Big Data Isn’t a Competition: As Spillers noted near the beginning of his presentation, more than a million people from all 50 states and nearly 150 countries go to Mayo Clinic for care. That’s a lot of people – which you may think means Mayo Clinic has the common problem of dealing with all that data. But Spillers was quick to point out that his story wasn’t about how big the data was. As he put it: “It’s not a competition!”

    Instead, the real problem with medical data is that it tends to be wide but not deep. As he explained: You go to a retail store frequently – maybe every day or even every other day – but you don’t go to your doctor nearly as frequently.

    This means that new data types – largely ones that are unstructured and streamed in real-time — are becoming increasingly important to add depth to the insights to ultimately improve patient care. This stuck with me, as the ability to handle unstructured and real-time data is undoubtedly a challenge being faced across industries.

    2. Data Discovery Shouldn’t Be the Only Goal: Another trend, as Spiller pointed out, is the emphasis on data discovery. As he put it: You throw your data into a lake and transform your industry! Great, right?

    Of course. But the problem – another one that resonates beyond healthcare – is that you can’t predict discovery … and Spiller needed to utilize Mayo Clinic’s data in a way that was measurable and predictable, and that could drive decisions. During Mayo Clinic’s project, discovery was a reduced to a “happy side effect” – a phrase I love. “We will enable discovery,” Spiller said, “but we aren’t going to center our initial plan on it.”

    This is an interesting point, because it’s easy to become enamored with the idea of data discovery. Mayo Clinic’s approach is a nice middle ground – they aren’t overlooking discovery by any means; they just chose to center their plan on a very specific goal. In this case, it was decreasing surgery preparation times in order to save millions of dollars per surgeon per year, allowing the doctors to see more patients … and allowing surgeons to impact more lives. That kind of focus was key – and in this case, it paid off.

    3. It’s Good to Have Friends: This last lesson comes straight from one of Spillers’ slides. See, getting to that end impact of improving lives sounds great, but it’s rarely easy. In the case of Mayo Clinic, their entire big data project was undertaken by a team of six … none of which were experts in new big data technologies at the beginning of the project. As Spiller explained, that made the support of Teradata and Hortonworks a huge asset throughout the six-month deployment. The consultants guided Mayo Clinic’s team as opposed to simply doing everything for them – a point Spiller emphasized.

    It’s the classic “You teach a man to fish” quote. No matter how you slice it, the key to big data success is empowering users to access data, build applications and unearth insights themselves. This is true whether you’re talking about healthcare patients, healthcare providers, or users in just about any industry!

    That’s the beauty of being data-driven: There’s no limit to the lessons you can learn and the insights gained. Intrigued by Data Discovery? Learn more with Data Discovery for Dummies!

    Rose Cintron Allen bio sized photoRose Cintron-Allen is the Practice Lead Healthcare Consultant for Teradata with over 30 years’ experience in the pharmacy management, health and life insurance industries. Rose’s expertise is in developing decision support solutions for the healthcare industry and helping organizations meet their business challenges through technology solutions.

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