Big Data, Big Hairy Problems – Bring ‘Em On!

New Blog Post:  Simon Arkell, CEO, Predixion Software

A couple of weeks ago I was honored to participate in the Accenture “Journey to Analytics ROI” panel in San Francisco.  To say that I was enamored with the location, organization and quality of attendees is an understatement.  You see we have been working with Accenture for much of the last 12 months and, most recently, in addition to inviting Predixion Software to be a global alliance partner, Accenture led our most recent round of funding as a company alongside GE.  Having an organization with the size and reputation of Accenture as a key investor and strategic partner is a massive accelerator for Predixion as a 4 year old company, and the experience of actually participating in an Accenture event such as this is great for business and the industry.  Our space is topical, exciting, intriguing challenging and competitive!

During the Accenture panel it became obvious to most of us that big data is upon us and the industry has to do a better job of making predictive analytics more accessible to the average business user.  Much of the content of the panel was centered around this and many of the questions were big data centric.  From capturing data, to making sense of it and making it actionable, it is clear, that these topics are on most peoples’ minds.

To me, big data is an amorphous topic that can mean so many things.  What is clear is that the age of big data and analytics is well and truly upon us and we are just scratching the surface.  In the “Kitty Hawk Days of Big Data” enterprises must react and participate or risk falling behind.  Accenture rightly focuses on “The Journey to ROI” because many projects cannot get funded sufficiently if there is no ROI attached.  The challenge we face is that we are in a new age and use cases, although high in potential, have not all had sufficient time to bear fruit and generate ROI.  This is likely to change as innovative companies try new things and generate the return they are looking for and then publish those outcomes.  The momentum will grow and it will be companies like Predixion and Accenture that move the needle for corporations around the globe, across all industries.  New companies with funny names like Jointly, Cirro, SourceThought, Maana, Ubix, Pivotal and others are sprouting up with new approaches that take big data well past just another flavor of Hadoop and it’s exciting to see their growth.

One example of the meteoric rise of data volume, veracity, velocity and all the other V’s is the sensor data generated in what GE calls the “Industrial Internet.”  Cisco calls it the “Internet of Things.”  I call it “Really Bloody Big Data!” GE’s software initiative to pull this together is based in San Ramon, CA and is co-incidentally called “Predix.”  We at Predixion are proud to be listed as a strategic partner alongside great companies like Intel, Amazon Web Services, Intel, Accenture and Cisco and we are working with those partners to help solve big hairy problems at GE.  The industrial internet is effectively the management of the incredible volumes of data that come from sensors that are attached to all things made by GE.  From oil well blowout preventers to MRI scanners, locomotives and jet engines, the value that can be created when captured, understood and used is incredible.  GE states that just a 1% reduction in inefficiency in the healthcare industry as a result of this technology would save the industry over $63 Billion per annum.  These are big numbers folks and I for one am glad to be working with Accenture and GE to be a part of the future for these types of revolutions.

With software like Predixion’s and global consulting services like Accenture’s attacking problems like GE’s, you have a potent combination that can change industries.  It’s not enough to install great software, the real gems lay in the change management that can come from implementing such innovative solutions across industries.  How does a nurse change the way he operates if he is now intervening on high risk patients whose predicted outcome he has never had visibility into before?  How does an airline technician change her approach to preventative maintenance when the data flying off a jet engine part is scoring a predictive model in real time and alerting her on a smart phone that a part needs replacing?  I was lucky enough to dine with some industry heavyweights this past week including the CEO of GE, Jeff Immelt.  The big request from his biggest customers?  ZERO DOWN TIME.  It is the big hairy goal and predictive analytics can take companies there in all industries.  Its fascinating stuff and we are at the beginning of a new revolution.

Bring ‘Em On!

Simon Arkell

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Predixion Software Further Advances Predictive Analytics with its Latest Release

Check Out What’s New in Predixion Enterprise Insight™ 3.1

Predixion Software has introduced a new release of its flagship collaborative predictive analytics platform, Predixion Enterprise Insight™.  The 3.1 release furthers Predixion’s revolutionary technology – enabling non-technical users to take advantage of advanced predictive analytics or skilled business analysts and data scientists to expedite the creation, re-use, sharing and deployment of their predictive models and applications.

Building on the functionality enhancements of the 3.0 release, Predixion Enterprise Insight™ 3.1, continues to deliver big data visualizations, an innovative data preparation workbench, comprehensive in-database analytics and extended data source integration with advancements in the user’s experience. Key features include:

  • A new, modern user interface
  • Enriched Machine Learning Semantic Model allows defining Modeling Goals for automatic selection of the best model for a given problem
    • Modeling Goals can be accuracy-related, such as the best area under the ROC Curve, the best recall, or the best R2 metric
    • Modeling Goals can be business related, such as cost minimization or profit maximization
  • Updated Accuracy Charts including a quantile chart for classification models
  • User created post-processing functions
  • Extended data access enabling connections to most data sources

The newest release is ready for Download now.

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FreeCreditReport.Com: The Future of Healthcare?


Predictive Analytics: Saving Lives

I had many interesting conversations recently at the HIMSS conference in New Orleans.  The healthcare industry is actively talking about shifting the focal point of care from illness to wellness but few folks really understood that predictive analytics is fundamental in that monumental shift.  At present the healthcare system knows very little about us till we show up at the hospital or in a doctor’s office sick.  In order to become preventive, the healthcare system will have to begin tracking our vitals decades before it currently does and listening in ways it currently does not.

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Can We Wash Our Hands of Hospital Acquired Infections with Predictive Analytics?

As I was getting ready to see my next patient, I began what has now become a familiar ritual for doctors and nurses everywhere, washing my hands, doing my part to not become a vector for disease. As I toweled off my chapped hands for the umpteenth time today, a thought occurred to me: how come we’re not better at preventing hospital acquired infections (HAIs) despite all this hand washing? Across the country doctors and nurses are scrubbing our hands until they are impossibly chapped, yet HAIs abound. We’re doing our part but not really making much of a dent. I wondered if there might be a way that our IT systems and the immense quantity of data we collect on each and every patient might lend a helping hand…

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ACO Success Lies in Predictive Analytics

I find it hard to imagine that Accountable Care Organizations (ACO) are going to be as wildly successful as projected without an ability to actively use the data they are obligated to collect. The Centers for Medicare & Medicaid Services (CMS) require the average ACO to compile data on their patients and then use that same data to demonstrate that they’ve met the CMS requirements of data use, reporting and improving quality. If those requirements aren’t met… well let’s just say that ACO might not be around for much longer.

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Getting Started with Predixion Insight Developer Edition

You may not be aware that just a few weeks ago we released our Predixion Insight Developer Edition.  I have to say I’m happily surprised at the amount of uptake and attention this release had generated, with new users coming on board and adopting Predixion Insight as their predictive platform of choice.

Predixion Insight Developer Edition is a completely free version of our Predixion Insight Enterprise that is licensed for development, testing, and evaluation purposes.  This is the exact same service that we deploy in the cloud and with our enterprise customers – you get the whole enchilada that you can deploy right on your desktop or laptop.

Since Predixion Insight is a server product the pre-requisites and installation can be burdensome to the non-technical crew.  If that describes you, and you still want to use Predixion Insight for dev, test, and eval purposes, you can use our cloud service – again, for free – under the same restrictions.  Since it is a hosted service, you won’t get the full flexibility of the enterprise platform, but all of the Office-integrated analytical functionality will be at your disposal.  Subscribe to the cloud service here.

If you are technical enough to install some server-type software, then read on.

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Exposing the Shortcomings of LACE as a Valid Tool for Reducing Hospital Readmissions

With the first round of CMS penalties about to come out for hospitals with unacceptable readmission rates, there will be a lot of people suddenly interested in ways to decrease their readmission rates. I’m guessing that a lot of those people will want to use the LACE index, developed in Ontario, Canada, to predict the risk of patients for death or unplanned readmission within 30 days of discharge. LACE is an acronym for Length of Stay, Acuity of admission, Co-morbities (as measured by a Charlson Score) and number of previous ED visits in the last six (6) months preceding this admission. Read More »

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Sharing and Collaborating with Predixion Insight

The most significant insights aren’t discovered in a vacuum. Predixion Insight provides the tools and methodologies allowing you to share predictive results with your colleagues from various aspects of your business in order to extract the most value from your data. This article will describe the variety of ways that you can share using Predixion Insight for collaboration and productionalization. Read More »

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Using Predictive Analytics to Seriously Accelerate PI Cycle Time (Seriously)

One of the most frustrating things for me about starting a new clinical process improvement (PI) project is just how flipping long it takes to get actionable results. Most of us use the tried and true PDCA (Plan, Do, Check, Act) method of W. Edward Deming fame.

Predictive analytics short-circuits this PDCA process by looking at huge chunks of data (from your EHR, lab, pharmacy, etc.) and by simultaneously examining lots of variables associated with the process being improved, in order to show which of those variables have the strongest association with the outcome you are measuring. Read More »

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Introducing: “Practical Predictive Analytics for Healthcare 101″ White Paper

Using predictive analytics and modeling tools is becoming a common and often daily occurrence in the work of caring for patients and populations in the healthcare industry.  But for someone who may be new to the field or has had limited exposure and/or experience with predictive analytics, the concept of mining data to predict the future may seem not only foreign, but a bit intimidating. Read More »

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