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Summary:

The massive amount of data that is emerging from connected, digital systems, is fundamentally changing everything, from Internet search to entertainment, to disease management, to energy consumption. Here’s 10 case studies that highlight the power of big data.

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One hospital’s embrace of big data

By Barb Darrow

The University of Pittsburgh Medical Center is a microcosm (albeit a large one) of the big data problem facing medical organizations. Hospitals are under intense pressure to cut costs, but they are simultaneously expected to modernize their IT and maintain their patient care.

Until now, most medical organizations were focused on getting their electronic medical record (EMR) systems running. These systems digitize the paper-intensive world of traditional medicine. The problem is that many organizations, including UPMC, picked the best EMR for certain medical specialties and now must deal with a welter of systems that don’t talk to each other very well. The worst part? EMRs represent only a portion of the data hospitals generate.

The goal is to somehow create one complete electronic record for patients that includes all their data (images, pharmacy records, clinical notes, self-reported patient information), regardless of underlying system and to combine that information with relevant financial, genomic, and research data to provide a holistic view within the EMR, said Lisa Khorey, the VP of enterprise services and data management at UPMC.

Dr. Rasu Shrestha, the VP of medical information technologies, is intimately familiar with the challenges of managing vast amounts of medical data, as well as the opportunities for hospitals that do it well: He is both an M.D. and the IT guy who has to make it happen.

UPMC and its affiliates make up a $10 billion entity, with 55,000 employees at more than 20 academic and regional hospitals. Its health plan has close to 1.5 million members and a network of 125 hospitals. It encompasses both the health care payer (insurance company) and provider (hospital). Those two pools of data represent what Shrestha calls the “yin and yang” of accountable care.

The EMR work started years ago and is fully deployed, but this phase of bringing all the data together in a unified, meaningful, record at the point of care continues. UPMC’s contract with Nuance Communications, for example, was signed last year and is a ten-year commitment.

Mission possible?

The stakes are huge. For one thing, better patient care depends on this secure flow of pertinent patient data to the clinician. If UPMC’s Medicare Advantage plan meets certain quality and performance standards set by the Centers for Medicare and Medicaid Services (CMS), it could reap an additional $40 million to $50 million in pay-for-performance bonuses. Effective use of big data is a prerequisite to that payoff. Systems need to be in place to make sure those quality metrics can be measured and achieved.

UPMC also fields 31 clinical systems for various specialties: Cerner for inpatients, EpicCare for ambulatory care, Allscripts for affiliates and Varian for oncology. The doctor for any given patient might need information from many of those sources to get to the full story.

Of course, there are non-IT issues in all of these moves. Older clinicians are not necessarily thrilled with using new technology, but those barriers are falling as younger, tech-proficient doctors come up the ranks.

UPMC is certainly not the only hospital struggling with these issues, but a Nuance executive that works with many health care organizations said UPMC is well ahead of others in terms of moving beyond EMRs.

Doctors now try to take a more holistic view of their patients, and that requires the ability to pull together data from different sources. Imaging data is separate from surgery notes, which is separate from pharmacy data.

“If we look at big data, the idea is how to interconnect multiple points of data across the broad, biological continuum,” Shrestha said. “If the patient is diabetic, you don’t just see an endocrinologist looking at the liver in terms of liver function tests or any scans but across the biological spectrum of organs and then down to a cellular level. We look at pathology slides, reports on molecular imaging and down to the genomic levels.”

As the data gets more granular, the data set gets bigger. “We start talking about gigabytes per image. We have to get ready for this tsunami of data,” he said.

For large health care organizations, data proliferation means doctors have to spend time corralling the information. “We play detective more than anything, piecing together information as we interact with the patient,” Shrestha said in a recent interview. “We’re trying to make sense of all this by figuring out how to get to where I, as a clinician, get to be more a clinician and less a detective.”

Three big buckets of data

Data volume is one thing, but the diversity of data is another. Shrestha puts it in three buckets. First there is all that imaging: CAT scans, PET scans, MRI scans. UPMC has close to 2 PB of total archival data at this stage and nearly 1 PB of imaging data.

The second bucket is traditional structured data sitting in relational databases. That represents about 20 percent of all non-imaging data. This includes structured data both within the EMRs and in standard databases that underlie key operational systems like accounts payable and receivable, the transaction systems that run the hospital.

The third bucket — the remaining 80 percent of non-image data — is unstructured. This includes postoperative notes, radiology reports, discharge summaries. Some are written or typed. Much is spoken or dictated and has to be transcribed and digitized.

UPMC is still evaluating some of the technology that it will use, including IBM/Cognos and Oracle databases and related tools. It is using DBMotion to handle much of the EHR integration, and Nuance’s’ natural-language-processing technologies to deal with the voice-to-digital transcription process at the front end and act as a searchable back-end repository for that data once it is processed through the Clinical Language Understanding (CLU) engine.

UPMC has aggregated data from those 31 provider-based systems, and there have already been payoffs, Shrestha said. Because doctors can see not only what has been prescribed across all EMR systems but also the claims information, they know which prescriptions have been filled. “This is all about filtering the noise to get data that is actionable. In this case we won’t treat the patient with a pseudo condition of acute abdominal pain but get to the root of his problem, which is probably opiate addiction,” Shrestha said.

But there could be bigger payoffs down the road, as machine learning can be applied to historical patient data to extract medical insights that would otherwise never be found. “If you take all those patient records and run algorithms and machine learning tools against a 20-year set, it will find things we wouldn’t have found otherwise. Some will be valuable,” Khorey said.

UPMC plans to launch a digital pathology PACS (picture archiving and communication system) from Omnyx — a company formed by UPMC and GE Healthcare) that will generate more imaging data. These systems basically put that biological or chemical data from blood tests, cell cultures and so on into digital format. That is the next data tsunami UPMC is prepping for.

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  1. Reblogged this on Dots Of Color and commented:
    Big data big money!

    1. I don’t get it, what does Big Data have to do with a video card…or is this some lamesauce ad post?

    2. The emergence of this so-called big data phenomenon is also fundamentally changing everything from the way companies operate

      1. Yes, it does. Who controls the most data wins. At least Facebook would like to think so. ;-)

  2. Is gigabytes bytes more then a gigabyte?

    1. Katie Fehrenbacher gil Monday, March 12, 2012

      nope just a typo, fixed that, thanks!

      1. Typos happen.
        Gil’s “more thEn a gigabyte” is just plain ignorant.

    2. Grammar Police gil Thursday, March 15, 2012

      If you’re going to complain about a typo, make sure you don’t have any in your immature comment. When you have full mastery of the language, then you’ll be allowed to comment.

  3. infotech ideas Monday, March 12, 2012

    Great info! Bring the expo to SFO as well!

  4. remedy2020@gmail.com Monday, March 12, 2012

    Advertorial ! Advertorial! so fast you sold your soul!

  5. DataStax, more specifically Cassandra, can solve all big data problems.
    http://cassandra.apache.org/
    And its open sourced.

  6. SAP HANA to the rescue!

  7. Reblogged this on <i>cu Lì!</i> and commented:
    great info :)

  8. why do we have to click through so many pages. can you at least provide a way to read it in a single page? (like businessinsider) there is not even a print option and it doesn’t work with readability. i thought more of gigaom. disappointed.

  9. idiots…
    «“We want to unlock the black box of how an artist becomes a star,” White said»
    what makes the charts is good music, not $$$$$ pumped into it 8-X
    just like m$$$$$ can keep wasting billion$ on WP trying to make it a success, it won’t work. its crap, it doesn’t sell
    period

  10. Steven Brown Monday, March 19, 2012

    Big Data is a tactical problem. Content and Business Analytics and Intelligence is the logistical problem. One must pay particular attention to Business Process Models, Entity-Relationship Models, and Data Modeling to be able to use ETL and Data Integration Technologies for developing your data storage organization, retrieval, formatting, clustering, Web Caching; and backup, recovery, and archival retention strategies.

  11. Edwin Ritter Wednesday, May 9, 2012

    Reblogged this on Ritter's Ruminations & Ramblings and commented:
    As 2012 reaches the half way mark, here is a quick view on how this hot topic. This is the first of three. Posts on the other trends will follow.

    So ‘big data’ is a hot topic. What is it? Simply stated, everything you do on the web is tracked and creates data. So much data is collected that 90% of the online data was created in just the last two years. This data is stored, sliced, diced and analyzed. The growth in data is due to several things such as proliferation of smart phones and tablets, lower storage costs and improved analytical tools. This article reveals 10 ways in which big data will have an impact.

  12. Mission Impossible Wednesday, May 30, 2012

    Thank you for the thoughts on this so far.
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  13. Mission Impossible Thursday, May 31, 2012

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