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Making Data Work

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Making data work for providers, patients, payers, and population health. In healthcare, using this data in meaningful ways has the potential for people to live longer healthier lives.

Be sure to check out NetApp's healthcare solutions page: http://www.netapp.com/us/solutions/industry/healthcare/

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Making Data Work

  1. 1. of hospitals keep patient electronic health records.4 59% Making Data Work Applications of big data analysis in healthcare are more than promising. 1.http://www.theguardian.com/healthcare-network/2014/nov/04/big-data-enabling-future-healthcare 2.https://gigaom.com/2013/08/03/big-data-is-healthcares-biggest-threat-and-also-its-likely-savior/ 3.http://www.accenture.com/us-en/Pages/insight-stats-health-amount-data-health-organizations.aspx 4.http://www.eweek.com/it-management/health-care-it-investment-falling-short-in-mobile.html 5.http://www.entrepreneur.com/article/238955 6.http://www.informationweek.com/healthcare/analytics/healthcare-dives-into-big-data/d/d-id/1251138 7.http://www.nih.gov/news/health/oct2014/od-09.htm 8.http://www.bloomberg.com/news/articles/2013-02-08/ibm-s-watson-turned-into-cloud-products-for-wellp oint-s-doctors 9.http://www.forbes.com/sites/bruceupbin/2013/02/08/ibms-watson-gets-its-first-piece-of-business-in-healt hcare/ 10.http://www.idc.com/getdoc.jsp?containerId=prUS25262514 11.http://techcrunch.com/2014/11/20/healthcares-big-data-opportunity/ 12.http://www.technologyreview.com/news/529011/can-technology-fix-medicine/ 13.https://hbr.org/2014/10/predictive-medicine-depends-on-analytics/ 14.http://www.netapp.com/us/company/news/press-releases/news-rel-20111101-787689.aspx 15.http://www.mckinsey.com/insights/health_systems_and_services/the_big-data_revolution_in_us_health_c are 16.http://blogs.wsj.com/cio/2014/06/24/fitness-tracking-programs-enter-the-big-data-challenge/) 17.http://www.netapp.com/us/system/pdf-reader.aspx?pdfuri=tcm:10-126883-16&m=uz-leuven.pdf&q=UZ%20L euven&cp=1 Better use of big data in healthcare could eventually result in $300 to $450 billion in savings every year.15 For Providers, Patients, Payers and Population Health Express Scripts compiled data from doctors, pharmacies and laboratories to detect patterns among its 90 million U.S. members, who receive 1.4 billion prescriptions annually. The company can now predict, with 98% accuracy, 12 months in advance, which patients may not take their medicine.12 Leveraging these predictions could reduce the $289 billion annual cost of medication noncompliance in the U.S.13 A hospital in New Jersey analyzes geographical and historical data to create real-time predictions for where emergency services will be needed. The hospital’s response rates now average fewer than six minutes, compared to the national average of nine minutes. Before the new system, one in five patients regained a pulse after experiencing a cardiac arrest; now, it’s one in two.11 Transplant doctors search the Be The Match Registry of more than 15 million donors and 400,000 umbilical cord blood units using a sophisticated matching algorithm application 100 million times more complex than blood typing programs. Be The Match intends to aid 10,000 transplants by 2015.14 A hospital in Belgium uses data both for patient care and as a tool to further healthcare research and education. The hospital’s radiology data is growing rapidly. A CT scan today consists of 2,000 images, 20 times more than a typical CT scan five years ago.17 ® BUT HOW DOES IT HELP? 101010000100010000100001000101000001000010000010000100001000010001000100010001000010000100001000 010000100001000010001000101010001010100001000100001000010001010000010000100000100001000010000100 010001000100010000100000000100001000010000100001000100010101000101010000100010000100001000101000 001000010000010000100001000010001000100010001000010000100001000010000100001000010001000101010001 010100001000100001000010001010000010000100000100001000010000100010001000100010000100001000010000 100001000010000100010001010100010101000010001000010000100010100000100001000001000010000100001000 100010001000100001000000001000010000100001000010001000101010001010100001000100001000010001010000 010000100000100001000010000100010001000100010000100001000010000100001000010000100010001010100010 101000010001000010000100010100000100001000001000010000100001000100010001000100001000010000100001 000010000100001000100010101000101010000100010000100001000101000001000010000010000100001000010001 000100010001000010000000010000100001000010000100010001010100010101000010001000010000100010100000 100001000001000010000100001000100010001000100001000010000100001000010000100001000100010101000 A standard EKG machine gathers about 1,000 data points every second, while a 3D CT scan occupies over one 1 GB of space.2 Healthcare data is MASSIVE and it comes from EVERYWHERE The human body produces up to 150 trillion GB of information, which can be collected in many ways.1 By 2020, healthcare organizations are expected to use 25,000 petabytes of data, 50 times more data than today.3 Americans currently use mobile health technologies.5 95 Million Twenty percent of Aetna's corporate customers have signed up for its Get Active wellness program, which allows employees to funnel data from fitness trackers.16 95% of healthcare CEOs say they’re investigating better ways to use big data.6 Data storage for the NIH National Center for Biotech- nology Information Initia- tive could fill 400 million four-drawer filing cabinets.7 By 2016, 15% of hospitals will create comprehensive patient profiles that will allow them to deliver personalized treatment plans.10 By 2020, 80% of healthcare data will pass through the cloud at some point in its lifetime.10 How Analytics are Impacting and Improving Care Health insurance company WellPoint, the second-largest U.S. health insurer, analyzes and processes data from 605,000 pieces of medical evidence, two million pages of text, 25,000 training cases and 14,700 clinician hours to assist in medical decision-making. 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