Big Data in HealthcareMedical data represents a large, rapidly growing, and mostly unstructured data residing in multiple ...
3.1 Conceptual Challenges 133.1.1 Volume 133.1.2 Variety 133.1.3 Velocity 143.2 Practical Challenges 153.2.1 Healthcare As...
4.2.2.4 Explorys 254.2.2.4.1 Explorys Platform 254.2.2.5 Humedica 264.2.2.5.1 Humedica Minedshare 264.2.2.6 Predixion Soft...
5.2 More Towards Personalized Medicine 445.3 Potential To Predict - And Hopefully Then Prevent - Disease 445.4 More Analyt...
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Big Data In Healthcare Industry Available on Researchmoz.us

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Medical data represents a large, rapidly growing, and mostly unstructured data residing in multiple locations including lab and imaging systems, physician notes, medical correspondence, claims, CRM and financial systems. With resizing costs with the healthcare industry, there is an imperative to reduce the cost of care and efficiently manage resources without compromising patient care. Healthcare organizations have the opportunity to leverage big data technology to perform analytics to improve care and profitability.

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Transcript of "Big Data In Healthcare Industry Available on Researchmoz.us"

  1. 1. Big Data in HealthcareMedical data represents a large, rapidly growing, and mostly unstructured data residing in multiple locationsincluding lab and imaging systems, physician notes, medical correspondence, claims, CRM and financialsystems. With resizing costs with the healthcare industry, there is an imperative to reduce the cost of care andefficiently manage resources without compromising patient care. Healthcare organizations have theopportunity to leverage big data technology to perform analytics to improve care and profitability. Thisreport evaluates Big Data in healthcare ecosystem and opportunities including technologies, growth drivers,challenges, and stakeholders. The report analyzes different business models employed by healthcare big databusiness practices, including key factors affecting each business model, various company approaches andsolutions. Target Audience: Big Data application developers Telecommunications companies Big datamanagement companies Healthcare institutions of all types Investors in Big Data infrastructuretable Of Contents:1.0 Executive Summary 52.0 Introduction 62.1 What Is Big Data? 62.2 Big Data Categories 72.2.1 Structured Big Data 72.2.2 Un-structured Data 72.2.3 Semi-structured Data 82.3 Why Is It Important? 82.3.1 Pattern Discovery 82.3.2 Decision Making 82.3.3 Process Invention 92.3.4 Increasing Revenue 102.4 Big Data Growth Drivers 112.5 Big Data Technology 112.5.1 Sensors 112.5.2 Computer Networks 112.5.3 Data Storage 112.5.4 Cluster Computer Systems 122.5.5 Cloud Computing Facilities 122.5.6 Data Analysis Algorithms 123.0 Big Data In Healthcare 13Big Data in Healthcare
  2. 2. 3.1 Conceptual Challenges 133.1.1 Volume 133.1.2 Variety 133.1.3 Velocity 143.2 Practical Challenges 153.2.1 Healthcare As A Technology Laggard 153.2.2 Integration 153.2.3 Security 163.2.4 Standards 163.2.5 Real-time Processing 163.3 Healthcare Stakeholders 173.3.1 Patients 173.3.2 Providers 173.3.3 Researchers 173.3.4 Pharma Companies 173.3.5 Medical Devices Companies 183.3.6 Payers 183.3.7 Governments 183.3.8 Software Developers 184.0 Big Data Healthcare Business Models And Companies 194.1 Genomics Research 194.1.1 Important Factors For Genomic Research Solutions 194.1.1.1 Long Term Storage 194.1.1.2 Strong Processing Power 194.1.2 Key Players And Solutions 204.1.2.1 Genome Health Solutions 204.1.2.2 Gns Healthcare 204.2 Healthcare Big Data Analytics 214.2.1 Important Factors For Healthcare Data Warehousing Solutions 214.2.1.1 Cost 214.2.1.2 Flexible Data Operations 214.2.1.3 High Quality Reporting Service 214.2.1.4 Administration 224.2.1.5 Easier Maintenance 224.2.2 Key Players And Solutions 224.2.2.1 Ibm 224.2.2.1.1 Ibm Netezza 224.2.2.2 Oracle 234.2.2.2.1 Oracle Healthcare Data Warehousing Foundation 244.2.2.3 Zanett 244.2.2.3.1 The Zanett Real Enterprise Value (rev™) 24Big Data in Healthcare
  3. 3. 4.2.2.4 Explorys 254.2.2.4.1 Explorys Platform 254.2.2.5 Humedica 264.2.2.5.1 Humedica Minedshare 264.2.2.6 Predixion Software 264.2.2.6.1 Predixion Insight™ 274.2.2.7 Health Fidelity 274.2.2.7.1 Fidelity Platform 284.2.2.8 Practice Fusion 284.2.2.9 Athenahealth, Inc 294.2.2.9.1 Athenahealth Solutions 304.2.2.10 intersystems 304.2.2.10.1 healthshare 304.2.2.11 pentaho 314.2.2.11.1 pentaho Business Analytics 314.3 Fraud Detection And Management 344.3.1 Important Factors For Healthcare Fraud Detection And Management Solutions 344.3.1.1 Multiple Methods Of Analysis 344.3.1.2 Social Network Analysis 344.3.2 Key Players And Solutions 344.3.2.1 Verizon 344.3.2.1.1 Verizon Fraud Management 354.3.2.2 Pervasive 364.3.2.2.1 Pervasives Datarush 364.4 Personalized Medicine 374.4.1 Important Factors For Personalized Medicine Solution 374.4.1.1 Innovation Protection 374.4.1.2 Enhanced Network Infrastructure 384.4.2 Key Players And Solutions 384.4.2.1 Upmc Health 384.5 Mobile-based Healthcare 404.5.1 Important Factors On Mobile-based Healthcare Solutions 404.5.1.1 Wide Coverage 404.5.1.2 Support For Multi-platforms 404.5.2 Key Players And Solutions 404.5.2.1 Humetrixs Ibluebutton 404.5.2.2 Sproxil Inc. 414.5.2.3 Welldoc 424.5.2.4 Zeo, Inc 435.0 Future Outlook 445.1 More Research For Big Data Analytics 44Big Data in Healthcare
  4. 4. 5.2 More Towards Personalized Medicine 445.3 Potential To Predict - And Hopefully Then Prevent - Disease 445.4 More Analytics For Doctors 445.5 More Towards Drug Discovery 44About Us:ResearchMoz(http://www.researchmoz.us/) is the one stop online destination to find and buy market researchreports & Industry Analysis. We fulfill all your research needs spanning across industry verticals with ourhuge collection of market research reports.Contact:M/s Sheela,90 State Street,Suite 700,Albany NY - 12207United StatesTel: +1-518-618-1030USA - Canada Toll Free 866-997-4948Email: sales@researchmoz.usBlog: http://researchmoz.blogspot.com/Website: http://www.researchmoz.us/Big Data in Healthcare

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