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Big Data: Embracing Data to Transform Healthcare and Pharma Commercial Strategy - Featuring Expert Panel Views from Industry Survey 2016

Big Data: Embracing Data to Transform Healthcare and Pharma Commercial Strategy - Featuring Expert Panel Views from Industry Survey 2016

Summary

GBI Research’s latest report," Big Data: Embracing Data to Transform Healthcare and Pharma Commercial Strategy - Featuring Expert Panel Views from Industry Survey 2016" provides a comprehensive analysis of the Big Data landscape. GBI Research conducted an extensive industry survey of 73 experts from the pharmaceutical and healthcare industries - including both organizations that already utilize Big Data and those that do not. Our survey gathered experience and opinion on the use of Big Data, and insights on key trends for the present and future use of the technology within healthcare. The findings from the survey and results from secondary research efforts have been amalgamated with GBI’s own analytical views to provide an assessment that is comprehensive in outlook.

Big Data refers to any data set that is too large to store, process or analyze using traditional database software and hardware. It can have a significant impact on all aspects of the pharmaceutical and healthcare sector, and companies are making large investments to leverage the technology more effectively. Big Data has been a buzzword for many years, but it is no longer merely an abstract concept that could provide future benefits, as it is already providing competitive advantages for a variety of organizations. As such, companies that ignore its potential may fall behind their peers in our increasingly data-intensive world.

The report features an overview of Big Data and its place within healthcare. It examines the factors driving and necessitating the use of the technology within this industry, and provides detailed examples of how different Big Data sources and analytics techniques could be used to provide direct benefits to pharmaceutical companies, healthcare institutions and patients. There is also an analysis of the main challenges surrounding the technology, as well as detailed real-world case studies of how major companies already implement Big Data and deal with some of the challenges. Finally, based upon the totality of our survey results and research, strategic recommendations and guidelines are provided for the effective implementation of Big Data within healthcare.

The results of GBI’s latest industry survey provide insightful analyses from different expert panels, including those that already use Big Data and those that do not, key regional markets, and respondents from within the pharmaceutical industry and those from the wider healthcare industry. The survey examined key issues, such the areas where organizations are currently utilizing Big Data, where they believe it can have the most impact, the main barriers to use and driving factors, likelihood of increasing investment within the next five years, and overall stance on the use of the technology within healthcare.

GBI Research conducted extensive research in order to provide a comprehensive view of Big Data for healthcare landscape. This new report adds to our unique portfolio of trusted industry analyses that enable our clients to assess the most promising areas in the market and exploit key business opportunities.

Scope

  • What is Big Data? What is its place within healthcare, and what are the main data sources?
  • How prevalent is the use of Big Data in healthcare?
  • What are the main driving factors necessitating the use of Big Data in healthcare? What is the relative importance of these factors according to industry?
  • What are examples of the commercial benefits that the use of Big Data and analytics can provide, in different aspects of the industry?
  • In which areas are organizations currently using Big Data, and where do they feel it will have the most impact in the next five years?
  • What are the main challenges associated with Big Data in healthcare? What is the relative importance of these factors according to industry? For the organizations that do not yet utilize Big Data, what specific reasons have led to their decision not to do so?
  • How do major pharmaceutical and healthcare companies use Big Data in the real world? What are some of the main partnerships between Big Pharma and technology companies? What is the underlying technical architecture of Big Data in healthcare?
  • What is the likelihood that organizations that already use Big Data will increase their investment within the next five years? Will those that do not currently invest in the technology begin doing so in the next five years?
  • How can Big Data be effectively implemented within an organization?
  • What is the overall stance of various experts in the healthcare field on the use of Big Data in healthcare?
Key Reasons to Purchase

This report will allow you to -
  • Gain insightful analyses and comprehensive understanding of Big Data in healthcare
  • Understand the key drivers necessitating the use of Big Data and the main barriers to implementation
  • Understand the views of 73 organizations within the industry on Big Data, and assess real-world case studies
  • Assess the most relevant uses of Big Data within your company, and effective ways of implementing Big Data strategies


1 Table of Contents
1.1 List of Tables
1.2 List of Figures
2 Big Data Overview
2.1 What is Big Data?
2.2 The ‘Three Vs’ of Big Data: Volume, Velocity and Variety
2.3 The Sources of Big Data in Healthcare
2.4 Big Data Lifecycle
2.5 How Prevalent is the use Big Data in Healthcare? Results from our Industry-Wide Survey
3 Drivers of Big Data in Healthcare
3.1 Advances in Technology: Explosion in Data Generation
3.1.1 Next-Generation Sequencing Technologies: Outpacing Moore’s Law
3.1.2 Proteomic Databases: ProteomicsDB Designed with Big Data Analytics in Mind
3.1.3 Electronic Health Records: A Form of Big Data
3.1.4 Social Media: Information That Cannot Be Found Anywhere Else
3.1.5 Devices: Smartphones, Wearables and Telemedicine Devices Represent a Continuous Source of Big Data
3.1.6 Cloud Technologies: Often Integral to Big Data
3.2 Needs and Trends Driving the Use of Big Data in Healthcare
3.2.1 Real-World Evidence: Data Outside of Clinical Trials
3.2.2 Value-Based Healthcare: Emphasizing Quality over Quantity
3.2.3 Personalized Medicine and Targeted Therapies: Transforming Healthcare
3.2.4 The R&D Productivity Gap
3.2.5 The Need to Increase Operational Efficiency and Reduce Operational Costs
3.3 What Are the Most Important Drivers? How Do Opinions Differ Between Different Groups and Regions? Results from Our Industry-Wide Survey
4 Commercial Implications of Big Data in Healthcare
4.1 Predictive Modeling: Fundamental Source of Big Data’s Power
4.1.1 Using Big Data for Patient-Specific Modeling: Potential for Huge Healthcare Savings
4.2 Big Data Unlocks the Potential of Personalized Medicine and Targeted Therapies
4.3 Utilizing the Unique Big Data Provided by Wearables and Fitness Trackers
4.4 Big Data for a More Systemic Approach to Drug Repositioning
4.5 Drug Discovery and Pre-Clinical Trials: Big-Data-Guided Drug Development
4.6 Leveraging Big Data to Overhaul the Clinical Trial Process
4.7 Implications for Real-World Evidence, Post-Approval Monitoring, Pharmacovigilance and Value-Based Healthcare
4.8 Actionable Insights for Sales and Marketing Processes
4.9 Improving Manufacturing Processes
4.10 In Which Healthcare Areas Do Organizations Currently Utilize Big Data? How Does This Differ between Regions? Results From Our Industry-Wide Survey
4.11 Where do Organizations Believe Big Data Will Have the Greatest Impact in the Next Five Years? Results From Our Industry Survey
5 Challenges Associated with Big Data in Healthcare
5.1 Data Quality: Analysis Output Can Only Be as Good as the Data Input
5.1.1 Does “Messy” Real-World Data Have a Place in Evidence-Based Medicine?
5.2 Data Silos: Organizations Not Willing to Share
5.3 Privacy, Security and Big Data: An Uneasy Relationship
5.3.1 Shortage of People with Relevant Skills
5.4 Technical and Infrastructure Challenges
5.5 What Are the Biggest Restraints Against the Use of Big Data in Healthcare? Results from Our Industry Survey
5.6 What Are the Particular Reasons Specific Organizations Have Not Implemented Big Data? Results from Our Industry Survey
6 Big Data in Practice: Real-World Case Studies and Technical Details
6.1 Big Pharma and Big Data: Various Technology Partnerships, including Roche, Allergan, AstraZeneca, Sanofi, Novartis, Teva, Medtronic, Novo Nordisk
6.2 Big Data Analytics: Underlying Architecture and Popular Platforms and Tools
6.3 Novartis: Overcoming the Challenge of Interacting with and Integrating Heterogeneous Big Data Sets to Ensure Competitive Advantage
6.4 Pfizer Combines Three Key Sources of Big Data to Create its Precision Medicine Analytics Ecosystem
6.5 Using Big Data to Prevent Pharmaceutical Counterfeiting and Fraud
6.6 Roche: Believes Big Data Presents a Huge Opportunity to Improve Treatments and Innovate
6.7 Advocate Health Care System Utilizes Big Data to Reduce Hospital Re-admissions by 20% within Three Months
6.8 Some 94% of Organizations that Use Big Data Are Likely to Increase their Investment within the Next Five Years According to our Industry-Wide Survey
7 Strategic Considerations for Effective Implementation of Big Data in Healthcare
7.1 Data Considerations when Designing a Big Data System: Focus on Optimizing Inputs
7.1.1 Data Collection: Strategies for Competitive Differentiation
7.1.2 In Summary: A Data Manifesto
7.2 Possible Big Data Ownership Structures within an Organization: Choose the Right One for You
7.3 Big Data Talent Can be both a Competitive Differentiator and Limiting Factor within Organizations
7.4 Treat Big Data Systems as an Ongoing Project that is Never Completed
7.5 Framework for Finding Business Use Cases for Big Data within your Organization
7.6 Big Data Landscape within Healthcare: Different Sectors are in Different Points of Progression
7.7 42% of Organizations Believe Big Data will Revolutionize Healthcare, According to our Industry-Wide Survey
7.8 Conclusion: Organizations that Ignore Big Data Risk Falling Behind
8 Appendix
8.1 GBI Industry Survey: Breakdown of Respondents by General Industry
8.2 GBI Industry Survey: Breakdown of Respondents by Specific Sector
8.3 GBI Industry Survey: Breakdown of Respondents by Region
8.4 GBI Industry Survey: Proportion of Healthcare Organizations that Currently Utilize Big Data
8.5 GBI Industry Survey: Big Data Utilization in Healthcare, Comparison of Expert Panels from Europe, North America and Asia
8.6 GBI Industry Survey: Most Important Factors Promoting the Use of Big Data in Healthcare
8.7 GBI Industry Survey: Most Important Factors Promoting Big Data, Pharmaceutical Expert Panel vs Overall Healthcare Expert Panel
8.8 GBI Industry Survey: Most Important Factors Promoting Big Data, Regional Breakdown
8.9 GBI Industry Survey: Most Common Healthcare Areas for Big Data Implementation
8.10 GBI Industry Survey: Extent of Utilization of Big Data across Organizations
8.11 GBI Industry Survey: The Most Common Healthcare Areas in which Big Data is Currently Implemented, Europe vs North America
8.12 GBI Industry Survey: Areas Where Big Data Will Have the Most Impact over the Next Five Years
8.13 GBI Industry Survey: Most Important Restraints on the use of Big Data in Healthcare
8.14 GBI Industry Survey, Most Important Restraints on Use of Big Data in Healthcare, Breakdown by Region
8.15 GBI Industry Survey: Reasons Preventing Organizations from Implementing Big Data into their Business
8.16 GBI Industry Survey: Likelihood of Organizations that Use Big Data Increasing Investment in the Technology in Next Five Years
8.17 GBI Industry Survey: Likelihood of Organizations that do not use Big Data Increasing Investment in the Technology in Next Five Years
8.18 GBI Industry Survey: Overall Stance of Organizations on the use of Big Data in Healthcare
8.19 References
8.20 Contact Us
8.21 Disclaimer

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