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
Table Of Contents
1 Table of Contents
1 Table of Contents 5
1.1 List of Tables 7
1.2 List of Figures 7
2 Big Data Overview 9
2.1 What is Big Data? 9
2.2 The ‘Three Vs’ of Big Data: Volume, Velocity and Variety 9
2.3 The Sources of Big Data in Healthcare 10
2.4 Big Data Lifecycle 12
2.5 How Prevalent is the use Big Data in Healthcare? Results from our Industry-Wide Survey 13
3 Drivers of Big Data in Healthcare 17
3.1 Advances in Technology: Explosion in Data Generation 17
3.1.1 Next-Generation Sequencing Technologies: Outpacing Moore’s Law 17
3.1.2 Proteomic Databases: ProteomicsDB Designed with Big Data Analytics in Mind 18
3.1.3 Electronic Health Records: A Form of Big Data 19
3.1.4 Social Media: Information That Cannot Be Found Anywhere Else 19
3.1.5 Devices: Smartphones, Wearables and Telemedicine Devices Represent a Continuous Source of Big Data 20
3.1.6 Cloud Technologies: Often Integral to Big Data 20
3.2 Needs and Trends Driving the Use of Big Data in Healthcare 21
3.2.1 Real-World Evidence: Data Outside of Clinical Trials 21
3.2.2 Value-Based Healthcare: Emphasizing Quality over Quantity 21
3.2.3 Personalized Medicine and Targeted Therapies: Transforming Healthcare 21
3.2.4 The R&D Productivity Gap 22
3.2.5 The Need to Increase Operational Efficiency and Reduce Operational Costs 22
3.3 What Are the Most Important Drivers? How Do Opinions Differ Between Different Groups and Regions? Results from Our Industry-Wide Survey 24
4 Commercial Implications of Big Data in Healthcare 27
4.1 Predictive Modeling: Fundamental Source of Big Data’s Power 27
4.1.1 Using Big Data for Patient-Specific Modeling: Potential for Huge Healthcare Savings 28
4.2 Big Data Unlocks the Potential of Personalized Medicine and Targeted Therapies 28
4.3 Utilizing the Unique Big Data Provided by Wearables and Fitness Trackers 29
4.4 Big Data for a More Systemic Approach to Drug Repositioning 29
4.5 Drug Discovery and Pre-Clinical Trials: Big-Data-Guided Drug Development 29
4.6 Leveraging Big Data to Overhaul the Clinical Trial Process 30
4.7 Implications for Real-World Evidence, Post-Approval Monitoring, Pharmacovigilance and Value-Based Healthcare 31
4.8 Actionable Insights for Sales and Marketing Processes 32
4.9 Improving Manufacturing Processes 32
4.10 In Which Healthcare Areas Do Organizations Currently Utilize Big Data? How Does This Differ between Regions? Results From Our Industry-Wide Survey 33
4.11 Where do Organizations Believe Big Data Will Have the Greatest Impact in the Next Five Years? Results From Our Industry Survey 36
5 Challenges Associated with Big Data in Healthcare 38
5.1 Data Quality: Analysis Output Can Only Be as Good as the Data Input 38
5.1.1 Does “Messy” Real-World Data Have a Place in Evidence-Based Medicine? 38
5.2 Data Silos: Organizations Not Willing to Share 38
5.3 Privacy, Security and Big Data: An Uneasy Relationship 39
5.3.1 Shortage of People with Relevant Skills 39
5.4 Technical and Infrastructure Challenges 40
5.5 What Are the Biggest Restraints Against the Use of Big Data in Healthcare? Results from Our Industry Survey 41
5.6 What Are the Particular Reasons Specific Organizations Have Not Implemented Big Data? Results from Our Industry Survey 42
6 Big Data in Practice: Real-World Case Studies and Technical Details 44
6.1 Big Pharma and Big Data: Various Technology Partnerships, including Roche, Allergan, AstraZeneca, Sanofi, Novartis, Teva, Medtronic, Novo Nordisk 44
6.2 Big Data Analytics: Underlying Architecture and Popular Platforms and Tools 45
6.3 Novartis: Overcoming the Challenge of Interacting with and Integrating Heterogeneous Big Data Sets to Ensure Competitive Advantage 48
6.4 Pfizer Combines Three Key Sources of Big Data to Create its Precision Medicine Analytics Ecosystem 49
6.5 Using Big Data to Prevent Pharmaceutical Counterfeiting and Fraud 49
6.6 Roche: Believes Big Data Presents a Huge Opportunity to Improve Treatments and Innovate 50
6.7 Advocate Health Care System Utilizes Big Data to Reduce Hospital Re-admissions by 20% within Three Months 51
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 53
7 Strategic Considerations for Effective Implementation of Big Data in Healthcare 55
7.1 Data Considerations when Designing a Big Data System: Focus on Optimizing Inputs 55
7.1.1 Data Collection: Strategies for Competitive Differentiation 55
7.1.2 In Summary: A Data Manifesto 56
7.2 Possible Big Data Ownership Structures within an Organization: Choose the Right One for You 56
7.3 Big Data Talent Can be both a Competitive Differentiator and Limiting Factor within Organizations 57
7.4 Treat Big Data Systems as an Ongoing Project that is Never Completed 57
7.5 Framework for Finding Business Use Cases for Big Data within your Organization 58
7.6 Big Data Landscape within Healthcare: Different Sectors are in Different Points of Progression 59
7.7 42% of Organizations Believe Big Data will Revolutionize Healthcare, According to our Industry-Wide Survey 60
7.8 Conclusion: Organizations that Ignore Big Data Risk Falling Behind 61
8 Appendix 63
8.1 GBI Industry Survey: Breakdown of Respondents by General Industry 63
8.2 GBI Industry Survey: Breakdown of Respondents by Specific Sector 63
8.3 GBI Industry Survey: Breakdown of Respondents by Region 63
8.4 GBI Industry Survey: Proportion of Healthcare Organizations that Currently Utilize Big Data 64
8.5 GBI Industry Survey: Big Data Utilization in Healthcare, Comparison of Expert Panels from Europe, North America and Asia 64
8.6 GBI Industry Survey: Most Important Factors Promoting the Use of Big Data in Healthcare 65
8.7 GBI Industry Survey: Most Important Factors Promoting Big Data, Pharmaceutical Expert Panel vs Overall Healthcare Expert Panel 65
8.8 GBI Industry Survey: Most Important Factors Promoting Big Data, Regional Breakdown 66
8.9 GBI Industry Survey: Most Common Healthcare Areas for Big Data Implementation 66
8.10 GBI Industry Survey: Extent of Utilization of Big Data across Organizations 67
8.11 GBI Industry Survey: The Most Common Healthcare Areas in which Big Data is Currently Implemented, Europe vs North America 67
8.12 GBI Industry Survey: Areas Where Big Data Will Have the Most Impact over the Next Five Years 68
8.13 GBI Industry Survey: Most Important Restraints on the use of Big Data in Healthcare 68
8.14 GBI Industry Survey, Most Important Restraints on Use of Big Data in Healthcare, Breakdown by Region 69
8.15 GBI Industry Survey: Reasons Preventing Organizations from Implementing Big Data into their Business 69
8.16 GBI Industry Survey: Likelihood of Organizations that Use Big Data Increasing Investment in the Technology in Next Five Years 70
8.17 GBI Industry Survey: Likelihood of Organizations that do not use Big Data Increasing Investment in the Technology in Next Five Years 70
8.18 GBI Industry Survey: Overall Stance of Organizations on the use of Big Data in Healthcare 71
8.19 References 71
8.20 Contact Us 75
8.21 Disclaimer 75
List Of Tables
1.1 List of Tables
Table 1: Sources of Big Data in Healthcare 11
Table 2: Types of Technological Devices and the Information They Can Feed into Big Data Systems 20
Table 3: Summary of the Drivers and Needs Necessitating the Use of Big Data in Healthcare 23
Table 4: Summary of Challenges Associated with Big Data in Healthcare 40
Table 5: Selected Partnerships Between Pharma and Big Data, Technology Companies 44
Table 6: Platforms and Tools for Big Data Analytics in Healthcare 47
Table 7: Case Study, Novartis - Overcoming Big Data Challenges to Ensure Competitive Advantage 48
Table 8: Case Study, Pfizer’s Precision Medicine Analytics Ecosystem 49
Table 9: Case Study, Fortune 100 Company Uses Big Data to Protect Against Counterfeiting 50
Table 10: Case Study, Roche and Big Data - Four Key Areas of Work Identified by the Company 50
Table 11: Case Study, Selected Roche (France) Big Data Projects 51
Table 12: Case Study, How Advocate Health System Implemented Big Data to Reduce Hospital Re-admissions and Achieve Many Other Benefits 52
Table 13: Most Common Big Data Ownership Structures within Organizations 56
Table 14: Key Team Members within a Big Data Program 57
Table 15: Hype Cycle for Emerging Technologies 59
List Of Figures
1.2 List of Figures
Figure 1: The ‘Three Vs’ of Big Data 9
Figure 2: Sources of Big Data in Healthcare 10
Figure 3: Typical Big Data Lifecycle 12
Figure 4: GBI Industry Survey, Breakdown of Respondents by General Industry 13
Figure 5: GBI Industry Survey, Breakdown of Respondents by Specific Sector 13
Figure 6: GBI Industry Survey, Breakdown of Respondents by Region 14
Figure 7: GBI Industry Survey, Proportion of Healthcare Organizations that Currently Utilize Big Data 14
Figure 8: GBI Industry Survey, Big Data Utilization in Healthcare, Comparison of Expert Panels from Europe, North America and Asia 15
Figure 9: Cost of Sequencing a Human Genome, 2001-2015 18
Figure 10: GBI Industry Survey, Most Important Factors Promoting the Use of Big Data in Healthcare 24
Figure 11: GBI Industry Survey, Most Important Factors Promoting Big Data, Pharmaceutical Expert Panel vs Overall Healthcare Expert Panel 25
Figure 12: GBI Industry Survey, Most Important Factors Promoting Big Data, Regional Breakdown 25
Figure 13: Using Big Data to Enable Predictive Analytics and Modeling 27
Figure 14: Insights Provided by Big Data for the Development of Personalized Medicines 28
Figure 15: Using Big Data for Drug Repositioning 29
Figure 16: Big-Data-Guided Drug Development and its Commercial Benefits 30
Figure 17: Using Big Data to Optimize Sales Force Coverage within Geographic Areas 32
Figure 18: GBI Industry Survey, Most Common Healthcare Areas for Big Data Implementation 33
Figure 19: GBI Industry Survey Results, Extent of Utilization of Big Data across Organizations 34
Figure 20: GBI Industry Survey, Most Common Healthcare Areas for Big Data Implementation, Europe vs North America 35
Figure 21: GBI Industry Survey: Areas Where Big Data Will Have the Most Impact over the Next Five Years 36
Figure 22: GBI Industry Survey, Most Important Restraints on Use of Big Data in Healthcare 41
Figure 23: GBI Industry Survey, Most Important Restraints on Use of Big Data in Healthcare, Breakdown by Region 42
Figure 24: GBI Industry Survey, Reasons Preventing Organizations from Implementing Big Data into their Business 42
Figure 25: Underlying Architecture of Big Data Analytics 46
Figure 26: GBI Industry Survey, Likelihood of Organizations that Use Big Data Increasing Investment in the Technology in Next Five Years 53
Figure 27: GBI Industry Survey, Likelihood of Organizations that do not use Big Data Investing in the Technology in Next Five Years 54
Figure 28: Hype Cycle for Big Data within Healthcare: Different Sectors at Differing Points of Progression 60
Figure 29: GBI Industry Survey, Overall Stance of Organizations on use of Big Data in Healthcare 61
Figure 30: Overview of Insights and Benefits Offered by Big Data 62
Figure 31: GBI Industry Survey, Breakdown of Respondents by General Industry 63
Figure 32: GBI Industry Survey, Breakdown of Respondents by Specific Sector 63
Figure 33: GBI Industry Survey, Breakdown of Respondents by Region 63
Figure 34: GBI Industry Survey, Proportion of Healthcare Organizations that Currently Utilize Big Data 64
Figure 35: GBI Industry Survey, Big Data Utilization in Healthcare, Comparison of Expert Panels from Europe, North America and Asia 64
Figure 36: GBI Industry Survey, Most Important Factors Promoting the Use of Big Data in Healthcare 65
Figure 37: GBI Industry Survey, Most Important Factors Promoting Big Data, Pharmaceutical Expert Panel vs Overall Healthcare Expert Panel 65
Figure 38: GBI Industry Survey, Most Important Factors Promoting Big Data, Regional Breakdown 66
Figure 39: GBI Industry Survey, Most Common Healthcare Areas for Big Data Implementation 66
Figure 40:GBI Industry Survey Results, Extent of Utilization of Big Data across Organizations 67
Figure 41: GBI Industry Survey, Most Common Healthcare Areas for Big Data Implementation, Europe vs North America 67
Figure 42: GBI Industry Survey, Areas Where Big Data Will Have the Most Impact over the Next Five Years 68
Figure 43: GBI Industry Survey, Most Important Restraints on Use of Big Data in Healthcare 68
Figure 44: GBI Industry Survey, Most Important Restraints on Use of Big Data in Healthcare, Breakdown by Region 69
Figure 45: GBI Industry Survey, Reasons Preventing Organizations from Implementing Big Data into their Business 69
Figure 46: GBI Industry Survey, Likelihood of Organizations that Use Big Data Increasing Investment in the Technology in Next Five Years 70
Figure 47: GBI Industry Survey, Likelihood of Organizations that do not use Big Data Investing in the Technology in Next Five Years 70
Figure 48: GBI Industry Survey, Overall Stance of Organizations on use of Big Data in Healthcare 71
