Global Big Data Analytics in Healthcare Market to 2023: Surge in Demand for Structured & Unstructured Dataset Analysis
DUBLIN, July 31, 2018 /PRNewswire/ --
The "Big Data Analytics in Healthcare by Component, by Deployment Type, by Analytics Type, by Application, by Region - Global Market Size, Share, Development, Growth, and Demand Forecast, 2013 - 2023" report has been added to ResearchAndMarkets.com's offering.
The global big data analytics in healthcare market is gaining interest due to the introduction of personalized healthcare systems and demand for high quality healthcare services. Through the adoption of big data, healthcare payers and providers are enhancing their capabilities by studying patient behavior towards a particular treatment and the diagnostic patterns, in order to provide them with customized and highly cost-effective services.
Based on deployment type, big data analytics in healthcare market is categorized into on-demand and on-premise. Of the two, the on-demand deployment generated larger revenue as compared to the on-premise software deployment. Further, on the basis of hardware, big data analytics in healthcare market is categorized into data storage, routers, firewalls, virtual private network, e-mail servers, and others; others include data centers hardware and on-premise and on-cloud hardware. Among these, data storage accounted for the largest revenue share in the market in 2017.
Geographically, North America has been the largest big data analytics in healthcare market; however, the fastest growth during the forecast period is expected from Asia-Pacific. This can be attributed to factors such as advancement in big data technologies, growing digitalization, expanding data analytics software industry, and increasing adoption of big data analytics services by healthcare providers in the region. Further, due to various initiatives undertaken by the government to integrate big data in the healthcare industry, for making more sophisticated and cheap healthcare services available to people, the market in the region is expected to grow significantly in the coming years.
Factors driving the growth of big data analytics in healthcare market include significant increase in demand for financial analytics in healthcare, surge in demand for exploring structured and unstructured data present in the healthcare industry, decreasing costs and availability of big data software and services, along with amplified adoption of new technologies for data analytics in healthcare business transformations, globally.
While the healthcare industry has been generating huge volumes of data, big data analytics solutions aim to generate valuable insights from such data to improve the quality of healthcare services and reduce the overall cost incurred in the healthcare ecosystem. This is achieved by exploring large sets of structured and unstructured databases, to gain and access trends and patterns present in the current healthcare environment. Financial analytics sealed the largest market share in 2017, as it provides healthcare organizations with greater and better visibility into several factors that drive revenues, reduce operational costs and manage shareholder value. The application uses sophisticated software technology such as specialized billing process and knowledge, to keep a track of various claims processed, and the amount of revenue collected from different segments.
Additionally, the demand for personalized health records through big data is also propelling the growth of big data analytics in healthcare market. The demand for high quality and personalized healthcare services has prompted patients to store their medical information online, which in turn helps doctors to schedule appointments as per the availability at both-ends, organize and keep a track of past diagnosis anytime anywhere, and provide patients with all the necessary information related to a disease or other health issues.
Data analytics providers are partnering with healthcare providers to increase their market share. The major players are also developing new solutions for healthcare data analytics. Some of the key players operating in the big data analytics in healthcare market are McKesson Corporation, Cognizant Technology Solutions Corporation, Epic System Corporation, Cerner Corporation, Dell Inc., GE Healthcare, Siemens AG, Koninklijke Philips N.V., and Xerox Corporation.
Most of the major vendors in the big data analytics in healthcare market are actively focusing on enhancing their offerings to meet the surging demand for advanced healthcare solutions. This includes software development, hardware integration, and big data analytics learning.
Key Topics Covered
Chapter 1. Research Background
1.1 Research Objectives
1.2 Market Definition
1.3 Research Scope
1.3.1 Market Segmentation By Component
1.3.2 Market Segmentation By Deployment Type
1.3.3 Market Segmentation By Analytics Type
1.3.4 Market Segmentation By Application
1.3.5 Market Segmentation By Geography
1.3.6 Analysis Period
1.3.7 Market Data Reporting Unit
1.3.7.1 Value
1.4 Key Stakeholders
Chapter 2. Research Methodology
2.1 Secondary Research
2.2 Primary Research
2.2.1 Breakdown Of Primary Research Respondents
2.2.1.1 By Region
2.2.1.2 By Industry Participant
2.2.1.3 By Company Type
2.3 Market Size Estimation
2.4 Data Triangulation
2.5 Assumptions For The Study
Chapter 3. Executive Summary
Chapter 4. Introduction
4.1 Definition Of Market Segments
4.1.1 By Component
4.1.1.1 Services
4.1.1.2 Software
4.1.1.2.1 Electronic Health Record (Ehr)
4.1.1.2.2 Workforce Management
4.1.1.2.3 Practice Management
4.1.1.3 Hardware
4.1.1.3.1 Data Storage
4.1.1.3.2 Routers
4.1.1.3.3 Firewall
4.1.1.3.4 Virtual Private Network (Vpn)
4.1.1.3.5 Email Servers
4.1.1.3.6 Others
4.1.2 By Deployment Type
4.1.2.1 On-Premise
4.1.2.2 On Demand
4.1.3 By Analytics Type
4.1.3.1 Descriptive Analytics
4.1.3.2 Predictive Analytics
4.1.3.3 Prescriptive Analytics
4.1.4 By Application
4.1.4.1 Financial Analytics
4.1.4.1.1 Claim Processing
4.1.4.1.2 Revenue Cycle Management
4.1.4.1.3 Risk Adjustment And Assessment
4.1.4.1.4 Payment Integrity And Fraud, Waste And Abuse
4.1.4.2 Operational Analytics
4.1.4.3 Population Health Analytics
4.1.4.4 Clinical Data Analytics
4.1.4.4.1 Quality Control
4.1.4.4.2 Population Health Management
4.1.4.4.3 Clinical Decision Support
4.1.4.4.4 Reporting And Compliance
4.1.4.4.5 Precision Health
4.2 Market Dynamics
4.2.1 Trends
4.2.1.1 Big Data Improves Clinical Studies, Population And Inventory Management
4.2.2 Drivers
4.2.2.1 Increase In Demand For Financial Analytics In Healthcare Sector
4.2.2.2 Surge In Demand For Structured And Unstructured Dataset Analysis
4.2.2.3 Government Initiative For Adoption Of Ehr
4.2.2.4 Impact Analysis Of Drivers On Market Forecast
4.2.3 Restraints
4.2.3.1 Lack Of Skilled Staff Hindering The Implementation Of Big Data In Healthcare Sector
4.2.3.2 Lack Of Trust In Technology And Security Concerns
4.2.3.3 Adoption Of Different Analytical Tools Will Affect Data Interoperability
4.2.3.4 Impact Analysis Of Restraints On Market Forecast
4.2.4 Opportunities
4.2.4.1 Iot In Healthcare Sector Would Ensure Real Time Mobility Of Information
4.2.4.2 Adoption Of Value-Based Patient Centric Care Model
4.3 Porter's Five Forces Analysis
Chapter 5. Global Market Size And Forecast
5.1 By Component
5.1.1 Software By Type
5.1.2 Hardware By Type
5.2 By Analytics Type
5.3 By Deployment Type
5.4 By Application
5.4.1 Financial Analytics By Type
5.4.2 Clinical Data Analytics By Type
5.5 By Region
Chapter 6. North America Market Size And Forecast
6.1 By Component
6.1.1 Software By Type
6.1.2 Hardware By Type
6.2 By Analytics Type
6.3 By Deployment Type
6.4 By Application
6.4.1 Financial Analytics By Type
6.4.2 Clinical Data Analytics By Type
6.5 By Country
Chapter 7. Europe Market Size And Forecast
7.1 By Component
7.1.1 Software By Type
7.1.2 Hardware By Type
7.2 By Analytics Type
7.3 By Deployment Type
7.4 By Application
7.4.1 Financial Analytics By Type
7.4.2 Clinical Data Analytics By Type
7.5 By Country
Chapter 8. Apac Market Size And Forecast
8.1 By Component
8.1.1 Software By Type
8.1.2 Hardware By Type
8.2 By Analytics Type
8.3 By Deployment Type
8.4 By Application
8.4.1 Financial Analytics By Type
8.4.2 Clinical Data Analytics By Type
8.5 By Country
Chapter 9. Row Market Size And Forecast
9.1 By Component
9.1.1 Software By Type
9.1.2 Hardware By Type
9.2 By Analytics Type
9.3 By Deployment Type
9.4 By Application
9.4.1 Financial Analytics By Type
9.4.2 Clinical Data Analytics By Type
9.5 By Country
Chapter 10. Competitive Landscape
10.1 Competitive Benchmarking Of Key Players
10.2 Recent Activities Of Key Players
10.3 Global Strategic Developments Of Key Players
10.3.1 Mergers And Acquisitions
10.3.2 Product And Service Launches
10.3.3 Partnerships
10.3.4 Client Wins
Chapter 11. Company Profiles
11.1 Mckesson Corporation
11.1.1 Business Overview
11.1.2 Product And Service Offerings
11.1.3 Key Financial Summary
11.2 Cerner Corporation
11.2.1 Business Overview
11.2.2 Product And Service Offerings
11.2.3 Key Financial Summary
11.3 Allscripts Healthcare Solutions, Inc.
11.3.1 Business Overview
11.3.2 Products And Service Offerings
11.3.3 Key Financial Summary
11.4 Epic Systems Corporation
11.4.1 Business Overview
11.4.2 Products And Service Offerings
11.5 Koninklijke Philips N.V.
11.5.1 Business Overview
11.5.2 Products And Service Offerings
11.5.3 Key Financial Summary
11.6 Cognizant Technology Solutions Corporation
11.6.1 Business Overview
11.6.2 Product And Service Offerings
11.6.3 Key Financial Summary
11.7 Optum, Inc.
11.7.1 Business Overview
11.7.2 Products And Service Offerings
11.8 Wipro Limited
11.8.1 Business Overview
11.8.2 Product And Service Offerings
11.8.3 Key Financial Summary
11.9 Siemens Ag
11.9.1 Business Overview
11.9.2 Product And Service Offerings
11.9.3 Key Financial Summary
11.10 International Business Machines Corporation (Ibm)
11.10.1 Business Overview
11.10.2 Product And Service Offerings
11.10.3 Key Financial Summary
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