Global Big Data in Healthcare Market

Report ID : 1215 | Published : 2022-05-24 | Pages: | Format:

Big data healthcare analytics has arisen as a foremost learning technique to deal with the large volume of data in the healthcare sector. The healthcare industry has a bunch of data, and it could benefit from interactive dynamic big data platforms with cutting-edge technologies and tools to improve patient care and services. The ability to conduct comparative effectiveness research to find more clinically appropriate and cost-effective ways to diagnose and treat patients has been characterized as one of the benefits of analytics in healthcare. Big data techniques can improve the quality of healthcare data analysis, and it is beneficial for patients and healthcare organizations.

Major driving factors of the big data in healthcare market are the advancements in healthcare technologies, increasing funding to improve healthcare services, rising patient pool.

The market growth is further attributed to high demand for cost-effective treatments, adoption of mobile healthcare applications, and the fast integration of digital technologies by healthcare organizations. However, the requirement of significant investments to implement big data services and the lack of awareness about the digital-technology based healthcare applications may hinder the market growth over the forecast period.

Big data in healthcare market is segmented into component and services, application, delivery model, healthcare vertical, and region. The component and services segment comprises hardware (data servers and storage, servers, and networking), software (electronic health records, practice management software, revenue cycle management software, and workforce management software), and analytical services (descriptive analytics, prescriptive analytics, and predictive analytics). The hardware segment is predicted to dominate the market during the forecast years due to the high demand for digital, computer-based healthcare platforms. By application, the market is classified into clinical data analytics (quality care, population health management, clinical decision support, precision medicine, and reporting compliance), financial analytics (claims processing, revenue cycle management software, and risk assessment), and operational analytics (workforce analytics and supply chain analytics). The clinical data analytics segment leads this market as it provides real-time data analysis and saves cost and time. By delivery model, the market is categorized into on-demand and on the cloud. By healthcare vertical, the market is classified into pharmaceutical, medical devices, healthcare services, and other verticals. The healthcare services are accounted for the highest market share due to the increasing demand for advanced healthcare data management services. Region-wise, the market is studied across North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa.

North America is expected to witness the highest growth in the big data in healthcare market during the forecast years, followed by Asia-Pacific due to the rising adoption of modern technologies and the surging need to handle and analyze massive medical records.

Some of the key players operating in the big data in healthcare market are Allscripts Healthcare Solutions, Inc., Aetna, Inc., Cerner Corporation, Cognization Technology Solutions Corporation, Computer Programs and Systems, eClinicalWorks, DELL, GE Healthcare, Health Catalyst, Epic Systems, IBM Corporation, Siemens Healthineers, Xerox Holdings Corporation, Oracle Corporation, McKesson Corporation, MedeAnalytics, Inc., Optum, Philips Healthcare, Tableau Software, Inc., Premier, Inc., SAP ERP, SAS, and other.

Chapter 1. Methodology and Scope

1.1. Research Methodology

1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

Chapter 3. Global Big Data in Healthcare Market Snapshot

Chapter 4. Global Big Data in Healthcare Market Variables, Trends & Scope

4.1. Market Segmentation & Scope

4.2. Drivers

4.3. Challenges

4.4. Trends

4.5. Investment and Funding Analysis

4.6. Industry Analysis – Porter’s Five Forces Analysis

4.7. Competitive Landscape & Market Share Analysis

4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: By Applications Estimates & Trend Analysis

5.1. By Applications & Market Share, 2020 & 2030

5.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Applications:

5.2.1. Opportunity Assessment

5.2.2. Clinical Data Analytics

5.2.3. Financial Analytics

5.2.4. Operational Analytics

Chapter 6. Market Segmentation 2: By Products Estimates & Trend Analysis

6.1. By Products & Market Share, 2020& 2030

6.2. Market Size (Value US$ Mn) & Forecasts and Trend Analyses, 2020 to 2030 for the following By Products:

6.2.1. Hardware

6.2.1.1.  Data and Storage

6.2.1.2.  Servers

6.2.1.3.  Networking

6.2.2. Software

6.2.2.1.  Electronic Health Records

6.2.2.2.  Practice Management Software

6.2.2.3.  Revenue Cycle Management Software

6.2.2.4.  Workforce Management Software

6.2.3. Analytics Services

6.2.3.1.  Descriptive Analytics

6.2.3.2.  Prescriptive Analytics

6.2.3.3.  Predictive Analytics

Chapter 7. Big Data in Healthcare Market Segmentation 3: Regional Estimates & Trend Analysis

7.1. North America

7.1.1. North America Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts By Applications, 2019-2030

7.1.2. North America Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts By Therapy, 2019-2030

7.1.3. North America Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts by Products, 2019-2030

7.1.4. North America Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts by country, 2019-2030

7.2. Europe

7.2.1. Europe Big Data in Healthcare Market revenue (US$ Million) By Applications, 2019-2030

7.2.2. Europe Big Data in Healthcare Market revenue (US$ Million) By Therapy, 2019-2030

7.2.3. Europe Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts by Products, 2019-2030

7.2.4. Europe Big Data in Healthcare Market revenue (US$ Million) by country, 2019-2030

7.3. Asia Pacific

7.3.1. Asia Pacific Big Data in Healthcare Market revenue (US$ Million) By Applications, 2019-2030

7.3.2. Asia Pacific Big Data in Healthcare Market revenue (US$ Million) By Therapy, 2019-2030

7.3.3. Asia Pacific Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts by Products, 2019-2030

7.3.4. Asia Pacific Big Data in Healthcare Market revenue (US$ Million) by country, 2019-2030

7.4. Latin America

7.4.1. Latin America Big Data in Healthcare Market revenue (US$ Million) By Applications, 2019-2030

7.4.2. Latin America Big Data in Healthcare Market revenue (US$ Million) By Therapy, 2019-2030

7.4.3. Latin America Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts by Products, 2019-2030

7.4.4. Latin America Big Data in Healthcare Market revenue (US$ Million) by country, 2019-2030

7.5. Middle East & Africa

7.5.1. Middle East & Africa Big Data in Healthcare Market revenue (US$ Million) By Applications, 2019-2030

7.5.2. Middle East & Africa Big Data in Healthcare Market revenue (US$ Million) By Therapy, 2019-2030

7.5.3. Middle East & Africa Big Data in Healthcare Market revenue (US$ Million) estimates and forecasts by Products, 2019-2030

7.5.4. Middle East & Africa Big Data in Healthcare Market revenue (US$ Million) by country, 2019-2030

Chapter 8. Competitive Landscape

8.1. Major Mergers and Acquisitions/Strategic Alliances

8.2. Company Profiles

8.2.1. Aetna, Inc.

8.2.2. Allscripts Healthcare Solutions, Inc.

8.2.3. Cerner Corporation

8.2.4. Cognization Technology Solutions Corporation

8.2.5. Computer Programs and Systems

8.2.6. DELL

8.2.7. Epic Systems

8.2.8. eClinicalWorks

8.2.9. GE Healthcare

8.2.10. Health Catalyst

8.2.11. IBM Corporation

8.2.12. McKesson Corporation

8.2.13. MedeAnalytics, Inc.

8.2.14. Optum

8.2.15. Oracle Corporation

8.2.16. Philips Healthcare

8.2.17. Premier, Inc.

8.2.18. SAP ERP

8.2.19. SAS

8.2.20. Siemens Healthineers

8.2.21. Tableau Software, Inc.

8.2.22. Xerox Holdings Corporation

8.2.23. Other Prominent Players

Global Big Data in Healthcare Market, by Components and Services 2022-2030 (Value US$ Mn)

  • Hardware
    • Data and Storage
    • Servers
    • Networking
  • Software
    • Electronic Health Records
    • Practice Management Software
    • Revenue Cycle Management Software
    • Workforce Management Software
  • Analytics Services
    • Descriptive Analytics
    • Prescriptive Analytics
    • Predictive Analytics

Global Big Data in Healthcare Market, by Application, 2022-2030 (Value US$ Mn)

  • Clinical Data Analytics
  • Quality Care
  • Population Health Management
  • Clinical Decision Support
  • Precision Medicine
  • Reporting Compliance
  • Financial Analytics
  • Claims Processing
  • Revenue Cycle Management Software
  • Risk Assessment
  • Operational Analytics
  • Workforce Analytics
  • Supply Chain Analytics

Global Big Data in Healthcare Market, by Delivery Model, 2022-2030 (Value US$ Mn)

  • On-Demand
  • Cloud

Global Big Data in Healthcare Market, by Healthcare Vertical, 2022-2030 (Value US$ Mn)

  • Pharmaceutical
  • Medical Devices
  • Healthcare Services
  • Other Verticals

Global Big Data in Healthcare Market, by Region, 2022-2030 (Value US$ Mn)

  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East & Africa

North America Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)

  • U.S.
  • Canada

Europe Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)

  • Germany
  • France
  • Italy
  • Spain
  • Russia
  • Rest of Europe

Asia Pacific Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)

  • India
  • China
  • Japan
  • South Korea
  • Australia & New Zealand

Latin America Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)

  • Brazil
  • Mexico
  • Rest of Latin America

Middle East & Africa Big Data in Healthcare Market, by Country, 2022-2030 (Value US$ Mn)

  • GCC Countries
  • South Africa
  • Rest of Middle East & Africa 

Competitive Landscape

  • Company Overview
  • Financial Performance
  • Key Development

Latest Strategic Developments

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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Big Data in Healthcare Market is Expected to Reach $ 84.5 Billion by 2030

CAGR of 16.20% during the forecast period of 2022-2030.

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