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市場調查報告書

醫療產業大數據世界市場:市場分析、成長預測、競爭環境、國家分類分析 (2017-2025年)

Global Big Data in Healthcare Market - Analysis and Forecast 2017-2025: Focus on Components and Services, Applications, Competitive Landscape and Country Analysis

出版商 BIS Research Inc. 商品編碼 348543
出版日期 內容資訊 英文 303 Pages
商品交期: 最快1-2個工作天內
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醫療產業大數據世界市場:市場分析、成長預測、競爭環境、國家分類分析 (2017-2025年) Global Big Data in Healthcare Market - Analysis and Forecast 2017-2025: Focus on Components and Services, Applications, Competitive Landscape and Country Analysis
出版日期: 2018年03月29日 內容資訊: 英文 303 Pages
簡介

世界醫療產業大數據市場2016年創下114億5000萬美元規模的紀錄。2017年至2025年預計可維持2位數成長。

本報告針對世界醫療產業大數據市場調查、提供市場定義與概要、市場成長各種影響因素與市場機會分析、競爭環境與市場佔有率、相關法規、標準規格、零件、服務、用途、地區/主要國家分類動向與市場規模變化與預測、主要企業檔案。

摘要整理

第1章 調查範圍、調查方法

第2章 市場概要

  • 大數據:概要
  • 醫療產業大數據使用者

第3章 市場動力

  • 市場成長促進因素、課題影響分析
  • 市場成長促進因素
  • 市場課題
  • 市場機會

第4章 競爭環境

  • 市場佔有率分析
  • 主要發展、策略
    • 投入產品
    • M&A
    • 合作、協力、合意

第5章 產業分析

  • 法規情況
  • 企業、產業團體
  • 標準規格

第6章 世界醫療產業大數據市場分析、預測:零件、服務分類

  • 概要
  • 硬體
    • 資料儲存
    • 伺服器
    • 網路
  • 軟體
    • EHR (Electronic Health Records)
    • 診療管理軟體
    • 收益循環管理軟體
    • 工作量管理軟體
  • 分析服務
    • 說明分析
    • 處方分析
    • 預測分析

第7章 世界醫療產業大數據市場分析、預測:用途分類

  • 概要
  • 臨床數據分析
    • 高品質的醫療
    • PHM (Population Health Management)
    • 臨床決策支援
    • 精密醫療
    • 匯報與合法性
  • 財務分析
    • 索賠處理
    • 收益循環管理軟體
    • 風險評估
  • 營運分析
    • 人材分析
    • 供應鏈分析

第8章 地區分析

  • 概要
  • 北美
    • 美國
    • 加拿大
  • 歐洲
    • 英國
    • 法國
    • 西班牙
    • 義大利
    • 德國
    • 其他
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 澳洲
    • 其他
  • 其他地區
    • 拉丁美洲
    • 中東、非洲

第9章 企業檔案

  • Aetna, Inc.
  • Allscripts Healthcare Solutions, Inc.
  • Cerner Corporation
  • Cognization Technology Solutions Corporation
  • Computer Programs and Systems
  • DELL
  • Epic Systems
  • eClinicalWorks
  • GE Healthcare
  • Health Catalyst
  • IBM Corporation
  • McKesson Corporation
  • MedeAnalytics, Inc.
  • Optum
  • Oracle Corporation
  • Philips Healthcare
  • Premier, Inc.
  • SAP
  • SAS
  • Siemens Healthineer
  • Tableau Software, Inc.
  • Xerox

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目錄
Product Code: BH004B

Health data has been growing at unprecedented rates, driven by fall in storage costs, emergence of cloud storage, growing regulatory mandates and the increasing government initiatives to promote adoption of healthcare information systems. The increasing adoption of wearable devices, at-home testing services and mhealth applications that are empowering patients to proactively manage their health are further contributing to the pool of personal data. The availability of large volumes of health information has paved way for massive advances in clinical research, development of precision medicine and clinical decision support tools, quicker drug discovery and more detailed view of population health, which has opened new arrays for managing chronic diseases.

The global big data in healthcare market amounted to $11.45 billion in 2016 and is expected to witness a double-digit growth throughout the forecast period of 2017-2025.

The research study is a compilation of various segmentations including the market breakdown by components and services, by application, and by region. This report provides a detailed market analysis and forecast of hardware, software and services, and prescriptive, descriptive and predictive analytics services. Additionally, it also includes analysis of applications of big data for clinical analytics, financial analytics, and operational analytics.

The market has been analyzed based on various micro and macro trends influencing it. While highlighting the key driving and restraining forces for this dynamic market, the report also provides a comprehensive section on competitive landscape, industry attractiveness, market share analysis, and competitive benchmarking within the global big data in the healthcare market.

The following key questions have been addressed in the report:

  • How has the big data in healthcare market evolved in the past and how is it anticipated to evolve during the forecast period from 2017 to 2025?
  • What are the major market factors propelling the growth of the market?
  • What are the various challenges that the industry is facing which need to be addressed?
  • Who are the key players across components, services, applications and regions for big data in healthcare?
  • What are the key developmental strategies adopted by the key players to stand out in this market?
  • What were the market shares of the different data analytics services providers in 2017?
  • How will the market for each component and application of big data in healthcare market grow during the forecast period? What will be the revenue generated by each segment by the end of 2025?
  • Which applications are an investment priority in different regions and why? What will be the revenue generated through each application through the forecast period?

The report also includes an exhaustive analysis of the market for each geographical region, namely North America, Europe, Asia-Pacific, Latin America and RoW. Each geographical region analysis details the individual push and pull forces, and market for components and services and analytics applications, in addition to the key players from that region.

The report also examines the role of the leading market players involved in the industry. The company profiles section highlights significant information about the key companies, such as their product portfolio, financial positions, and the SWOT analysis of these players. Some of the key players in the big data in healthcare market are McKesson Corporation, Allscripts, Epic Systems, Cerner Corporation, SAP, SAS, and Tableau, among others.

Executive Summary

Amid rising healthcare costs, increasing rates of chronic diseases, aging population and declining reimbursement costs, hospitals and other healthcare organizations are under considerable pressure to prioritize investments focusing on improving outcomes and resource management. The increasing supply of health-related data from various sources has the potential to transform the healthcare delivery system, reduce costs, improve patient outcomes and provide value-based care. The volume of healthcare data accounted for over 700 exabytes in 2017 from 153 million in 2013 and is projected to grow to 2,314 exabytes by 2020. Falling storage costs, emergence of cloud-based services and subscription models, government initiatives and regulatory mandates to encourage adoption of healthcare information systems and increasing adoption of mHealth, eHealth and wearable technologies among consumers are expected to drive the growth of the market.

Organizations are employing analytical tools and artificial intelligence and machine learning techniques on this growing pool of data to derive data-driven insights to reduce healthcare costs, enhance revenue streams, develop personalized medicine, and manage proactive patient care. Among, components and services, analytics services contributed the dominant share of $5.80 billion in 2017 and are expected to be the fastest growing segment throughout the forecast period. Financial analytics is the most prominent application of big data and contributed a market share of $2.38 billion 2016, due to early application of analytics for improving financial outcomes by analysing performance across revenue cycle management, insurance claims handling and fraud detection. However, clinical analytics is the priority investment for most of the organizations and is thus expected to witness the highest CAGR of 23.77% from 2017 to 2025, to reach the value of $11.35 billion by 2025. The access to large volumes of medical data has paved way for massive advances in clinical research, development of precision medicine and clinical decision support tools, speedier drug discovery and opened new arrays for managing chronic diseases.

While North America has been the leading market for big data in healthcare due to early adoption of the technology in the region, APAC is anticipated to grow at the fastest rate in the forecast period as development of big data infrastructure, and applications has become a priority field of investment for governments of the emerging economies of India and China. However, challenges must be overcome to improve connectivity and linkage between existing databases is to realize the complete potential of data-driven health care systems. National and international platforms need to be established that can consolidate patient data over time and across different clinics.

Encouraging adoption of healthcare information systems, promoting usage of interoperable shared electronic health records (EHRs) and appropriate security measures to protect sensitive information, adoption of standard clinical terminologies, and building a more collaborative research environment will play a key role in improving the use of data analytics tools among the healthcare organizations. Substantial commitment and collaboration is demanded from all the stakeholders, along with a strong governance framework to ensure effective use of big data.

Table of Contents

Executive Summary

1 Report Scope and Methodology

  • 1.1 Scope of the Report
  • 1.2 Key Objectives
  • 1.3 Research Methodology
    • 1.3.1 Key Data Points From Primary Sources
    • 1.3.2 Key Data Points from Secondary Sources
    • 1.3.3 Data Triangulation
    • 1.3.4 Bottom-Up Approach (Segmental Analysis)
    • 1.3.5 Top-Down Approach (Segmental Analysis)
    • 1.3.6 Assumptions and Limitations
    • 1.3.7 Assumptions and Limitations for Market Estimation and Forecast

2 Market Overview

  • 2.1 Big Data Overview
  • 2.3 Big Data Users in Healthcare

3 Market Dynamics

  • 3.1 Impact Analysis of Market Drivers and Challenges
  • 3.2 Market Drivers
  • 3.3 Market Challenges
  • 3.4 Market Opportunities

4 Competitive Landscape

  • 4.1 Market Share Analysis
  • 4.2 Key Developments and Strategies
    • 4.2.1 Product Launches
    • 4.2.2 Mergers and Acquisitions
    • 4.2.3 Collaborations, Partnerships and Agreements

5 Industry Analysis

  • 5.1 Regulatory Scenario
  • 5.2 Consortiums and Associations
  • 5.3 Standards

6 Global Big Data in Healthcare Market by Components and Services

  • 6.1 Overview
  • 6.2 Hardware
    • 6.2.1 Data Storage
    • 6.2.2 Servers
    • 6.2.3 Networking
  • 6.3 Software
    • 6.3.1 Electronic Health Records
    • 6.3.2 Practice Management Software
    • 6.3.3 Revenue Cycle Management Software
    • 6.3.4 Workforce Management Software
  • 6.4 Analytics Services
    • 6.4.1 Descriptive Analytics
    • 6.4.2 Prescriptive Analytics
    • 6.4.3 Predictive Analytics

7 Global Big Data in Healthcare Market by Application

  • 7.1 Overview
  • 7.2 Clincial Data Analytics
    • 7.2.1 Quality Care
    • 7.2.2 Population Health Management
    • 7.2.3 Clinical Decision Support
    • 7.2.4 Precision Medicine
    • 7.2.5 Reporting Compliance
  • 7.3 Financial Analytics
    • 7.3.1 Claims Processing
    • 7.3.2 Revenue Cycle Management Software
    • 7.3.3 Risk Assesment
  • 7.4 Operational Analytics
    • 7.4.1 Workforce Analytics
    • 7.4.2 Supply Chain Analytics

8 Global Big Data in Healthcare Market by Region

  • 8.1 Overview
  • 8.2 North America
    • 8.2.1 The U.S.
    • 8.2.2 Canada
  • 8.3 Europe
    • 8.3.1 The U.K
    • 8.3.2 France
    • 8.3.3 Spain
    • 8.3.4 Italy
    • 8.4.5 Germany
    • 8.4.6 Others
  • 8.4 Asia Pacific
    • 8.4.1 China
    • 8.4.2 Japan
    • 8.4.3 India
    • 8.4.4 Australia
    • 8.4.5 Others
  • 8.5 Rest of the World
    • 8.5.1 Latin America
    • 8.5.2 Middle East and Africa

9 Company Profiles

  • 9.1 Aetna, Inc.
    • 9.1.1 Aetna, Inc. Overview
    • 9.1.2 Active Health Management Overview
    • 9.1.3 Product Portfolio
    • 9.1.4 Financials
      • 9.1.4.1 Financial Summary
    • 9.1.5 SWOT Analysis
  • 9.2 Allscripts Healthcare Solutions, Inc.
    • 9.2.1 Overview
    • 9.2.2 Product Portfolio
    • 9.2.3 Financials
    • 9.2.3.1 Financial Summary
    • 9.2.4 SWOT Analysis
  • 9.3 Cerner Corporation
    • 9.3.1 Overview
    • 9.3.2 Product Portfolio
    • 9.3.3 Financials
      • 9.3.3.1 Financial Summary
    • 9.3.4 SWOT Analysis
  • 9.4 Cognization Technology Solutions Corporation
    • 9.4.1 Overview
    • 9.4.2 Product Portfolio
    • 9.4.3 Financials
      • 9.4.3.1 Financial Summary
    • 9.4.4 SWOT Analysis
  • 9.5 Computer Programs and Systems
    • 9.5.1 Overview
    • 9.5.2 Product Portfolio
    • 9.5.3 Financials
    • 9.5.3.1 Financial Summary
    • 9.5.4 SWOT Analysis
  • 9.6 DELL
    • 9.6.1 Overview
    • 9.6.2 Product Portfolio
    • 9.6.3 Financials
    • 9.6.3.1 Financial Summary
    • 9.6.4 SWOT Analysis
  • 9.7 Epic Systems
    • 9.7.1 Overview
    • 9.7.2 Product Portfolio
    • 9.7.3 Corporate Summary
    • 9.7.4 SWOT Analysis
  • 9.8 eClinicalWorks
    • 9.8.1 Overview
    • 9.8.2 Product Portfolio
    • 9.8.3 Corporate Summary
    • 9.8.4 SWOT Analysis
  • 9.9 GE Healthcare
    • 9.9.1 Overview
    • 9.9.2 Product Portfolio
    • 9.9.3 Financials
    • 9.9.3.1 Financial Summary
    • 9.9.4 SWOT Analysis
  • 9.10 Health Catalyst
    • 9.10.1 Overview
    • 9.10.2 Product Portfolio
    • 9.10.3 Corporate Summary
    • 9.10.4 SWOT Analysis
  • 9.11 IBM Corporation
    • 9.11.1 IBM Corporation Overview
    • 9.11.2 Truven Health Analytics Overview
    • 9.11.3 IBM Product Portfolio
    • 9.11.4 Truven Health Analytics Product Portfolio
    • 9.11.5 Financials
    • 9.11.5.1 Financial Summary
    • 9.11.6 SWOT Analysis
  • 9.12 McKesson Corporation
    • 9.12.1 Overview
    • 9.12.2 Product Portfolio
    • 9.12.3 Financials
    • 9.12.3.1 Financial Summary
    • 9.12.4 SWOT Analysis
  • 9.13 MedeAnalytics, Inc.
    • 9.13.1 Overview
    • 9.13.2 Product Portfolio
    • 9.13.3 Corporate Summary
    • 9.13.4 SWOT Analysis
  • 9.14 Optum
    • 9.14.1 Optum Overview
    • 9.14.2 United Health Group Overview
    • 9.14.3 Product Portfolio
    • 9.14.4 Financials
      • 9.14.4.1 Financial Summary
    • 9.14.5 SWOT Analysis
  • 9.15 Oracle Corporation
    • 9.15.1 Overview
    • 9.15.2 Product Portfolio
    • 9.15.3 Financials
    • 9.15.3.1 Financial Summary
    • 9.15.4 SWOT Analysis
  • 9.16 Philips Healthcare
    • 9.16.1 Overview
    • 9.16.2 Product Portfolio
    • 9.16.3 Financials
    • 9.16.3.1 Financial Summary
    • 9.16.4 SWOT Analysis
  • 9.17 Premier, Inc.
    • 9.17.1 Overview
    • 9.17.2 Product Portfolio
    • 9.17.3 Financials
      • 9.17.3.1 Financial Summary
    • 9.17.4 SWOT Analysis
  • 9.18 SAP
    • 9.18.1 Overview
    • 9.18.2 Product Portfolio
    • 9.18.3 Financials
      • 9.18.3.1 Financial Summary
    • 9.18.4 SWOT Analysis
  • 9.19 SAS
    • 9.19.1 Overview
    • 9.19.2 Product Portfolio
    • 9.19.3 Corporate Summary
    • 9.19.4 SWOT Analysis
  • 9.20 Siemens Healthineer
    • 9.20.1 Siemens Healthineer Overview
    • 9.20.2 Siemens Overview
    • 9.20.3 Product Portfolio
    • 9.20.4 Financials
      • 9.20.4.1 Financial Summary
    • 9.20.5 SWOT Analysis
  • 9.21 Tableau Software, Inc.
    • 9.21.1 Overview
    • 9.21.2 Product Portfolio
    • 9.21.3 Financials
      • 9.21.3.1 Financial Summary
    • 9.21.4 SWOT Analysis
  • 9.22 Xerox
    • 9.22.1 Overview
    • 9.22.2 Product Portfolio
    • 9.22.3 Financials
      • 9.22.3.1 Financial Summary
    • 9.22.4 SWOT Analysis

List of Tables

  • 1 Impact Analysis of Drivers
  • 2 Impact Analysis of Challenges
  • 3 Product Launches
  • 4 Mergers and Acquisitions
  • 5 Collaborations, Partnerships and Agreements
  • 6 Regulatory Bodies
  • 7 Consortiums/Associations
  • 8 Key Standards for Big Data in Healthcare
  • 9 Table: Some of the Big data in healthcare hardware vendors
  • 10 Table: Some of the Big data in healthcare hardware vendors
  • 11 Some of the Big Data in Healthcare Service Providers
  • 12 Key Big Data in Healthcare Initiatives taken in Europe
  • 13 Key Initiatives Taken by the Chinese Government in Favor of Healthcare IT
  • 14 The U.S. Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 15 Canada Big Data in Healthcare Market by Compon+C16ent, 2016-2025 ($Million)
  • 16 The U.K. Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 17 France Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 18 Germany Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 19 Spain Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 20 Italy Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 21 Others Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 22 China Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 23 Japan Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 24 India Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 25 Others Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 26 LATAM Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 27 Middle East and Africa Big Data in Healthcare Market by Component, 2016-2025 ($Million)
  • 28 Overview - Aetna, Inc.
  • 29 Overview - Allscripts Healthcare Solutions, Inc.
  • 30 Overview - Active Health Management
  • 31 Overview - Cerner Corporation
  • 32 Overview - Cognization Technology Solutions Corporation
  • 33 Overview - Computer Programs and Systems
  • 34 Overview - DELL
  • 35 Overview - Epic Systems
  • 36 Overview - eClinicalWorks
  • 37 Overview - GE Healthcare
  • 38 Overview - Health Catalyst
  • 39 Overview - IBM Corporation
  • 40 Overview - Truven Health Analytics
  • 41 Overview - McKesson Corporation
  • 42 Overview - MedeAnalytics, Inc.
  • 43 Overview - Optum
  • 44 Overview - United Health Group
  • 45 Overview - Corporation
  • 46 Overview - Philips Healthcare
  • 47 Overview - Premier, Inc.
  • 48 Overview - SAP
  • 49 Overview - SAS
  • 50 Overview - Siemens Healthineer
  • 51 Overview - Siemens+C29
  • 52 Overview - Tableau Software, Inc.
  • 53 Overview - Xerox
  • List of Figures
  • 1 Market Drivers and Challenges
  • 2 Global Big Data in Healthcare Market by Component, 2016
  • 3 Global Big Data in Healthcare Market by Component, 2025
  • 4 Global Big Data in Healthcare Market by Application, 2016 & 2025
  • 5 Global Big Data in Healthcare Market by Region, 2016
  • 6 Global Big Data in Healthcare Market by Region, 2025
  • 7 Global Big Data in Healthcare Market CAGR % (2017-2025) by Country
  • 8 Scope of the Report
  • 9 The Secondary Data Sources used in this Study
  • 10 Bottom Up Approach
  • 11 Top Down Approach
  • 12 Big Data Users in Healthcare Industry
  • 13 Market Dynamics Global Big Data in the Healthcare Market
  • 14 Adoption of EHR Among Non-Federal Acute Care Hospitals in the U.S.: 2009-2015
  • 15 Market Share Data Analytics in Healthcare
  • 16 EHR Market Share
  • 17 Share of Different Strategies in the Market
  • 18 Segmentation of the Big Data in Healthcare Market by Component
  • 19 Global Big Data in Healthcare Market by Component ($Million
  • 20 Importance of Hardware Components in Big Data Analytics in the Healthcare Sector
  • 21 Software by Type
  • 22 EHR Adoption Rates among Physicians: Top 10 Countries
  • 23 Electronic Health Purchase: Key Drivers
  • 24 Advantages of Practice Management Software
  • 25 Advantages of Revenue Cycle Management Software
  • 26 Advantages of Workforce Management Software
  • 27 Segmentation of Healthcare Analytics Applications
  • 28 Global Big Data in Healthcare Market by Application
  • 29 Use of Clinical Data Analytics
  • 30 Use of Clinical Data Analytics in Recent Healthcare Initiatives
  • 31 Applications of Clinical Data Analytics
  • 32 Benefits of Clinical Data Analytics in Quality Care
  • 33 Population Health Management Procedure
  • 34 Benefits of Clinical Data Analytics in Population Health Management
  • 35 Clinical Decision Support Process
  • 36 Benefits of Clinical Decision Support in Big Data Healthcare
  • 37 Benefits of Big Data Analytics in Precision Health
  • 38 Benefits of Big Data Analytics in Reporting and Compliance
  • 39 Financial Analytics Sub-Segments
  • 40 Claims Processing Procedure
  • 41 Benefits of Claims Processing
  • 42 Process for Revenue Cycle Management
  • 43 Steps in Risk Assessment
  • 44 Some Financial Risks Associated with Healthcare Industry
  • 45 Benefits of Big Data Analytics in Risk Assessment
  • 46 Operational Analytics Sub-Segments
  • 47 Important Elements In Workforce Analytics
  • 48 Benefits of Workforce Analytics
  • 49 Process of Supply Chain In Healthcare
  • 50 Benefits of Supply Chain Analytics in Healthcare
  • 51 Global Big Data in Healthcare Market by Region ($Million)
  • 52 Drivers and Challenges in the Healthcare Big Data Analytics Market in North American Region
  • 53 North America Big Data in Healthcare Market by Component ($Million)
  • 54 North America Big Data in Healthcare Market by Application ($Million)
  • 55 North America Big Data in Healthcare Market by Country ($Million)
  • 56 The U.S. Big Data in Healthcare Market, 2016-2025 ($Million)
  • 57 Percentage of Respondents Spending 1-5% of their Operating Budget on Big Data Analytics
  • 58 Top Current and Future Analytics Drivers in the U.S
  • 59 Big Data Analytics Investment Priorities in the U.S. Hospitals
  • 60 Segments Witnessing Early Adoption of Healthcare Analytics in Canada
  • 61 Canada Active EHR Users
  • 62 Current and Future State of Canadian Healthcare Analytics
  • 63 Canada Big Data in Healthcare Market, 2016-2025 ($Million)
  • 64 Total IT Budget as Percentage of Annual Hospital Budget
  • 65 Europe Big Data in Healthcare Market by Components ($Million
  • 66 Europe Big Data in Healthcare Market by Application ($Million)
  • 67 Europe Big Data in Healthcare Market by Country ($Million)
  • 68 The U.K. Big Data in Healthcare Market, 2016-2025 ($Million)
  • 69 France Big Data in Healthcare Market, 2016-2025 ($Million)
  • 70 Spain Big Data in Healthcare Market, 2016-2025 ($Million)
  • 71 Italy Big Data in Healthcare Market, 2016-2025 ($Million)
  • 72 Germany Big Data in Healthcare Market, 2016-2025 ($Million)
  • 73 Others Big Data in Healthcare Market, 2016-2025 ($Million)
  • 74 APAC Big Data in Healthcare Market by Components ($Billion)
  • 75 APAC Big Data in Healthcare Market by Application ($Million)
  • 76 APAC Big Data in Healthcare Market by Country ($Million)
  • 77 Clinical Information System Implementation Rates in China, 2013-2014
  • 78 China Big Data in Healthcare Market, 2016-2025 ($Million)
  • 79 Japan Big Data in Healthcare Market, 2016-2025 ($Million)
  • 80 India Big Data in Healthcare Market, 2016-2025 ($Million)
  • 81 Australia Big Data in Healthcare Market, 2016-2025 ($Million)
  • 82 Others Big Data in Healthcare Market, 2016-2025 ($Million)
  • 83 RoW Big Data in Healthcare Market by Components
  • 84 RoW Big Data in Healthcare Market by Application ($Million)
  • 85 Middle East ad Africa Big Data in Healthcare Market, 2016-2025 ($Million)
  • 86 LATAM Big Data in Healthcare Market, 2016-2025 ($Million)
  • 87 Active Health Management Product Portfolio
  • 88 Aetna Inc.: Overall Financials (2014-2016)
  • 89 Aetna Inc.: Revenue by Business Segment (2014-2016)
  • 90 Aetna Inc.: Revenue by Region (2014-2016)
  • 91 Active Health Management SWOT Analysis
  • 92 Allscripts Healthcare Solutions Inc. Product Portfolio
  • 93 Allscripts Healthcare Solutions, Inc.: Overall Financials (2014-2016)
  • 94 Allscripts Healthcare Solutions, Inc.: Revenue by Region (2014-2016)
  • 95 Allscripts Healthcare Solutions, Inc. Revenue by Business Segment (2014-2016)
  • 96 Allscripts SWOT Analysis
  • 97 Cerner Corporation: Product Portfolio
  • 98 Cerner Corporation: Overall Financials (2014-2016)
  • 99 Cerner Corporation: Net Revenue by Region (2014-2016)
  • 100 Cerner Corporation SWOT Analysis
  • 101 Cognizant Technology Solutions Product Portfolio
  • 102 Cognizant Technology Solutions Corporation Overall Financial (2014-2016)
  • 103 Cognizant Technology Solutions Corporation Net Revenue by Region (2014-2016)
  • 104 Cognizant Technology Solutions Corporation Net Revenue by Business Segment (2014-2016)
  • 105 Cognizant Technology Solutions SWOT Analysis
  • 106 Computer Programs and Systems, Inc. Product Portfolio
  • 107 Computer Programs and Systems, Inc: Overall Financials(2014-2016
  • 108 Computer Programs and Systems,Inc: Revenue by Segment (2014-2016)
  • 109 Computer Programs and systems ,Inc :Revenue(U.S.),2014-2016
  • 110 Computer Programs and systems ,Inc :Revenue(RoW),2014-2016
  • 111 Computer Programs and Systems, Inc. SWOT Analysis
  • 112 Dell: Overall Financials (2014-2016
  • 113 Dell: Net Revenue by Business Segment (2014-2015
  • 114 Dell: Net Revenue by Region (2014-2015)
  • 115 DELL SWOT Analysis
  • 116 Epic Systems Product Portfolio
  • 117 Epic Systems SWOT Analysis
  • 118 eClinicalWorks Product Portfolio
  • 119 eClinicalWorks SWOT Analysis
  • 120 GE Healthcare Product Portfolio
  • 121 GE Corporation: Overall Financials (2014-2016)
  • 122 GE Corporation: Net Revenue by Region (2014-2016)
  • 123 GE Corporation: Net Revenue by Business Segment (2014-2016)
  • 124 GE Corporation: Percentage of Revenues By Healthcare Sub Segments : 2016
  • 125 GE Healthcare SWOT Analysis
  • 126 Health Catalyst Product Portfolio
  • 127 Health Catalyst SWOT Analysis
  • 128 IBM Corporation : Overall Financials (2014-2016)
  • 129 IBM Corporation : Net Revenue by Region (2014-2016)
  • 130 IBM Corporation: Net Revenue by Business Segments (2014-2016)
  • 131 IBM Corporation SWOT Analysis
  • 132 McKesson Corporation Product Portfolio
  • 133 McKesson Corporation: Overall Financials (2015-2017)
  • 134 McKesson Corporation: Net Revenue by Business Segment (2015-2017)
  • 135 McKesson Corporation SWOT Analysis
  • 136 MedeAnalytics Inc. Product Portfolio
  • 137 MedeAnalytics Inc. SWOT Analysis
  • 138 Optum Product Portfolio
  • 139 United Health Group : Overall Financials (2014-2016)
  • 140 United Health Group : Net Revenue by Business Segments (2014-2016)+C27
  • 141 United Health Group : Net Revenue by Business Segment (2014-2016)
  • 142 OPTUM SWOT Analysis
  • 143 Oracle Corporation Product Portfolio
  • 144 Oracle Corporation: Overall Financials (2015-2017)
  • 145 Oracle Corporation Net Revenue by Region (2015-2017)
  • 146 Oracle Corporation Net Revenue by Business Segment (2015-2017)
  • 147 Oracle Corporation SWOT Analysis
  • 148 Philips Healthcare Product Portfolio
  • 149 Philips Healthcare Overall Financials (2015-2017)
  • 150 Philips Healthcare Net Revenue by Region (2015-2017)
  • 151 Philips Healthcare Revenue by Business Segment (2015-2017)
  • 152 Philips Healthcare SWOT Analysis
  • 153 Premier Inc. Product Portfolio
  • 154 Premier Inc.: Overall Financials (2014-2016)
  • 155 Premier Inc. Revenue by Business Segment (2014-2016)
  • 156 Premier Inc. Revenue by Business Segment (2014-2016)
  • 157 Premier Inc. SWOT Analysis
  • 158 SAP Product Portfolio
  • 159 SAP Overall Financials (2015-2017)
  • 160 SAP Net Revenue by Region (2015-2017)
  • 161 SAP Revenue by Business Segment (2015-2017)
  • 162 SAP: Cloud Subscriptions and Support Revenue by Region (2014-2016)
  • 163 SAP: Cloud and Software Revenue by Region (2014-2016)
  • 164 SAP SWOT Analysis
  • 165 SAS Product Portfolio
  • 166 SAS SWOT Analysis
  • 167 Siemens: Product Portfolio
  • 168 Siemens: Overall Financials (2014-2016)
  • 169 Siemens: Net Revenue by Region (2014-2016)
  • 170 Siemens: Net Revenue by Business Segment (2014-2016)
  • 171 Siemens Healthineers SWOT Analysis
  • 172 Tableau Software,Inc. Product Portfolio
  • 173 Tableau Software, Inc.: Overall Financials (2014-2016)
  • 174 Tableau Software, Inc.: Net Revenue by Business Segments (2014-2016)
  • 175 Tableau Software, Inc.: Net Revenue by Region (2014-2016)
  • 176 Tableau Software,Inc. SWOT Analysis
  • 177 Xerox Overall Financials(2014-2016)
  • 178 Xerox Net Revenue by Business Segment (2014-2016)
  • 179 Xerox Net Revenue by Region (2014-2016)
  • 180 Xerox SWOT Analysis
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