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ビッグデータ＆アナリティクス・ヘルスケアの世界市場-2024～2031年

Global Big Data & Analytics Healthcare Market - 2024-2031

出版日
ページ情報
英文 176 Pages
納期
即日から翌営業日
カスタマイズ可能
適宜更新あり
価格
価格表記: USDを日本円(税抜)に換算
本日の銀行送金レート: 1USD=146.99円
ビッグデータ＆アナリティクス・ヘルスケアの世界市場-2024～2031年
出版日: 2024年12月04日
発行: DataM Intelligence
ページ情報: 英文 176 Pages
納期: 即日から翌営業日
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  • 概要
  • 目次
概要

概要

世界のビッグデータ＆アナリティクス・ヘルスケア市場は、2023年に336億米ドルに達し、2031年には1,109億9,000万米ドルに達すると予測され、予測期間2024-2031年のCAGRは16.2%で成長する見込みです。

ビッグデータ＆アナリティクス・ヘルスケアとは、医療システム、機器、患者から生成される大規模かつ多様なデータセットを体系的に収集、統合、分析し、臨床および業務上の意思決定を改善することを指します。この分野は、機械学習、人工知能（AI）、予測モデリングなどの先進技術を活用し、患者ケアの強化、ヘルスケア業務の最適化、医療イノベーションの推進を目的とした実用的な洞察を導き出します。ビッグデータ解析は、精密医療を可能にし、コストを削減し、患者の転帰を改善し、慢性疾患の管理やパンデミック時の資源配分といった世界の健康課題に取り組むことで、ヘルスケアを変革します。

ビッグデータ＆アナリティクス・ヘルスケア市場の需要は、テクノロジーの進歩、電子カルテ（EHR）の普及拡大、より効率的なヘルスケア管理の必要性などを背景に、急速に拡大しています。例えば、国立衛生研究所によると、ビッグデータの80%増加はクラウドソース、ビッグデータ分析、モバイル技術、ソーシャルメディア技術によるものであると記録されています。この成長は、患者の転帰を改善し、コストを削減し、ヘルスケア環境における業務効率を最適化するためのアナリティクスへの依存度が高まっていることを反映しています。

市場力学：

促進要因と阻害要因

ヘルスケアデータ量の増加

ヘルスケアデータ量の増加は、ビッグデータ＆アナリティクス・ヘルスケア市場の成長を大きく後押ししており、予測期間中も市場を牽引すると予想されます。ヘルスケアシステムがデジタル化し、より高度なテクノロジーを採用するにつれて、さまざまなプラットフォームで生成されるデータ量が急増しています。このデータ量の増加は、患者ケアの改善、業務の最適化、コスト削減のための貴重な洞察を抽出できる高度な分析ツールに対する大きな需要を生み出しています。例えば、デラウェア大学によると、米国病院協会は2020年の報告書の中で、ヘルスケア分野では年間約2,314エクサバイトのデータが生成されていると指摘しています。

EHRの世界の普及がデータ増加に大きく貢献しています。米国医療情報技術調整官（National Coordinator for Health Information Technology）によると、2021年時点で、米国の診療所医師のほぼ10人に9人（88％）が何らかの電子カルテ（EHR）を採用し、ほぼ5人に4人（78％）が認証済みのHERを採用しており、デジタルで保存されアクセスされる患者データが大幅に増加しています。患者の病歴、診断、治療、投薬などを含むこのデータは、ビッグデータ分析ツールの基盤となり、ヘルスケアプロバイダーが個別化されたケアを提供し、臨床転帰を改善するのに役立っています。

さらに、データに基づく洞察は、ヘルスケアの効率を改善するために不可欠です。大規模なデータセットに依存する予測分析は、患者の入院を予測し、再入院を防ぎ、資源配分を最適化することができます。例えば、病院の再入院はヘルスケアシステムにとって大きなコストです。ビッグデータツールは、リスクの高い患者を特定する予測モデルを通じて、こうした再入院を減らすために採用されています。

データ管理の複雑さ

データ管理の複雑さは、複数のソースからの膨大で多様なデータセットの取り扱い、統合、分析に課題があるため、ビッグデータ＆アナリティクス・ヘルスケア市場の成長を著しく阻害します。この複雑さが非効率、データのサイロ化、コスト増を招き、市場の普及を遅らせています。

ヘルスケアデータはEHR、ウェアラブル、医療用画像、IoT機器から生成されるが、構造化データと非構造化データの統合は依然として大きな課題です。例えば、米国国立衛生研究所（NIH）によると、ヘルスケアにおけるデジタルデータの80％以上は非構造化データとして利用可能であり、医療研究者にとって困難な新しい形式のデータ処理と標準化が必要です。これにより、実用的な洞察が制限され、意思決定が遅れます。

ヘルスケア組織は、米国のHIPAAや欧州のGDPRなどの規制により、患者データのセキュリティを優先しており、データの共有と管理をより複雑にしています。情報漏えいは信頼をさらに損ない、組織がアナリティクス・ツールを全面的に採用する意欲をそぐ。

例えば、HIPAAジャーナルによると、2023年8月には2,300万件のヘルスケア記録の漏洩が注目されています。過去12ヶ月間、毎月平均9,989,003件のヘルスケア記録が漏洩しています。さらに、コロラド州を拠点とする病理学研究所は、米国連邦規制当局に報告された医療検査機関としては最大規模の情報漏洩の1つである、180万人以上の患者に対して機密情報が漏洩したことを通知しており、ヘルスケア業界はハッカーにとって特に脆弱な業界となっています。

目次

第1章 調査手法と調査範囲

第2章 定義と概要

第3章 エグゼクティブサマリー

第4章 市場力学

  • 影響要因
    • 促進要因
      • ヘルスケアデータの増加
      • 価値に基づくケアへの移行
    • 抑制要因
      • データ管理の複雑さ
    • 機会
    • 影響分析

第5章 産業分析

  • ポーターのファイブフォース分析
  • サプライチェーン分析
  • 価格分析
  • 特許分析
  • 規制分析
  • SWOT分析
  • アンメットニーズ

第6章 コンポーネント別

  • ソフトウェア
  • ハードウェア
  • サービス

第7章 分析タイプ別

  • 予測分析
  • 記述的分析
  • 診断分析
  • 処方的分析
  • その他

第8章 展開モード別

  • オンプレミス
  • クラウドベース

第9章 用途別

  • 臨床分析
  • 財務分析
  • 運用分析
  • 不正行為の検出とリスク管理
  • その他

第10章 エンドユーザー別

  • 製薬・バイオテクノロジー企業
  • 病院と診療所
  • 金融・保険代理店
  • 調査機関

第11章 地域別

  • 北米
    • 米国
    • カナダ
    • メキシコ
  • 欧州
    • ドイツ
    • 英国
    • フランス
    • スペイン
    • イタリア
    • その他欧州地域
  • 南米
    • ブラジル
    • アルゼンチン
    • その他南米
  • アジア太平洋地域
    • 中国
    • インド
    • 日本
    • 韓国
    • その他アジア太平洋地域
  • 中東・アフリカ

第12章 競合情勢

  • 競合シナリオ
  • 市況・シェア分析
  • M&A分析

第13章 企業プロファイル

  • IBM
    • 会社概要
    • 製品ポートフォリオと概要
    • 財務概要
    • 主な発展
  • Koninklijke Philips N.V.
  • Optum, Inc.
  • FLATIRON HEALTH
  • Health Catalyst
  • Microsoft
  • Oracle
  • Google
  • Wipro
  • Cisco Systems, Inc.（LIST NOT EXHAUSTIVE）

第14章 付録

目次
Product Code: HCIT8850

Overview

The global big data & analytics healthcare market reached US$ 33.60 billion in 2023 and is expected to reach US$ 110.99 billion by 2031, growing at a CAGR of 16.2% during the forecast period 2024-2031.

Big data & analytics healthcare refers to the systematic collection, integration and analysis of large and diverse datasets generated by healthcare systems, devices and patients to improve clinical and operational decision-making. This field leverages advanced technologies, such as machine learning, artificial intelligence (AI) and predictive modeling, to derive actionable insights aimed at enhancing patient care, optimizing healthcare operations and driving medical innovation. Big data analytics transforms healthcare by enabling precision medicine, reducing costs, improving patient outcomes and addressing global health challenges, such as chronic disease management and resource allocation during pandemics.

The demand for big data and analytics healthcare market is growing rapidly, driven by advancements in technology, increasing adoption of electronic health records (EHRs) and the need for more efficient healthcare management. For instance, according to the National Institute of Health, it was recorded that an 80% increase in big data is due to cloud sources, big data analytics, mobile technology and social media technologies. This growth reflects the rising reliance on analytics for improving patient outcomes, reducing costs and optimizing operational efficiency in healthcare settings.

Market Dynamics: Drivers & Restraints

Rising volume of healthcare data

The rising volume of healthcare data is significantly driving the growth of the big data & analytics healthcare market and is expected to drive the market over the forecast period. As healthcare systems digitize and adopt more advanced technologies, the amount of data generated across various platforms has surged. This growing volume of data creates a significant demand for sophisticated analytics tools capable of extracting valuable insights to improve patient care, optimize operations and reduce costs. For instance, according to the University of Delaware, in a 2020 report, the American Hospital Association noted that the healthcare field generates approximately 2,314 exabytes of data annually.

The global adoption of EHRs has become a key contributor to data growth. According to the National Coordinator for Health Information Technology, as of 2021, nearly 9 in 10 (88%) of U.S. office-based physicians adopted any electronic health record (EHR) and nearly 4 in 5 (78%) had adopted a certified HER, leading to a massive increase in patient data being stored and accessed digitally. This data, including patient history, diagnoses, treatments and medications, serves as the foundation for Big Data analytics tools, which help healthcare providers to deliver personalized care and improve clinical outcomes.

Additionally, data-driven insights are critical for improving healthcare efficiency. Predictive analytics, which relies on large datasets, can forecast patient admissions, prevent readmissions and optimize resource allocation. For instance, hospital readmissions are a significant cost to the healthcare system. Big data tools are being employed to reduce these readmissions through predictive models that identify high-risk patients.

Complexity of data management

The complexity of data management significantly hampers the growth of the big data & analytics healthcare market due to challenges in handling, integrating and analyzing vast, diverse datasets from multiple sources. This complexity leads to inefficiencies, data silos and increased costs, slowing market adoption.

Healthcare data is generated from EHRs, wearables, medical imaging and IoT devices, but integrating structured and unstructured data remains a significant challenge. For instance, according to the National Institute of Health (NIH), over 80% of digital data in healthcare is available as unstructured data, requiring new forms of data processing and standardizing that prove challenging to health researchers. This limits actionable insights and delays decision-making.

Healthcare organizations prioritize patient data security due to regulations like HIPAA in the U.S. and GDPR in Europe, making data sharing and management more complex. Breaches further erode trust, discouraging organizations from fully adopting analytics tools.

For instance, according to the HIPAA Journal, in August 2023, 23 million breached healthcare records are noticed. Over the past 12 months, an average of 9,989,003 healthcare records were breached each month. Additionally, a Colorado-based pathology laboratory is notifying more than 1.8 million patients that their sensitive information was compromised one of the largest breaches reported by a medical testing lab to US federal regulators, making the healthcare industry especially vulnerable to hackers.

Segment Analysis

The global big data & analytics healthcare market is segmented based on component, analytics type, deployment mode, application, end-user and region.

Analytics Type:

The predictive analytics segment is expected to dominate the global big data & analytics healthcare market share

The predictive analytics segment is expected to dominate the big data & analytics healthcare market share over the forecast period due to its transformative ability to anticipate future trends, risks and health outcomes. Predictive analytics uses historical and real-time data combined with machine learning algorithms to forecast potential health events, improve patient care, optimize operations and reduce costs.

For instance, in October 2024, Clarify Health launched the industry's first AI-powered predictive analytics, Clarify Performance IQ Suite, that spans cost, quality and utilization assessment to deliver opportunity analytics. Leveraging advanced machine learning and natural language processing, the Performance IQ Suite empowers health plans and others with unparalleled insights to contain costs, improve care quality and gain a competitive edge.

Predicting readmissions is one of the most common applications. Hospitals use predictive models to assess the likelihood of a patient being readmitted within 30 days of discharge. These models use factors like age, medical history and current health status to predict readmission risks. For instance, Corewell Health care coordinators shared that a recent initiative, which uses predictive analytics to forecast risk and reduce readmissions, has kept 200 patients from being readmitted and resulted in a $5 million cost savings.

North America is expected to hold a significant position in the global Big Data & Analytics healthcare market

North America region is expected to hold the largest market share over the forecast period. North America, especially the United States boasts one of the most sophisticated healthcare systems in the world, with widespread adoption of Electronic Health Records (EHRs), telemedicine and health data management systems. For instance, according to Oxford Academic, the study found that basic EHR adoption in the US surged from 6.6% to 81.2, creating a vast pool of structured and unstructured healthcare data that drives demand for analytics tools.

North America is home to many of the world's leading technology companies offering big data & analytics solutions in healthcare. Key players like IBM Watson Health and other local key players in the United States have been at the forefront of developing analytics tools for healthcare.

For instance, in November 2023, Cercle.ai, Inc., a new AI company focused on advancing healthcare for women, launched out of stealth. Leveraging AI, the Cercle Biomedical Graph platform collects billions of de-identified biomedical and genomics data points drawn securely from healthcare clinics and research labs around the world. It then converts often unstructured, fragmented clinical data into insights for researchers and providers.

Asia Pacific is growing at the fastest pace in the Big Data & Analytics healthcare market

The Asia Pacific region is experiencing the fastest growth in the big data & analytics healthcare market. Many Asia Pacific countries are undergoing a digital transformation in healthcare, with governments pushing for digitization of healthcare records, telemedicine adoption and smart health initiatives. Countries like China, India and Singapore have implemented national strategies to boost healthcare IT infrastructure and integrate advanced technologies, including big data analytics.

For instance, in China, the government's Healthy China 2030 initiative is driving the use of health data analytics, including the integration of electronic health records (EHRs) and wearable devices across hospitals.

The APAC region is seeing an expansion in healthcare IT infrastructure, including the adoption of cloud computing, AI, machine learning and IoT devices. These technologies generate large volumes of data that can be analyzed to improve healthcare services.

For instance, in January 2024, GenepoweRx launched an AI platform GeneConnectRx, for big data analytics and drug discovery. This revolutionary step in personalized medicine marks a paradigm shift, empowering healthcare providers to customize treatments based on individual genetic makeup. GeneConnectRx integrates internal data, global resources, and cutting-edge models to forecast potential molecules for revolutionary drug discovery.

Competitive Landscape

The major global players in the big data & analytics healthcare market include IBM, Koninklijke Philips N.V., Optum, Inc., FLATIRON HEALTH, Health Catalyst, Microsoft, Oracle, Google, Wipro, Cisco Systems, Inc. and among others.

Why Purchase the Report?

  • Pipeline & Innovations: Reviews ongoing clinical trials, product pipelines, and forecasts upcoming advancements in medical devices and pharmaceuticals.
  • Product Performance & Market Positioning: Analyzes product performance, market positioning, and growth potential to optimize strategies.
  • Real-World Evidence: Integrates patient feedback and data into product development for improved outcomes.
  • Physician Preferences & Health System Impact: Examines healthcare provider behaviors and the impact of health system mergers on adoption strategies.
  • Market Updates & Industry Changes: Covers recent regulatory changes, new policies, and emerging technologies.
  • Competitive Strategies: Analyzes competitor strategies, market share, and emerging players.
  • Pricing & Market Access: Reviews pricing models, reimbursement trends, and market access strategies.
  • Market Entry & Expansion: Identifies optimal strategies for entering new markets and partnerships.
  • Regional Growth & Investment: Highlights high-growth regions and investment opportunities.
  • Supply Chain Optimization: Assesses supply chain risks and distribution strategies for efficient product delivery.
  • Sustainability & Regulatory Impact: Focuses on eco-friendly practices and evolving regulations in healthcare.
  • Post-market Surveillance: Uses post-market data to enhance product safety and access.
  • Pharmacoeconomics & Value-Based Pricing: Analyzes the shift to value-based pricing and data-driven decision-making in R&D.

The global big data & analytics healthcare market report delivers a detailed analysis with 60+ key tables, more than 50 visually impactful figures, and 176 pages of expert insights, providing a complete view of the market landscape.

Target Audience 2023

  • Manufacturers: Pharmaceutical, Medical Device, Biotech Companies, Contract Manufacturers, Distributors, Hospitals.
  • Regulatory & Policy: Compliance Officers, Government, Health Economists, Market Access Specialists
  • Technology & Innovation: AI/Robotics Providers, R&D Professionals, Clinical Trial Managers, Pharmacovigilance Experts.
  • Investors: Healthcare Investors, Venture Fund Investors, Pharma Marketing & Sales.
  • Consulting & Advisory: Healthcare Consultants, Industry Associations, Analysts.
  • Supply Chain: Distribution and Supply Chain Managers.
  • Consumers & Advocacy: Patients, Advocacy Groups, Insurance Companies.
  • Academic & Research: Academic Institutions.

Table of Contents

1. Methodology and Scope

  • 1.1. Research Methodology
  • 1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

  • 3.1. Snippet by Component
  • 3.2. Snippet by Analytics Type
  • 3.3. Snippet by Deployment Mode
  • 3.4. Snippet by Application
  • 3.5. Snippet by End-User
  • 3.6. Snippet by Region

4. Dynamics

  • 4.1. Impacting Factors
    • 4.1.1. Drivers
      • 4.1.1.1. Rising Volume of Healthcare Data
      • 4.1.1.2. Shift Towards Value-Based Care
    • 4.1.2. Restraints
      • 4.1.2.1. Complexity of Data Management
    • 4.1.3. Opportunity
    • 4.1.4. Impact Analysis

5. Industry Analysis

  • 5.1. Porter's Five Force Analysis
  • 5.2. Supply Chain Analysis
  • 5.3. Pricing Analysis
  • 5.4. Patent Analysis
  • 5.5. Regulatory Analysis
  • 5.6. SWOT Analysis
  • 5.7. Unmet Needs

6. By Component

  • 6.1. Introduction
    • 6.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 6.1.2. Market Attractiveness Index, By Component
  • 6.2. Software*
    • 6.2.1. Introduction
    • 6.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 6.3. Hardware
  • 6.4. Services

7. By Analytics Type

  • 7.1. Introduction
    • 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Analytics Type
    • 7.1.2. Market Attractiveness Index, By Analytics Type
  • 7.2. Predictive Analytics*
    • 7.2.1. Introduction
    • 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 7.3. Descriptive Analytics
  • 7.4. Diagnostic Analytics
  • 7.5. Prescriptive Analytics
  • 7.6. Others

8. By Deployment Mode

  • 8.1. Introduction
    • 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 8.1.2. Market Attractiveness Index, By Deployment Mode
  • 8.2. On-Premises*
    • 8.2.1. Introduction
    • 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 8.3. Cloud-Based

9. By Application

  • 9.1. Introduction
    • 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 9.1.2. Market Attractiveness Index, By Application
  • 9.2. Clinical Analytics*
    • 9.2.1. Introduction
    • 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 9.3. Financial Analytics
  • 9.4. Operational Analytics
  • 9.5. Fraud Detection and Risk Management
  • 9.6. Others

10. By End-User

  • 10.1. Introduction
    • 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 10.1.2. Market Attractiveness Index, By End-User
  • 10.2. Pharmaceutical and Biotechnology Companies*
    • 10.2.1. Introduction
    • 10.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
  • 10.3. Hospitals and Clinics
  • 10.4. Finance and Insurance Agencies
  • 10.5. Research Organizations

11. By Region

  • 11.1. Introduction
    • 11.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
    • 11.1.2. Market Attractiveness Index, By Region
  • 11.2. North America
    • 11.2.1. Introduction
    • 11.2.2. Key Region-Specific Dynamics
    • 11.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Analytics Type
    • 11.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.2.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.2.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.2.8.1. U.S.
      • 11.2.8.2. Canada
      • 11.2.8.3. Mexico
  • 11.3. Europe
    • 11.3.1. Introduction
    • 11.3.2. Key Region-Specific Dynamics
    • 11.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Analytics Type
    • 11.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.3.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.3.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.3.8.1. Germany
      • 11.3.8.2. U.K.
      • 11.3.8.3. France
      • 11.3.8.4. Spain
      • 11.3.8.5. Italy
      • 11.3.8.6. Rest of Europe
  • 11.4. South America
    • 11.4.1. Introduction
    • 11.4.2. Key Region-Specific Dynamics
    • 11.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Analytics Type
    • 11.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.4.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.4.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.4.8.1. Brazil
      • 11.4.8.2. Argentina
      • 11.4.8.3. Rest of South America
  • 11.5. Asia-Pacific
    • 11.5.1. Introduction
    • 11.5.2. Key Region-Specific Dynamics
    • 11.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Analytics Type
    • 11.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.5.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
    • 11.5.8. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
      • 11.5.8.1. China
      • 11.5.8.2. India
      • 11.5.8.3. Japan
      • 11.5.8.4. South Korea
      • 11.5.8.5. Rest of Asia-Pacific
  • 11.6. Middle East and Africa
    • 11.6.1. Introduction
    • 11.6.2. Key Region-Specific Dynamics
    • 11.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Component
    • 11.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Analytics Type
    • 11.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By Deployment Mode
    • 11.6.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
    • 11.6.7. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

12. Competitive Landscape

  • 12.1. Competitive Scenario
  • 12.2. Market Positioning/Share Analysis
  • 12.3. Mergers and Acquisitions Analysis

13. Company Profiles

  • 13.1. IBM*
    • 13.1.1. Company Overview
    • 13.1.2. Product Portfolio and Description
    • 13.1.3. Financial Overview
    • 13.1.4. Key Developments
  • 13.2. Koninklijke Philips N.V.
  • 13.3. Optum, Inc.
  • 13.4. FLATIRON HEALTH
  • 13.5. Health Catalyst
  • 13.6. Microsoft
  • 13.7. Oracle
  • 13.8. Google
  • 13.9. Wipro
  • 13.10. Cisco Systems, Inc. (LIST NOT EXHAUSTIVE)

14. Appendix

  • 14.1. About Us and Services
  • 14.2. Contact Us