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市场调查报告书
商品编码
1423107

2024-2032 年医疗保健大数据分析市场报告（按组件、分析类型、交付模型、应用程式、最终用户和地区）

Healthcare Big Data Analytics Market Report by Component, Analytics Type, Delivery Model, Application, End-User, and Region 2024-2032
出版日期: | 出版商: IMARC | 英文 146 Pages | 商品交期: 2-3个工作天内

价格

2023年，全球医疗保健巨量资料分析市场规模达到418亿美元。展望未来， IMARC Group预计到2032年市场规模将达到1,182亿美元，2024-2032年复合年增长率（CAGR ）为11.9%。由于人们越来越关注加强患者护理和治疗结果、透过电子健康记录 (EHR)、医学影像和基因组资料不断增加的资料量，以及透过整合先进技术来简化医疗保健运营，该市场正在经历稳定增长。

医疗保健大数据分析市场分析：

市场成长与规模：在医疗保健资料量不断增加以及对数据驱动洞察的需求不断增长的推动下，市场正在强劲成长。

技术进步：创新，例如人工智慧 (AI) 支援的诊断和预测分析，以提供个人化建议。此外，云端运算和巨量资料平台正在实现更有效率的资料储存和处理。

产业应用：医疗保健巨量资料分析可应用于临床决策支援、药物研究、人口健康管理和远距医疗。它还有助于疾病追踪、个人化治疗和改善患者治疗结果。

地理趋势：在严格的资料安全和隐私措施的推动下，北美引领市场。然而，由于医疗保健机构越来越关注数据驱动的决策，亚太地区正在成为一个快速成长的市场。

竞争格局：主要参与者正在致力于整合来自不同来源的资料，包括电子健康记录 (EHR)、医疗设备、穿戴式装置和研究资料库，以全面了解病患健康和医疗保健运作。

挑战与机会：虽然市场面临资料安全和隐私问题等挑战，但也遇到了利用资料进行个人化医疗的机会。

未来展望：随着先进技术的日益采用，医疗保健巨量资料分析市场的未来看起来充满希望。此外，对人口健康管理的日益关注预计将促进市场成长。

医疗保健大数据分析市场趋势：

增加资料量

医疗保健产业正在经历大量资料的产生。这包括电子健康记录 (EHR)、医学影像和基因组资料。穿戴式装置的采用不断增加，同时也会产生大量资料。除此之外，传统的资料分析方法还不够。此外，医疗保健组织也意识到需要利用巨量资料分析来改善病患照护、提高营运效率并做出明智的决策。此外，先进的分析工具和技术可以快速处理和分析大型资料集，并提取与临床决策相关的有价值的见解、识别趋势并优化资源分配。除此之外，预测分析可以帮助医院预测病患入院状况，进而改善员工调度和资源管理。此外，大型医院和医疗机构每天都在处理大量资料，包括行政、财务和营运资料。与此一致的是，医疗保健领域对循证决策的日益关注正在促进市场的成长。

先进技术的融合

机器学习（ML）、人工智慧（AI）、区块链、自然语言处理（NLP）、机器人技术和远距医疗以及云端运算等先进技术的集成，以简化医疗保健运营，正在推动市场成长。此外，机器学习演算法可以识别人类分析师可能无法注意到的医疗资料模式。此外，人工智慧驱动的聊天机器人和虚拟助理正在提高患者的参与度并提供个人化的健康建议。人工智慧驱动的影像分析可以高精度检测医学影像中的异常情况，帮助放射科医生诊断癌症或骨折等疾病。除此之外，NLP 演算法还用于从非结构化医疗资料中提取有价值的信息，例如临床记录、医学文献和患者叙述。该技术可以自动处理文字资料，从而更容易将叙述资料纳入分析中。此外，区块链技术有助于增强医疗资料的安全性和完整性。它为健康记录提供了一个安全的分类账，确保病患资料防篡改并且只有授权方可以存取。

更加重视改善患者治疗效果

对加强患者护理和治疗结果的日益关注正在推动市场的成长。与此一致的是，对基于价值的护理的需求增加，因为它的重点是在控製成本的同时改善患者的治疗结果。此外，医疗保健组织越来越多地根据所提供的护理品质而不是所提供的服务数量获得报销。除此之外，巨量资料分析使医疗保健组织能够追踪患者的治疗结果、监控治疗计划的遵守情况，并确定提高品质和降低成本的干预措施。它还透过对患者群体进行细分并针对特定群体制定干预措施来帮助人口健康管理。此外，医疗保健巨量资料分析使医疗保健提供者能够根据大量患者资料做出明智的决策。这些资料分析解决方案有助于分析历史患者资料、治疗效果和临床路径，并允许提供者确定最有效的治疗和介入措施。

目录

第一章：前言

第 2 章：范围与方法

  • 研究目的
  • 利害关係人
  • 资料来源
    • 主要资源
    • 二手资料
  • 市场预测
    • 自下而上的方法
    • 自上而下的方法
  • 预测方法

第 3 章：执行摘要

第 4 章：简介

  • 概述
  • 主要行业趋势

第 5 章：全球医疗保健大数据分析市场

  • 市场概况
  • 市场业绩
  • COVID-19 的影响
  • 市场区隔：依成分
  • 市场区隔：依分析类型
  • 市场区隔：依交付模式
  • 市场区隔：按应用
  • 市场区隔：按最终用户
  • 市场区隔：按地区
  • 市场预测

第 6 章：市场区隔：按组成部分

  • 服务
    • 市场走向
    • 市场预测
  • 软体
    • 市场走向
    • 主要类型
      • 电子健康记录软体
      • 实践管理软体
      • 劳动力管理软体
    • 市场预测
  • 硬体
    • 市场走向
    • 主要类型
      • 资料储存
      • 路由器
      • 防火墙
      • 虚拟私人网路
      • 电子邮件伺服器
      • 其他的
    • 市场预测

第 7 章：市场区隔：按分析类型

  • 描述性分析
    • 市场走向
    • 市场预测
  • 预测分析
    • 市场走向
    • 市场预测
  • 规范性分析
    • 市场走向
    • 市场预测
  • 认知分析
    • 市场走向
    • 市场预测

第 8 章：市场区隔：依交付模式

  • 本地交付模式
    • 市场走向
    • 市场预测
  • 按需交付模式
    • 市场走向
    • 市场预测

第 9 章：市场区隔：按应用

  • 财务分析
    • 市场走向
    • 市场预测
  • 临床分析
    • 市场走向
    • 市场预测
  • 营运分析
    • 市场走向
    • 市场预测
  • 其他的
    • 市场走向
    • 市场预测

第 10 章：市场区隔：依最终用户

  • 医院和诊所
    • 市场走向
    • 市场预测
  • 金融和保险机构
    • 市场走向
    • 市场预测
  • 研究机构
    • 市场走向
    • 市场预测

第 11 章：市场区隔：按地区

  • 北美洲
    • 市场走向
    • 市场预测
  • 欧洲
    • 市场走向
    • 市场预测
  • 亚太地区
    • 市场走向
    • 市场预测
  • 中东和非洲
    • 市场走向
    • 市场预测
  • 拉丁美洲
    • 市场走向
    • 市场预测

第 12 章：SWOT 分析

  • 概述
  • 优势
  • 弱点
  • 机会
  • 威胁

第 13 章：价值链分析

第 14 章：波特的五力分析

  • 概述
  • 买家的议价能力
  • 供应商的议价能力
  • 竞争程度
  • 新进入者的威胁
  • 替代品的威胁

第 15 章：价格分析

第16章：竞争格局

  • 市场结构
  • 关键参与者
  • 关键参与者简介
    • CitiusTech Inc.
    • Cognizant
    • Cotiviti, Inc.
    • ExlService Holdings, Inc.
    • Gainwell Technologies LLC
    • Health Catalyst
    • Hewlett Packard Enterprise Development LP
    • Inovalon
    • Koninklijke Philips NV
    • McKesson Corporation
    • MedeAnalytics, Inc.
    • Optum, Inc.
    • Oracle Corporation
    • SAS Institute Inc.
    • Veradigm LLC
    • Wipro Limited
Product Code: SR112024A1542

Abstract

The global healthcare big data analytics market size reached US$ 41.8 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 118.2 Billion by 2032, exhibiting a growth rate (CAGR) of 11.9% during 2024-2032. The market is experiencing steady growth driven by the growing focus on enhanced patient care and outcomes, rising data volume through electronic health records (EHRs), medical imaging, and genomic data, and integration of advanced technologies to streamline healthcare operations.

Healthcare Big Data Analytics Market Analysis:

Market Growth and Size: The market is witnessing strong growth, driven by the increasing volume of healthcare data, along with the growing demand for data-driven insights.

Technological Advancements: Innovations, such as artificial intelligence (AI)-powered diagnostics and predictive analytics, for personalized recommendations. Moreover, cloud computing and big data platforms are enabling more efficient data storage and processing.

Industry Applications: Healthcare big data analytics finds applications in clinical decision support, pharmaceutical research, population health management, and telemedicine. It also aids in disease tracking, treatment personalization, and improving patient outcomes.

Geographical Trends: North America leads the market, driven by stringent data security and privacy measures. However, Asia Pacific is emerging as a fast-growing market due to the rising focus on data-driven decision-making in healthcare facilities.

Competitive Landscape: Key players are working on integrating data from diverse sources, including electronic health records (EHRs), medical devices, wearables, and research databases, to enable a comprehensive view of patient health and healthcare operations.

Challenges and Opportunities: While the market faces challenges, such as data security and privacy concerns, it also encounters opportunities in utilizing data for personalized medicine.

Future Outlook: The future of the healthcare big data analytics market looks promising, with the increasing adoption of advanced technologies. Additionally, the rising focus on population health management is projected to bolster the market growth.

Healthcare Big Data Analytics Market Trends:

Increasing data volume

The healthcare industry is experiencing a huge volume of data generation. This includes electronic health records (EHRs), medical imaging, and genomic data. There is an increase in the adoption of wearable devices that also generate large amounts of data. Besides this, traditional methods of analyzing data are insufficient. In addition, healthcare organizations are recognizing the need to utilize big data analytics to improve patient care, enhance operational efficiency, and make informed decisions. Moreover, advanced analytics tools and techniques can process and analyze large datasets quickly and extract valuable insights relating to clinical decisions, identify trends, and optimize resource allocation. Apart from this, predictive analytics can help hospitals forecast patient admissions, allowing for improved staff scheduling and resource management. Furthermore, large hospitals and healthcare organizations are handling massive amounts of data daily, including administrative, financial, and operational data. In line with this, the rising focus on evidence-based decision-making in healthcare is contributing to the growth of the market.

Integration of advanced technologies

Integration of advanced technologies, such as machine learning (ML), artificial intelligence (AI), blockchain, natural language processing (NLP), robotics and telemedicine, and cloud computing, to streamline healthcare operations is impelling the market growth. In addition, ML algorithms can identify patterns in medical data that might not be noticeable to human analysts. Moreover, AI-powered chatbots and virtual assistants are improving patient engagement and delivering personalized health recommendations. AI-driven image analysis can detect anomalies in medical images with high accuracy, aiding radiologists in diagnosing conditions like cancer or fractures. Besides this, NLP algorithms are used to extract valuable information from unstructured healthcare data, such as clinical notes, medical literature, and patient narratives. This technology allows for the automated processing of textual data, making it easier to incorporate narrative data into analytics. Furthermore, blockchain technology assists in enhancing the security and integrity of healthcare data. It provides a secure ledger for health records, ensuring that patient data remains tamper-proof and accessible only to authorized parties.

Increasing focus on enhanced patient outcomes

The rising focus on enhanced patient care and outcomes is bolstering the growth of the market. In line with this, there is an increase in the demand for value-based care, as it focuses on achieving improved patient outcomes while controlling costs. Moreover, healthcare organizations are increasingly being reimbursed based on the quality of care delivered, rather than the volume of services provided. Besides this, big data analytics allows healthcare organizations to track patient outcomes, monitor adherence to treatment plans, and identify interventions that improve quality and reduce costs. It also helps in population health management by segmenting patient populations and tailoring interventions to specific groups. Furthermore, healthcare big data analytics enables healthcare providers to make informed decisions based on a wealth of patient data. These data analytics solutions assist in analyzing historical patient data, treatment efficacy, and clinical pathways and allow providers to identify the most effective treatments and interventions.

Healthcare Big Data Analytics Industry Segmentation:

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the global and regional levels for 2024-2032. Our report has categorized the market based on component, analytics type, delivery model, application, and end-user.

Breakup by Component:

Services

Software

Electronic Health Record Software

Practice Management

Workforce Management

Hardware

Data Storage

Routers

Firewalls

Virtual Private Networks

E-Mail Servers

Others

Service accounts for the majority of the market share

The report has provided a detailed breakup and analysis of the market based on the component. This includes service, software (electronic health record software, practice management software, and workforce management software), and hardware (data storage, routers, firewalls, virtual private networks, e-mail servers, and others). According to the report, service represented the largest segment.

Service includes consulting, implementation, maintenance, and support. In addition, consulting services involve assisting healthcare organizations in defining their data analytics strategies, selecting appropriate tools, and optimizing data workflows. Besides this, implementation services focus on the actual deployment of data analytics solutions, including software integration and customization. Furthermore, maintenance and support services ensure the continued operation and performance of data analytics systems.

Software encompasses a wide range of applications, including data analytics platforms, business intelligence tools, and data visualization software. Data analytics platforms benefit in facilitating data processing, analysis, and reporting. Moreover, business intelligence tools enable users to create dashboards and reports for data-driven decision-making. Besides this, data visualization software helps in presenting complex healthcare data in a visually understandable format, aiding in insights discovery.

Hardware includes the physical infrastructure required for data storage and processing. It involves servers, storage systems, and network equipment that support the storage and retrieval of vast healthcare datasets. High-performance computing (HPC) clusters and cloud infrastructure are often used to handle the computational demands of big data analytics.

Breakup by Analytics Type:

Descriptive Analytics

Predictive Analytics

Prescriptive Analytics

Cognitive Analytics

Descriptive analytics holds the largest market share

A detailed breakup and analysis of the market based on the analytics type have also been provided in the report. This includes descriptive analytics, predictive analytics, prescriptive analytics, and cognitive analytics. According to the report, descriptive analytics accounted for the largest market share.

Descriptive analytics involves the examination of historical healthcare data to understand past trends and events. It provides a foundational understanding about patient demographics, treatment outcomes, and resource utilization. Descriptive analytics is widely used for reporting and creating visualizations to communicate insights effectively.

Predictive analytics focuses on forecasting future healthcare events or outcomes based on historical data and statistical modeling. It enables healthcare providers to anticipate patient needs, disease outbreaks, and demands of healthcare resources. Predictive analytics is essential for early disease detection and risk assessment, aiding in preventive care and optimized resource allocation.

Prescriptive analytics goes beyond predicting future events to provide actionable recommendations and solutions. In line with this, it helps healthcare organizations make informed decisions by suggesting suitable courses of action to achieve desired outcomes.

Cognitive analytics combines advanced technologies like artificial intelligence (AI) and natural language processing (NLP) to mimic human thought processes. It can interpret unstructured healthcare data, such as physician notes and patient narratives, to derive insights. Cognitive analytics is used for complex tasks like medical image analysis, clinical decision support, and sentiment analysis of patient feedback.

Breakup by Delivery Model:

On-Premise Delivery Model

On-Demand Delivery Model

On-demand delivery model represents the leading market segment

The report has provided a detailed breakup and analysis of the market based on the delivery model. This includes on-premise delivery model and on-demand delivery model. According to the report, on-demand delivery model represented the largest segment.

On-demand delivery model involves the use of cloud computing infrastructure and services to store, process, and analyze healthcare data. It allows healthcare organizations to access data analytics tools and platforms remotely over the internet, eliminating the need for extensive on-site hardware and software. Cloud-based solutions offer scalability, flexibility, and cost-effectiveness, as healthcare providers can pay for services on a subscription or usage basis.

On-premise delivery model, also known as traditional delivery model, involves the installation and maintenance of data analytics software and infrastructure within the physical premises of a healthcare facility. It allows healthcare organizations to have complete control over their data and analytics systems, ensuring data security and compliance with regulatory requirements. On-premise solutions are suitable for organizations with strict data governance policies or specific security concerns.

Breakup by Application:

Financial Analytics

Clinical Analytics

Operational Analytics

Others

Clinical analytics exhibits a clear dominance in the market

The report has provided a detailed breakup and analysis of the market based on the application. This includes financial analytics, clinical analytics, operational analytics, and others. According to the report, clinical analytics represented the largest segment.

Clinical analytics involves the analysis of healthcare data related to patient care and treatment. It includes the examination of electronic health records (EHRs), medical images, lab results, and patient demographics to improve clinical decision-making. Clinical analytics plays a crucial role in early disease detection, treatment optimization, and personalized medicine.

Financial analytics in healthcare focuses on the management and optimization of financial resources within healthcare organizations. It includes budgeting, revenue cycle management, claims processing, and cost containment. Financial analytics helps healthcare providers maximize revenue, reduce costs, and improve overall financial performance.

Operational analytics focuses on improving the efficiency and effectiveness of healthcare operations. It includes the analysis of data related to hospital logistics, supply chain management, patient flow, and resource allocation. Furthermore, operational analytics helps healthcare organizations streamline processes and enhance operational excellence.

Breakup by End-User:

Hospitals and Clinics

Finance and Insurance Agencies

Research Organizations

Hospitals and clinics represent the biggest market share

The report has provided a detailed breakup and analysis of the market based on the end-user. This includes hospitals and clinics, finance and insurance agencies, and research organizations. According to the report, hospitals and clinics represented the largest segment.

Hospitals and clinics are primary end users of healthcare big data analytics solutions. Healthcare providers in these settings use analytics to improve patient care, optimize resource allocation, and enhance operational efficiency. Analytics applications in this segment include clinical decision support, patient outcomes analysis, and population health management.

Finance and insurance agencies play a vital role in healthcare, managing billing, reimbursement, and insurance claims. These organizations use analytics to assess risk, detect fraud, and ensure accurate financial transactions within the healthcare ecosystem. Financial analytics tools play a crucial role in managing revenue cycles effectively.

Research organizations, including pharmaceutical companies, academic institutions, and research centers, use analytics to increase drug discovery, conduct clinical trials, and analyze healthcare trends. Research organizations rely on advanced analytics, including predictive and cognitive analytics, to extract valuable insights from healthcare data.

Breakup by Region:

North America

Europe

Asia Pacific

Middle East and Africa

Latin America

North America leads the market, accounting for the largest healthcare big data analytics market share

The market research report has also provided a comprehensive analysis of all the major regional markets, which include North America, Europe, Asia Pacific, Middle East and Africa, and Latin America. According to the report, North America accounted for the largest market share due to the presence of improved healthcare infrastructure facilities. In line with this, the rising adoption of big data analytics solutions to manage vast healthcare data, improve patient care, and optimize costs is propelling the market growth. Furthermore, stringent data security and privacy measures in the region are impelling the market growth.

Europe stands as another key region in the market, driven by the increasing focus on data analytics to measure and improve patient outcomes. In addition, the growing demand for advanced data analytics for enhanced healthcare decision-making is offering a positive market outlook in the region.

Asia Pacific maintains a strong presence in the market, with the rising number of research institutions and pharmaceutical companies. Besides this, the increasing need for data security and privacy in healthcare data analytics is supporting the growth of the market. Moreover, the growing focus on data-driven decision-making in healthcare facilities is positively influencing the market.

The Middle East and Africa exhibit growing potential in the healthcare big data analytics market on account of the rising adoption of electronic health records (EHRs), which provide valuable data for analysis. In addition, the growing need for data analytics for risk assessment and intervention planning is offering a positive market outlook.

Latin America region shows a developing market for healthcare big data analytics due to the increasing focus on population health management and preventive care. Apart from this, the rising adoption of electronic health records (EHRs) and telemedicine is strengthening the market growth in the region.

Leading Key Players in the Healthcare Big Data Analytics Industry:

Key players are working on integrating data from diverse sources, including electronic health records (EHRs), medical devices, wearables, and research databases, to enable a comprehensive view of patient health and healthcare operations. Apart from this, companies are investing in the development of advanced analytics tools, including machine learning (ML) algorithms, predictive modeling, natural language processing (NLP), and data visualization software. These tools help in analyzing large healthcare datasets efficiently and extracting actionable insights. Moreover, major players are focusing on providing clinical decision support systems that assist healthcare professionals in making informed decisions about patient care. These systems offer real-time insights, treatment recommendations, and risk assessments.

The market research report has provided a comprehensive analysis of the competitive landscape. Detailed profiles of all major companies have also been provided. Some of the key players in the market include:

CitiusTech Inc.

Cognizant

Cotiviti, Inc.

ExlService Holdings, Inc.

Gainwell Technologies LLC

Health Catalyst

Hewlett Packard Enterprise Development LP

Inovalon

Koninklijke Philips N.V.

McKesson Corporation

MedeAnalytics, Inc.

Optum, Inc.

Oracle Corporation

SAS Institute Inc.

Veradigm LLC

Wipro Limited

(Please note that this is only a partial list of the key players, and the complete list is provided in the report.)

Latest News:

December, 2021: Oracle Corporation acquired Cerner to transform healthcare delivery by providing medical professionals with enhanced information. With this acquisition, Oracle can provide overworked medical professionals with a new generation of easier-to-use digital tools that enable access to information via a hands-free voice interface to secure cloud applications.

Key Questions Answered in This Report

  • 1. What was the size of the global healthcare big data analytics market in 2023?
  • 2. What is the expected growth rate of the global healthcare big data analytics market during 2024-2032?
  • 3. What has been the impact of COVID-19 on the global healthcare big data analytics market?
  • 4. What are the key factors driving the global healthcare big data analytics market?
  • 5. What is the breakup of the global healthcare big data analytics market based on the component?
  • 6. What is the breakup of the global healthcare big data analytics market based on the analytics type?
  • 7. What is the breakup of the global healthcare big data analytics market based on the delivery model?
  • 8. What is the breakup of the global healthcare big data analytics market based on the application?
  • 9. What is the breakup of the global healthcare big data analytics market based on the end-user?
  • 10. What are the key regions in the global healthcare big data analytics market?
  • 11. Who are the key players/companies in the global healthcare big data analytics market?

Table of Contents

1 Preface

2 Scope and Methodology

  • 2.1 Objectives of the Study
  • 2.2 Stakeholders
  • 2.3 Data Sources
    • 2.3.1 Primary Sources
    • 2.3.2 Secondary Sources
  • 2.4 Market Estimation
    • 2.4.1 Bottom-Up Approach
    • 2.4.2 Top-Down Approach
  • 2.5 Forecasting Methodology

3 Executive Summary

4 Introduction

  • 4.1 Overview
  • 4.2 Key Industry Trends

5 Global Healthcare Big Data Analytics Market

  • 5.1 Market Overview
  • 5.2 Market Performance
  • 5.3 Impact of COVID-19
  • 5.4 Market Breakup by Component
  • 5.5 Market Breakup by Analytics Type
  • 5.6 Market Breakup by Delivery Model
  • 5.7 Market Breakup by Application
  • 5.8 Market Breakup by End-User
  • 5.9 Market Breakup by Region
  • 5.10 Market Forecast

6 Market Breakup by Component

  • 6.1 Service
    • 6.1.1 Market Trends
    • 6.1.2 Market Forecast
  • 6.2 Software
    • 6.2.1 Market Trends
    • 6.2.2 Major Types
      • 6.2.2.1 Electronic Health Record Software
      • 6.2.2.2 Practice Management Software
      • 6.2.2.3 Workforce Management Software
    • 6.2.3 Market Forecast
  • 6.3 Hardware
    • 6.3.1 Market Trends
    • 6.3.2 Major Types
      • 6.3.2.1 Data Storage
      • 6.3.2.2 Routers
      • 6.3.2.3 Firewalls
      • 6.3.2.4 Virtual Private Networks
      • 6.3.2.5 E-Mail Servers
      • 6.3.2.6 Others
    • 6.3.3 Market Forecast

7 Market Breakup by Analytics Type

  • 7.1 Descriptive Analytics
    • 7.1.1 Market Trends
    • 7.1.2 Market Forecast
  • 7.2 Predictive Analytics
    • 7.2.1 Market Trends
    • 7.2.2 Market Forecast
  • 7.3 Prescriptive Analytics
    • 7.3.1 Market Trends
    • 7.3.2 Market Forecast
  • 7.4 Cognitive Analytics
    • 7.4.1 Market Trends
    • 7.4.2 Market Forecast

8 Market Breakup by Delivery Model

  • 8.1 On-Premise Delivery Model
    • 8.1.1 Market Trends
    • 8.1.2 Market Forecast
  • 8.2 On-Demand Delivery Model
    • 8.2.1 Market Trends
    • 8.2.2 Market Forecast

9 Market Breakup by Application

  • 9.1 Financial Analytics
    • 9.1.1 Market Trends
    • 9.1.2 Market Forecast
  • 9.2 Clinical Analytics
    • 9.2.1 Market Trends
    • 9.2.2 Market Forecast
  • 9.3 Operational Analytics
    • 9.3.1 Market Trends
    • 9.3.2 Market Forecast
  • 9.4 Others
    • 9.4.1 Market Trends
    • 9.4.2 Market Forecast

10 Market Breakup by End-User

  • 10.1 Hospitals and Clinics
    • 10.1.1 Market Trends
    • 10.1.2 Market Forecast
  • 10.2 Finance and Insurance Agencies
    • 10.2.1 Market Trends
    • 10.2.2 Market Forecast
  • 10.3 Research Organizations
    • 10.3.1 Market Trends
    • 10.3.2 Market Forecast

11 Market Breakup by Region

  • 11.1 North America
    • 11.1.1 Market Trends
    • 11.1.2 Market Forecast
  • 11.2 Europe
    • 11.2.1 Market Trends
    • 11.2.2 Market Forecast
  • 11.3 Asia Pacific
    • 11.3.1 Market Trends
    • 11.3.2 Market Forecast
  • 11.4 Middle East and Africa
    • 11.4.1 Market Trends
    • 11.4.2 Market Forecast
  • 11.5 Latin America
    • 11.5.1 Market Trends
    • 11.5.2 Market Forecast

12 SWOT Analysis

  • 12.1 Overview
  • 12.2 Strengths
  • 12.3 Weaknesses
  • 12.4 Opportunities
  • 12.5 Threats

13 Value Chain Analysis

14 Porter's Five Forces Analysis

  • 14.1 Overview
  • 14.2 Bargaining Power of Buyers
  • 14.3 Bargaining Power of Suppliers
  • 14.4 Degree of Competition
  • 14.5 Threat of New Entrants
  • 14.6 Threat of Substitutes

15 Price Analysis

16 Competitive Landscape

  • 16.1 Market Structure
  • 16.2 Key Players
  • 16.3 Profiles of Key Players
    • 16.3.1 CitiusTech Inc.
    • 16.3.2 Cognizant
    • 16.3.3 Cotiviti, Inc.
    • 16.3.4 ExlService Holdings, Inc.
    • 16.3.5 Gainwell Technologies LLC
    • 16.3.6 Health Catalyst
    • 16.3.7 Hewlett Packard Enterprise Development LP
    • 16.3.8 Inovalon
    • 16.3.9 Koninklijke Philips N.V.
    • 16.3.10 McKesson Corporation
    • 16.3.11 MedeAnalytics, Inc.
    • 16.3.12 Optum, Inc.
    • 16.3.13 Oracle Corporation
    • 16.3.14 SAS Institute Inc.
    • 16.3.15 Veradigm LLC
    • 16.3.16 Wipro Limited

List of Figures

  • Figure 1: Global: Healthcare Big Data Analytics Market: Major Drivers and Challenges
  • Figure 2: Global: Healthcare Big Data Analytics Market: Sales Value (in Billion US$), 2018-2023
  • Figure 3: Global: Healthcare Big Data Analytics Market: Breakup by Component (in %), 2023
  • Figure 4: Global: Healthcare Big Data Analytics Market: Breakup by Analytics Type (in %), 2023
  • Figure 5: Global: Healthcare Big Data Analytics Market: Breakup by Delivery Model (in %), 2023
  • Figure 6: Global: Healthcare Big Data Analytics Market: Breakup by Application (in %), 2023
  • Figure 7: Global: Healthcare Big Data Analytics Market: Breakup by End-User (in %), 2023
  • Figure 8: Global: Healthcare Big Data Analytics Market: Breakup by Region (in %), 2023
  • Figure 9: Global: Healthcare Big Data Analytics Market Forecast: Sales Value (in Billion US$), 2024-2032
  • Figure 10: Global: Healthcare Big Data Analytics Industry: SWOT Analysis
  • Figure 11: Global: Healthcare Big Data Analytics Industry: Value Chain Analysis
  • Figure 12: Global: Healthcare Big Data Analytics Industry: Porter's Five Forces Analysis
  • Figure 13: Global: Healthcare Big Data Analytics (Services) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 14: Global: Healthcare Big Data Analytics (Services) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 15: Global: Healthcare Big Data Analytics (Software) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 16: Global: Healthcare Big Data Analytics (Software) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 17: Global: Healthcare Big Data Analytics (Hardware) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 18: Global: Healthcare Big Data Analytics (Hardware) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 19: Global: Healthcare Big Data Analytics (Descriptive Analytics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 20: Global: Healthcare Big Data Analytics (Descriptive Analytics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 21: Global: Healthcare Big Data Analytics (Predictive Analytics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 22: Global: Healthcare Big Data Analytics (Predictive Analytics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 23: Global: Healthcare Big Data Analytics (Prescriptive Analytics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 24: Global: Healthcare Big Data Analytics (Prescriptive Analytics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 25: Global: Healthcare Big Data Analytics (Cognitive Analytics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 26: Global: Healthcare Big Data Analytics (Cognitive Analytics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 27: Global: Healthcare Big Data Analytics (On-Premise Delivery Model) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 28: Global: Healthcare Big Data Analytics (On-Premise Delivery Model) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 29: Global: Healthcare Big Data Analytics (On-Demand Delivery Model) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 30: Global: Healthcare Big Data Analytics (On-Demand Delivery Model) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 31: Global: Healthcare Big Data Analytics (Financial Analytics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 32: Global: Healthcare Big Data Analytics (Financial Analytics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 33: Global: Healthcare Big Data Analytics (Clinical Analytics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 34: Global: Healthcare Big Data Analytics (Clinical Analytics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 35: Global: Healthcare Big Data Analytics (Operational Analytics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 36: Global: Healthcare Big Data Analytics (Operational Analytics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 37: Global: Healthcare Big Data Analytics (Other Applications) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 38: Global: Healthcare Big Data Analytics (Other Applications) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 39: Global: Healthcare Big Data Analytics (Hospitals and Clinics) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 40: Global: Healthcare Big Data Analytics (Hospitals and Clinics) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 41: Global: Healthcare Big Data Analytics (Finance and Insurance Agencies) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 42: Global: Healthcare Big Data Analytics (Finance and Insurance Agencies) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 43: Global: Healthcare Big Data Analytics (Research Organizations) Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 44: Global: Healthcare Big Data Analytics (Research Organizations) Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 45: North America: Healthcare Big Data Analytics Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 46: North America: Healthcare Big Data Analytics Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 47: Europe: Healthcare Big Data Analytics Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 48: Europe: Healthcare Big Data Analytics Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 49: Asia Pacific: Healthcare Big Data Analytics Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 50: Asia Pacific: Healthcare Big Data Analytics Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 51: Middle East and Africa: Healthcare Big Data Analytics Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 52: Middle East and Africa: Healthcare Big Data Analytics Market Forecast: Sales Value (in Million US$), 2024-2032
  • Figure 53: Latin America: Healthcare Big Data Analytics Market: Sales Value (in Million US$), 2018 & 2023
  • Figure 54: Latin America: Healthcare Big Data Analytics Market Forecast: Sales Value (in Million US$), 2024-2032

List of Tables

  • Table 1: Global: Healthcare Big Data Analytics Market: Key Industry Highlights, 2023 & 2032
  • Table 2: Global: Healthcare Big Data Analytics Market Forecast: Breakup by Component (in Million US$), 2024-2032
  • Table 3: Global: Healthcare Big Data Analytics Market Forecast: Breakup by Analytics Type (in Million US$), 2024-2032
  • Table 4: Global: Healthcare Big Data Analytics Market Forecast: Breakup by Delivery Model (in Million US$), 2024-2032
  • Table 5: Global: Healthcare Big Data Analytics Market Forecast: Breakup by Application (in Million US$), 2024-2032
  • Table 6: Global: Healthcare Big Data Analytics Market Forecast: Breakup by End-User (in Million US$), 2024-2032
  • Table 7: Global: Healthcare Big Data Analytics Market Forecast: Breakup by Region (in Million US$), 2024-2032
  • Table 8: Global: Healthcare Big Data Analytics Market Structure
  • Table 9: Global: Healthcare Big Data Analytics Market: Key Players