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市场调查报告书
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1738541

2026 年至 2032 年医疗数据分析市场（按类型、应用、组件、部署、最终用户和地区划分）

Healthcare Data Analytics Market By Type, Application, Component, Deployment, End-Users, Region for 2026-2032
出版日期: | 出版商: Verified Market Research | 英文 202 Pages | 商品交期: 2-3个工作天内

价格
简介目录

医疗数据分析市场评估-2026-2032

EHR 的广泛采用导致了大量数位健康数据的产生，需要高级电子健康记录，预计这将推动市场在 2024 年超过 328.7 亿美元，到 2032 年达到 1735.7 亿美元的估值。

从按服务收费模式转向基于价值的医疗模式的转变，需要以数据主导的决策，以改善疗效并降低成本。因此，增加对以金额为准的医疗的关注度，将推动市场在2026年至2032年期间实现23.12%的复合年增长率。

医疗数据分析市场定义/概述

医疗数据分析涉及检查和解读大量医疗数据，以得出切实可行的见解。医疗数据分析利用先进的统计模型和机器学习演算法，被动分析来自电子健康记录(EHR)、保险理赔和病患调查等来源的资料。这些洞察有助于医疗服务提供者改善患者照护、简化业务并预测潜在的健康风险。

这个分析流程能够识别医疗服务中的模式和趋势，从而帮助做出更明智的决策并制定个人化治疗方案。它有助于更早发现疾病，加强预防保健，优化资源配置，最终降低营运成本。透过识别效率低下和有待改进的领域，医疗机构可以提升服务品质和病患治疗效果。

慢性病的增加以及人工智慧 (AI) 和机器学习 (ML) 的进步将如何推动医疗数据分析市场的成长？

慢性病的增加推动了对预测分析和人口健康管理的需求。根据美国疾病管制与预防中心 (CDC) 的数据，截至 2022 年，美国美国中将有 6 人患有慢性病，每 10 人中将有 4 人患有两种或两种以上的慢性病。人工智慧 (AI) 和机器学习 (ML) 技术正在增强医疗数据分析的能力，从而带来更深入的见解。美国医院协会 (AHA) 2021 年的一项调查发现，67% 的医院正在使用或计划在未来一年内使用人工智慧来支援临床决策。

抑制医疗成本上涨的需求推动了数据分析在成本优化和资源配置的应用。根据美国医疗保险和医疗补助服务中心 (CMS) 的数据，美国全国医疗保健支出增加了 9.7%，2020 年达到 4.1 兆美元，占 GDP 的 19.7%。医疗技术领域的资金和投资不断增加，推动了数据分析市场的成长。根据美国国家卫生资讯科技协调办公室 (ONC) 的数据，截至 2021 年，96% 的非联邦急诊医院已实施经过认证的 EHR 技术。美国医疗保险和医疗补助服务中心 (CMS) 报告称，2022 年将有 1,100 万名受益人加入 Medicare Advantage 价值型医疗模式，比 2021 年增长 9.4%。

资料安全和隐私问题将如何阻碍医疗资料分析市场的成长？

美国《健康保险流通与责任法》等对病患资料隐私的严格规定，使组织难以自由地共用和分析资料。在强有力的安全措施与方便资料存取以进行分析之间取得平衡仍然是一个复杂的问题。根据美国卫生与公众服务部民权办公室的数据，2020 年发生了 642 起医疗保健资料外洩事件，影响了 500 多笔记录，共超过 2,900 万笔个人记录。缺乏具备医疗保健领域知识的合格数据科学家和分析师，限制了该行业充分利用数据分析的能力。在美国医疗保健资讯管理协会 (AHIMA) 2021 年的一项调查中，59% 的医疗保健组织表示他们难以招募到合格的医疗保健资讯专业人员。

不同的医疗IT系统无法无缝交换数据，阻碍了整个医疗生态系统的全面数据分析。 2022年，美国国家健康资讯科技协调员办公室 (ONC) 报告称，只有55%的医院能够将外部来源的病患资料整合到其电子健康记录 (EHR) 系统中，而无需人工输入。进阶分析工具和基础设施所需的大量前期投资可能是一个障碍，尤其对于规模较小的医疗机构。根据美国医疗保健财务管理协会 (HFMA) 2020年的报告，中型医院实施一套全面的医疗分析系统的平均成本在200万美元到1000万美元之间。

目录

第一章 全球医疗数据分析市场简介

  • 市场概览
  • 研究范围
  • 先决条件

第二章执行摘要

第三章：已验证的市场研究调查方法

  • 资料探勘
  • 验证
  • 第一手资料
  • 资料来源列表

第四章 全球医疗数据分析市场展望

  • 概述
  • 市场动态
    • 驱动程式
    • 限制因素
    • 机会
  • 波特五力模型
  • 价值链分析

第五章全球医疗数据分析市场（按类型）

  • 概述
  • 说明分析
  • 预测分析
  • 说明分析

第六章全球医疗数据分析市场（按组成部分）

  • 概述
  • 软体
  • 硬体
  • 服务

第七章全球医疗数据分析市场（按部署）

  • 概述
  • 本地
  • 网站託管
  • 云端基础

第 8 章全球医疗数据分析市场（按最终用户）

  • 概述
  • 医疗保健提供者
  • 医疗保健提供者
  • 生命科学公司

第九章全球医疗数据分析市场（按地区）

  • 概述
  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 法国
    • 其他欧洲国家
  • 亚太地区
    • 中国
    • 日本
    • 印度
    • 其他亚太地区
  • 其他的
    • 拉丁美洲
    • 中东和非洲

第十章全球医疗数据分析市场的竞争格局

  • 概述
  • 各公司市场排名
  • 重点发展策略

第十一章 公司简介

  • Allscripts
  • Cerner
  • Health Catalyst
  • IBM
  • Inovalon
  • McKesson
  • MedeAnalytics
  • Optum
  • Oracle
  • Wipro
  • Verscend
  • Verscend
  • CitusTech
  • Cerner Corporation
  • Koninklijke Philips NV

第十二章 重大进展

  • 产品发布/开发
  • 合併与收购
  • 业务扩展
  • 伙伴关係与合作

第十三章 附录

  • 相关调查
简介目录
Product Code: 60349

Healthcare Data Analytics Market Valuation - 2026-2032

The widespread implementation of EHRs has created vast amounts of digital health data, driving the need for advanced analytics. Thus, the rising adoption of electronic health records surged the growth of market size surpassing USD 32.87 Billion in 2024 to reach a valuation of USD 173.57 Billion by 2032.

The shift from fee-for-service to value-based care models necessitates data-driven decision-making to improve outcomes and reduce costs. Thus, the increasing focus on value-based care enables the market to grow at a CAGR of 23.12% from 2026 to 2032.

Healthcare Data Analytics Market: Definition/ Overview

Healthcare data analytics involves the process of examining and interpreting large volumes of medical data to derive actionable insights. By utilizing advanced statistical models and machine learning algorithms, healthcare data analytics passively analyzes data from sources such as electronic health records (EHRs), insurance claims, and patient surveys. These insights help healthcare providers improve patient care, streamline operations, and forecast potential health risks.

This analytical process identifies patterns and trends in healthcare delivery, allowing for more informed decision-making and personalized treatment plans. It supports the early detection of medical conditions, enhances preventive care, and helps optimize resource allocation, which can reduce operational costs. By identifying inefficiencies and areas for improvement, healthcare institutions can improve service quality and patient outcomes.

How the Growing Prevalence of Chronic Diseases and Advancements in Artificial Intelligence (AI) and Machine Learning (ML) Surge the Growth of the Healthcare Data Analytics Market?

The rise in chronic conditions is driving the need for predictive analytics and population health management. In The Centers for Disease Control and Prevention (CDC) stated that as of 2022, 6 in 10 adults in the US had a chronic disease, and 4 in 10 had two or more. AI and ML technologies are enhancing the capabilities of healthcare data analytics, enabling more sophisticated insights. A 2021 survey by the American Hospital Association (AHA) found that 67% of hospitals were using or planning to use AI to support clinical decision-making within the next year.

The need to control rising healthcare expenses is driving the adoption of data analytics for cost optimization and resource allocation. According to the Centers for Medicare & Medicaid Services (CMS), national health spending in the US grew 9.7% to reach USD 4.1 Trillion in 2020, accounting for 19.7% of GDP. Increased funding and investment in healthcare technology are fueling the growth of the data analytics market. According to the Office of the National Coordinator for Health Information Technology (ONC), as of 2021, 96% of all non-federal acute care hospitals had adopted certified EHR technology. The Centers for Medicare & Medicaid Services (CMS) reported that in 2022, 11 million beneficiaries were enrolled in Medicare Advantage value-based care models, representing a 9.4% increase from 2021.

How the Data Security and Privacy Concerns Impede the Growth of the Healthcare Data Analytics Market?

Stringent regulations regarding patient data privacy, like HIPAA in the US, make it difficult for organizations to share and analyze data freely. Balancing robust security measures with facilitating data access for analytics remains a complex issue. According to the U.S. Department of Health and Human Services Office for Civil Rights, there were 642 healthcare data breaches affecting 500 or more records in 2020, impacting over 29 million individual records. There is a shortage of qualified data scientists and analysts with healthcare domain knowledge, limiting the industry's ability to fully leverage data analytics. A 2021 survey by the American Health Information Management Association (AHIMA) found that 59% of healthcare organizations reported difficulty in recruiting qualified health information professionals.

The inability of different healthcare IT systems to seamlessly exchange data hinders comprehensive data analysis across the healthcare ecosystem. The Office of the National Coordinator for Health Information Technology (ONC) reported in 2022 that only 55% of hospitals could integrate patient data from external sources into their EHR systems without manual entry. The significant upfront investment required for advanced analytics tools and infrastructure can be a barrier, especially for smaller healthcare organizations. A 2020 report by the Healthcare Financial Management Association (HFMA) indicated that the average cost of implementing a comprehensive healthcare analytics system ranged from USD 2 Million to USD 10 Million for mid-sized hospitals.

Category-Wise Acumens

How the Increasing Demand for Historical Data Analysis Surge the Growth of Descriptive Analytics Segment?

The descriptive analytics segment is dominant in the healthcare data analytics market, especially as its capabilities have been widely recognized during the pandemic. By leveraging historical data and patient records, descriptive analytics has been pivotal in understanding the spread of the virus, contributing significantly to its increased adoption. This surge in demand for historical data analysis has helped healthcare providers track virus trends and patient outcomes and support informed decision-making.

Descriptive analytics serves as a valuable tool in interpreting "what has happened" by transforming raw data into actionable insights. Hospitals and healthcare institutions, for instance, use descriptive analytics to enhance operational efficiency by monitoring insurance claims. By detecting anomalies and errors in claim submissions, healthcare organizations can ensure smoother administrative processes, reducing costs and improving financial performance.

Beyond healthcare providers, many organizations across the healthcare sector have also recognized the market potential of descriptive analytics. It enables them to refine their operations, detect inefficiencies, and improve patient outcomes. This wide adoption of descriptive analytics tools not only accelerates innovation within healthcare but also positions this segment as a critical driver of market growth. Its effectiveness during a global health crisis underscores its importance in modern healthcare data analytics.

How the Increasing Investment in the Healthcare Industry Accelerates the Growth of Service Segment?

The services segment has emerged as dominant in the healthcare data analytics market, driven by significant investments from the healthcare industry in IT infrastructure and data digitization. As the healthcare sector shifts towards more data-driven decision-making, the demand for sophisticated analytics platforms has increased. Many healthcare organizations, however, lack the internal resources or expertise to develop and manage comprehensive analytics solutions. In addition, they are increasingly outsourcing their data analytics needs to specialized service providers, fueling the rapid growth of the services segment.

Data analytics companies have responded to this demand by offering a complete range of services, from data integration and management to advanced analytics and reporting. These companies provide tailored solutions that help healthcare organizations harness the power of their data without the need for extensive in-house infrastructure. This outsourcing trend has allowed healthcare institutions to focus on their core competencies while benefiting from cutting-edge analytics capabilities.

Country/Region-wise Acumens

How does the Advanced Healthcare IT Infrastructure Escalate the Growth of the Healthcare Data Analytics Market in North America?

North America substantially dominates the healthcare data analytics market owing to the region's state-of-the-art healthcare facilities, and the adoption of these platforms and better technological availability have all resulted in a large market share for North America. According to the Office of the National Coordinator for Health Information Technology (ONC), as of 2021, 96% of all non-federal acute care hospitals in the United States had adopted certified EHR technology, providing a robust foundation for data analytics.

North America, particularly the United States, leads in healthcare expenditure, with a significant portion dedicated to healthcare IT and analytics. The Centers for Medicare & Medicaid Services (CMS) reported that U.S. national health expenditure grew 9.7% to $4.1 trillion in 2020, accounting for 19.7% of GDP. This high spending includes substantial investments in healthcare technology and analytics.

Government programs and regulations in North America have been driving the adoption of healthcare IT solutions, including data analytics platforms. The U.S. Department of Health and Human Services reported that as of 2022, more than 90% of office-based physicians had adopted an EHR system, largely due to incentives provided through the HITECH Act and subsequent programs.

How does the Rapid Digitalization of Healthcare Systems Surge the Growth of the Healthcare Data Analytics Market in Asia Pacific?

Asia Pacific is anticipated to witness the fastest growth in the healthcare data analytics market

during the forecast period driven by the rapid digitalization of healthcare systems. There has been significant growth and advancements in the industry in this region, which has also contributed to its growth. The increasing adoption of electronic health records (EHRs) and other digital health technologies is driving the demand for data analytics solutions. According to a 2022 report by the Asia eHealth Information Network (AeHIN), EHR adoption rates in Southeast Asian countries increased from an average of 35% in 2019 to 57% by the end of 2021, indicating a rapid digital transformation in the region's healthcare sector.

Rising healthcare spending in Asia Pacific countries is fueling investments in advanced technologies, including data analytics platforms. The World Health Organization (WHO) reported that healthcare expenditure in the Western Pacific Region, which includes much of Asia Pacific, grew at an average annual rate of 6.5% between 2020 and 2022, outpacing global averages.

The rising burden of chronic diseases and an aging population in many Asia Pacific countries is driving the need for data-driven healthcare solutions to manage population health effectively.

A 2021 study published in The Lancet Regional Health - Western Pacific found that the prevalence of chronic diseases in East and Southeast Asia increased by 18% between 2010 and 2020, with projections suggesting a further 22% increase by 2030.

Competitive Landscape

The Healthcare Data Analytics Market is highly competitive, with a mix of established technology giants, specialized healthcare analytics providers, and emerging startups. The key players in this market are constantly innovating to offer advanced solutions that cater to the specific needs of healthcare organizations.

The organizations are focusing on innovating their product line to serve the vast population in diverse regions. Some of the prominent players operating in the healthcare data analytics market include:

  • Allscripts
  • Cerner
  • Health Catalyst
  • IBM, Inovalon
  • McKesson
  • MedeAnalytics
  • Optum
  • Oracle
  • SAS
  • Wipro
  • Verscend
  • CitusTech
  • Cerner Corporation
  • Koninklijke Philips N.V.

Latest Developments:

  • In June 2022, Oracle Corporation announced the acquisition of Cerner Corporation, combining Cerner's clinical skills with Oracle's enterprise platform analytics and automation experience.
  • In January 2022, IBM announced the partnership with Francisco to reach a definitive deal in which Francisco Partners will purchase healthcare data and analytics assets from IBM that are currently part of the Watson Health business.

Healthcare Data Analytics Market, By Category

  • Type:
  • Descriptive
  • Predictive
  • Prescriptive
  • Application:
  • Clinical Analytics
  • Financial Analytics
  • Operational Analytics
  • Component:
  • Software
  • Services
  • Hardware
  • Deployment:
  • On-premises
  • Cloud-based
  • End-User:
  • Hospitals & Clinics
  • Healthcare Payers
  • Pharmaceutical & Biotechnology Companies
  • Research Institutions & Academia
  • Government Agencies
  • Healthcare IT Vendors
  • Region:
  • North America
  • Europe
  • Asia-Pacific
  • South America
  • Middle East & Africa

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL HEALTHCARE DATA ANALYTICS MARKET

  • 1.1 Overview of the Market
  • 1.2 Scope of Report
  • 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

  • 3.1 Data Mining
  • 3.2 Validation
  • 3.3 Primary Interviews
  • 3.4 List of Data Sources

4 GLOBAL HEALTHCARE DATA ANALYTICS MARKET OUTLOOK

  • 4.1 Overview
  • 4.2 Market Dynamics
    • 4.2.1 Drivers
    • 4.2.2 Restraints
    • 4.2.3 Opportunities
  • 4.3 Porters Five Force Model
  • 4.4 Value Chain Analysis

5 GLOBAL HEALTHCARE DATA ANALYTICS MARKET, BY TYPE

  • 5.1 Overview
  • 5.2 Descriptive Analysis
  • 5.3 Predictive Analysis
  • 5.4 Prescriptive Analysis

6 GLOBAL HEALTHCARE DATA ANALYTICS MARKET, BY COMPONENT

  • 6.1 Overview
  • 6.2 Software
  • 6.3 Hardware
  • 6.4 Services

7 GLOBAL HEALTHCARE DATA ANALYTICS MARKET, BY DEPLOYMENT

  • 7.1 Overview
  • 7.2 On-premises
  • 7.3 Web-hosted
  • 7.4 Cloud-based

8 GLOBAL HEALTHCARE DATA ANALYTICS MARKET, BY END-USE

  • 8.1 Overview
  • 8.2 Healthcare Payers
  • 8.3 Healthcare Providers
  • 8.4 Life Science Companies

9 GLOBAL HEALTHCARE DATA ANALYTICS MARKET, BY GEOGRAPHY

  • 9.1 Overview
  • 9.2 North America
    • 9.2.1 U.S.
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 U.K.
    • 9.3.3 France
    • 9.3.4 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 China
    • 9.4.2 Japan
    • 9.4.3 India
    • 9.4.4 Rest of Asia Pacific
  • 9.5 Rest of the World
    • 9.5.1 Latin America
    • 9.5.2 Middle East and Africa

10 GLOBAL HEALTHCARE DATA ANALYTICS MARKET COMPETITIVE LANDSCAPE

  • 10.1 Overview
  • 10.2 Company Market Ranking
  • 10.3 Key Development Strategies

11 COMPANY PROFILES

  • 11.1 Allscripts
    • 11.1.1 Overview
    • 11.1.2 Financial Performance
    • 11.1.3 Product Outlook
    • 11.1.4 Key Developments
  • 11.2 Cerner
    • 11.2.1 Overview
    • 11.2.2 Financial Performance
    • 11.2.3 Product Outlook
    • 11.2.4 Key Developments
  • 11.3 Health Catalyst
    • 11.3.1 Overview
    • 11.3.2 Financial Performance
    • 11.3.3 Product Outlook
    • 11.3.4 Key Developments
  • 11.4 IBM
    • 11.4.1 Overview
    • 11.4.2 Financial Performance
    • 11.4.3 Product Outlook
    • 11.4.4 Key Developments
  • 11.5 Inovalon
    • 11.5.1 Overview
    • 11.5.2 Financial Performance
    • 11.5.3 Product Outlook
    • 11.5.4 Key Developments
  • 11.6 McKesson
    • 11.6.1 Overview
    • 11.6.2 Financial Performance
    • 11.6.3 Product Outlook
    • 11.6.4 Key Developments
  • 11.7 MedeAnalytics
    • 11.7.1 Overview
    • 11.7.2 Financial Performance
    • 11.7.3 Product Outlook
    • 11.7.4 Key Developments
  • 11.8 Optum
    • 11.8.1 Overview
    • 11.8.2 Financial Performance
    • 11.8.3 Product Outlook
    • 11.8.4 Key Developments
  • 11.9 Oracle
    • 11.9.1 Overview
    • 11.9.2 Financial Performance
    • 11.9.3 Product Outlook
    • 11.9.4 Key Developments
  • 11.10 Wipro
    • 11.10.1 Overview
    • 11.10.2 Financial Performance
    • 11.10.3 Product Outlook
    • 11.10.4 Key Developments
  • 11.11 Verscend
    • 11.11.1 Overview
    • 11.11.2 Financial Performance
    • 11.11.3 Product Outlook
    • 11.11.4 Key Developments
  • 11.11 Verscend
    • 11.11.1 Overview
    • 11.11.2 Financial Performance
    • 11.11.3 Product Outlook
    • 11.11.4 Key Developments
  • 11.12 CitusTech
    • 11.12.1 Overview
    • 11.12.2 Financial Performance
    • 11.12.3 Product Outlook
    • 11.12.4 Key Developments
  • 11.13 Cerner Corporation
    • 11.13.1 Overview
    • 11.13.2 Financial Performance
    • 11.13.3 Product Outlook
    • 11.13.4 Key Developments
  • 11.14 Koninklijke Philips N.V.
    • 11.14.1 Overview
    • 11.14.2 Financial Performance
    • 11.14.3 Product Outlook
    • 11.14.4 Key Developments

12 KEY DEVELOPMENTS

  • 12.1 Product Launches/Developments
  • 12.2 Mergers and Acquisitions
  • 12.3 Business Expansions
  • 12.4 Partnerships and Collaborations

13 Appendix

  • 13.1 Related Research