首页 > 市场调查报告书 > 医疗设备

e保健医院 IT

市场调查报告书

商品编码

1696204

日本医疗保健分析市场 - 2025 至 2033 年

Japan Healthcare Analytics Market - 2025-2033

出版日期: 2025年03月25日 | 出版商:

DataM Intelligence | 英文 180 Pages | 商品交期: 最快1-2个工作天内

价格

※ 本网页内容可能与最新版本有所差异。详细情况请与我们联繫。

简介目录

2024 年日本医疗保健分析市场规模达到 24 亿美元，预计到 2033 年将达到 151 亿美元，在 2025-2033 年预测期内的复合年增长率为 19.8%。

医疗保健分析是指使用资料分析和统计模型来改善决策并优化医疗保健结果。它涉及收集、处理和分析各种类型的资料，例如患者记录、治疗结果、营运指标和财务资料，以获得有助于改善患者护理、降低成本和增强整体医疗保健体验的见解。

它有两种类型：描述性规范性、预测分析和其他类型。描述性分析着重于了解历史趋势和模式，例如患者人口统计、治疗效果和医院表现。预测分析使用历史资料和统计技术来预测未来的结果，例如识别有患有特定疾病风险的患者或预测医院再入院情况。

医疗分析利用人工智慧 (AI)、机器学习和云端运算等先进技术处理大量资料，在改善临床实践、营运效率和医疗管理方面发挥着至关重要的作用。

市场动态：

驱动因素与约束因素

技术进步

技术进步是日本医疗分析市场成长的重要催化剂。人工智慧（AI）、机器学习和云端运算等尖端技术的融合正在彻底改变医疗保健资料的分析。这种转变使人们能够更有效率、更准确地了解病患照护、营运流程和财务管理。

人工智慧和机器学习特别增强了预测分析能力，使医疗保健提供者能够识别高风险患者，预测疾病爆发并优化治疗计划。这些技术透过早期介入和客製化治疗策略促进了主动的医疗管理。

基于云端的解决方案在日本也越来越受欢迎，为医疗保健机构提供了扩展其分析能力的灵活性，而无需承担高昂的基础设施成本。这种可扩展性允许无缝整合来自各种来源的资料，从而改善决策并增强医疗保健结果。

此外，自然语言处理 (NLP) 等进步正在改善非结构化资料（例如医疗记录和报告）的分析，从而提供更全面的患者健康状况视图。随着这些技术的不断发展，日本医疗保健产业可以预期营运效率、成本降低和病患照护的整体品质将进一步提高。

例如，2023 年 3 月，富士通在日本推出了一个新的基于云端的医疗保健平台，旨在推动个人化医疗保健和药物开发。该平台利用云端运算、人工智慧和 HL7 FHIR（快速医疗互通性资源）等互通性标准来增强跨医疗机构的资料可移植性和整合。

此外，2024 年 6 月，软银集团与 Tempus AI 成立了一家合资企业，名为 SB TEMPUS，旨在利用人工智慧 (AI) 分析个人医疗资料并制定治疗建议。软银执行长孙正义在东京的一次简报会上宣布了这一倡议，这标誌着软银在一段时间的相对不活跃之后重新将重点放在人工智慧投资上迈出了重要一步。

资料隐私问题

资料隐私问题是日本医疗分析市场发展的重大限制。由于医疗保健资料高度敏感，此类资料的收集、处理和共享必须符合严格的监管标准，例如日本的《个人资讯保护法》（APPI）。保护病患隐私和确保资料安全的需求通常会限制医疗资料的共享和利用，从而阻碍进阶分析的充分潜力

此外，人们也担心资料外洩的风险，这可能会对医疗保健组织造成重大的财务和声誉损失。随着云端解决方案和第三方平台的使用日益增多，这种风险尤其加剧，因为它们容易受到网路攻击。

这些安全问题可能会阻碍医疗保健提供者采用新技术或完全整合医疗保健资料分析系统。此外，由于公司必须确保符合合规标准，因此遵守这些法律和道德框架的复杂性可能会减缓技术采用和分析工具实施的速度。

市场领导者和先驱者
- 新兴先锋和杰出参与者
- 拥有销售量最大的品牌的既定领导者
- 拥有成熟产品的市场领导者
CXO 观点
最新进展与突破
案例研究/正在进行的研究
监管和报销情况
波特五力分析
供应链分析
SWOT 分析
未满足的需求和差距
市场进入和扩张的推荐策略
情境分析：最佳情况、基本情况和最坏情况预测
定价分析和价格动态
关键意见领袖

第 5 章：日本医疗分析市场（按类型）

描述性分析
预测分析
规范分析
诊断分析

第 6 章：日本医疗分析市场（按组成部分）

软体
服务
硬体

第 7 章：日本医疗分析市场（依交付模式）

本地部署
基于云端

第 8 章：日本医疗分析市场（按应用）

营运管理
营运管理
财务分析
人口健康管理
临床分析
其他的

第九章：竞争格局与市场定位

竞争概况和主要市场参与者
市占率分析与定位矩阵
策略伙伴关係、併购
产品组合和创新的关键发展
公司基准化分析

第十章：公司简介

MCKESSON CORPORATION

公司概况
产品组合
- 产品描述
- 产品关键绩效指标 (KPI)
- 历史和预测产品销售量
- 产品销售量
财务概览
- 公司收入
- 地区收入份额
- 收入预测
关键进展
- 合併与收购
- 关键产品开发活动
- 监管部门批准等
SWOT 分析

Inovalon.
CitiusTech Inc
Arcadia Solutions, LLC.
IBM
SAS Institute Inc.
Verisk Analytics, Inc.
Oracle

第 11 章：假设与研究方法

资料收集方法
数据三角测量
预测技术
数据验证和确认

第 12 章：附录

简介目录

Product Code: HCIT9359

The Japan healthcare analytics market reached US$ 2.40 billion in 2024 and is expected to reach US$ 15.10 billion by 2033, growing at a CAGR of 19.8 % during the forecast period 2025-2033.

Healthcare analytics refers to using data analysis and statistical models to improve decision-making and optimize healthcare outcomes. It involves collecting, processing, and analyzing various data types such as patient records, treatment outcomes, operational metrics, and financial data to derive insights that help improve patient care, reduce costs, and enhance the overall healthcare experience.

It is of two types descriptive prescriptive, predictive analytics and others. Descriptive analytics is focused on understanding historical trends and patterns, such as patient demographics, treatment effectiveness, and hospital performance. Predictive analytics uses historical data and statistical techniques to predict future outcomes, such as identifying patients at risk of developing specific conditions or forecasting hospital readmissions.

Healthcare analytics plays a crucial role in improving clinical practices, operational efficiency, and healthcare management by leveraging advanced technologies like artificial intelligence (AI), machine learning, and cloud computing to handle large volumes of data.

Market Dynamics: Drivers & Restraints

Technological Advancements

Technological advancements are a significant catalyst for growth in the Japanese healthcare analytics market. The integration of cutting-edge technologies such as artificial intelligence (AI), machine learning, and cloud computing is revolutionizing the analysis of healthcare data. This transformation enables more efficient and accurate insights into patient care, operational processes, and financial management.

AI and machine learning have particularly enhanced predictive analytics capabilities, allowing healthcare providers to identify high-risk patients, forecast disease outbreaks, and optimize treatment plans. These technologies facilitate proactive healthcare management by enabling early intervention and tailored treatment strategies.

Cloud-based solutions are also gaining traction in Japan, providing healthcare organizations with the flexibility to scale their analytics capabilities without incurring heavy infrastructure costs. This scalability allows for seamless integration of data from various sources, improving decision-making and enhancing healthcare outcomes.

Moreover, advancements like natural language processing (NLP) are improving the analysis of unstructured data, such as medical notes and reports, offering a more comprehensive view of patient health. As these technologies continue to evolve, the Japanese healthcare sector can anticipate further enhancements in operational efficiency, cost reduction, and overall quality of patient care.

For instance, in March 2023, Fujitsu launched a new cloud-based healthcare platform in Japan aimed at advancing personalized healthcare and drug development. The platform utilizes cloud computing, AI, and interoperability standards such as HL7 FHIR (Fast Healthcare Interoperability Resources) to enhance data portability and integration across healthcare institutions.

Also, in June 2024, SoftBank Group launched a joint venture with Tempus AI, named SB TEMPUS, aimed at leveraging artificial intelligence (AI) to analyze personal medical data and develop treatment recommendations. This initiative was announced by CEO Masayoshi Son during a briefing in Tokyo and marks a significant step in SoftBank's renewed focus on AI investments after a period of relative inactivity.

Data Privacy Concerns

Data privacy concerns are a significant restraint in the Japanese healthcare analytics market. As healthcare data is highly sensitive, the collection, processing, and sharing of such data must comply with strict regulatory standards, such as Japan's Act on the Protection of Personal Information (APPI). The need to protect patient confidentiality and ensure data security often limits the sharing and utilization of healthcare data, hindering the full potential of advanced analytics

Moreover, there are concerns about the risk of data breaches, which could result in significant financial and reputational damage to healthcare organizations. This risk is particularly heightened with the increasing use of cloud-based solutions and third-party platforms, which are susceptible to cyberattacks.

These security issues may discourage healthcare providers from adopting new technologies or fully integrating healthcare data analytics systems. Additionally, the complexity of navigating these legal and ethical frameworks can slow down the pace of technological adoption and the implementation of analytics tools, as companies must ensure they meet compliance standards.

Segment Analysis

The Japan healthcare analytics market is segmented based on type, component, delivery mode and application.

Type:

The predictive analytics segment of this type is expected to dominate the Japan healthcare analytics market share

The predictive analytics segment in the Japanese healthcare analytics market is rapidly growing, driven by the increasing demand for data-driven insights to improve patient care, optimize resources, and forecast health trends. Predictive analytics uses historical data, statistical algorithms, and machine learning models to predict future outcomes, which is particularly valuable in a healthcare environment where early intervention can significantly impact patient outcomes.

Healthcare providers use predictive models to identify patients at risk of developing certain diseases or conditions, such as diabetes, heart disease, or cancer. By doing so, healthcare systems can focus on preventative care, potentially reducing long-term costs and improving quality of life. Predictive analytics helps healthcare organizations identify patients likely to be readmitted to hospitals after discharge. By predicting readmission risk, hospitals can take proactive steps to ensure better post-discharge care, which is crucial in reducing healthcare costs and improving patient outcomes.

Predictive analytics is also used to forecast healthcare demand, allowing hospitals to optimize staffing levels, manage patient flow, and ensure that resources are available where and when they are needed. This leads to improved operational efficiency and cost savings. These predictive capabilities are increasingly supported by technologies like AI and cloud computing, allowing healthcare providers to scale their operations and improve the accuracy of their predictions.

For instance, in November 2024, Dentsu's launch of Tobiras, which integrates Meta's Advanced Analytics (Meta AA) technology with first-party data, represents a significant step forward in leveraging data-driven insights to optimize marketing efforts.

This tool is particularly valuable for businesses navigating the complexities of the algorithmic era. It provides secure access to previously inaccessible insights, allowing for better-targeted campaigns and, ultimately, a 10% improvement in ROI for early adopters. These factors have solidified the segment's position in the Japanese healthcare analytics market.

Competitive Landscape

The major players in the Japan healthcare analytics market include MCKESSON CORPORATION, Inovalon., CitiusTech Inc., Arcadia Solutions, LLC., IBM, SAS Institute Inc., Verisk Analytics, Inc., and Oracle Inc., among others.

Key Developments

In February 2025, TriNetX, partnered with Fujitsu to establish TriNetX Japan K.K. This joint venture aims to revolutionize the use of anonymized electronic health record (EHR) data from Japanese patients, enhancing clinical trial efficiency, advancing healthcare research, and accelerating drug development timelines.
In November 2023, RapidAI made significant strides in the healthcare sector by obtaining Class III Shonin clearance in Japan for its stroke identification platform. This regulatory approval allows RapidAI to market its advanced imaging solutions in Japan, which is the second-largest stroke market globally.
In January 2023, Fujitsu and Sapporo Medical University initiated a joint project aimed at realizing data portability in the healthcare sector. This project focuses on enabling patients to access and manage their healthcare data, including electronic health records (EHRs) and personal health records (PHRs), through a cloud-based platform.

Why Purchase the Report?

Pipeline & Innovations: Reviews ongoing clinical trials and product pipelines and forecasts upcoming advancements in medical devices and pharmaceuticals.
Product Performance & Market Positioning: Analyze 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: This covers recent regulatory changes, new policies, and emerging technologies.
Competitive Strategies: Analyze 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 Japan healthcare analytics 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 2024

Manufacturers: Pharmaceutical, Medical Device, Biotech Companies, Contract Manufacturers, Distributors, Hospitals.
Regulatory & Policy: Compliance Officers, Government, Health Economists, Market Access Specialists.
Component & 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.

1. Market Introduction and Scope

1.1. Objectives of the Report
1.2. Report Coverage & Definitions
1.3. Report Scope

2. Executive Insights and Key Takeaways

2.1. Market Highlights and Strategic Takeaways
2.2. Key Trends and Future Projections
2.3. Snippet by Type
2.4. Snippet by Component
2.5. Snippet by Delivery Mode
2.6. Snippet by Application

3. Dynamics

3.1. Impacting Factors
- 3.1.1. Drivers
  - 3.1.1.1. Technological Advancements
  - 3.1.1.2. Growing Demand for Predictive Analytics
- 3.1.2. Restraints
  - 3.1.2.1. Data Privacy Concerns
  - 3.1.2.2. Stringent Regulations
- 3.1.3. Opportunity
  - 3.1.3.1. Integration of AI and Big Data
- 3.1.4. Impact Analysis

4. Strategic Insights and Industry Outlook

4.1. Market Leaders and Pioneers
- 4.1.1. Emerging Pioneers and Prominent Players
- 4.1.2. Established leaders with the largest-selling Brand
- 4.1.3. Market leaders with established Product
4.2. CXO Perspectives
4.3. Latest Developments and Breakthroughs
4.4. Case Studies/Ongoing Research
4.5. Regulatory and Reimbursement Landscape
4.6. Porter's Five Forces Analysis
4.7. Supply Chain Analysis
4.8. SWOT Analysis
4.9. Unmet Needs and Gaps
4.10. Recommended Strategies for Market Entry and Expansion
4.11. Scenario Analysis: Best-Case, Base-Case, and Worst-Case Forecasts
4.12. Pricing Analysis and Price Dynamics
4.13. Key Opinion Leaders

5. Japan Healthcare Analytics Market, By Type

5.1. Introduction
- 5.1.1. Analysis and Y-o-Y Growth Analysis (%), By Type
- 5.1.2. Market Attractiveness Index, By Type
5.2. Descriptive Analytics*
- 5.2.1. Introduction
- 5.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
5.3. Predictive Analytics
5.4. Prescriptive Analytics
5.5. Diagnostic Analytics

6. Japan Healthcare Analytics Market, 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. Services
6.4. Hardware

7. Japan Healthcare Analytics Market, By Delivery Mode

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Delivery Mode
- 7.1.2. Market Attractiveness Index, By Delivery Mode
7.2. On-Premise*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Cloud-Based

8. Japan Healthcare Analytics Market, By Application

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 8.1.2. Market Attractiveness Index, By Application
8.2. Operations Management*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. Operations Management
8.4. Financial Analytics
8.5. Population Health Management
8.6. Clinical Analytics
8.7. Others

9. Competitive Landscape and Market Positioning

9.1. Competitive Overview and Key Market Players
9.2. Market Share Analysis and Positioning Matrix
9.3. Strategic Partnerships, Mergers & Acquisitions
9.4. Key Developments in Product Portfolios and Innovations
9.5. Company Benchmarking

10. Company Profiles

10.1. MCKESSON CORPORATION*
- 10.1.1. Company Overview
- 10.1.2. Product Portfolio
  - 10.1.2.1. Product Description
  - 10.1.2.2. Product Key Performance Indicators (KPIs)
  - 10.1.2.3. Historic and Forecasted Product Sales
  - 10.1.2.4. Product Sales Volume
- 10.1.3. Financial Overview
  - 10.1.3.1. Company Revenue's
  - 10.1.3.2. Geographical Revenue Shares
  - 10.1.3.3. Revenue Forecasts
- 10.1.4. Key Developments
  - 10.1.4.1. Mergers & Acquisitions
  - 10.1.4.2. Key Product Development Activities
  - 10.1.4.3. Regulatory Approvals, etc.
- 10.1.5. SWOT Analysis
10.2. Inovalon.
10.3. CitiusTech Inc
10.4. Arcadia Solutions, LLC.
10.5. IBM
10.6. SAS Institute Inc.
10.7. Verisk Analytics, Inc.
10.8. Oracle