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市場調查報告書

商品編碼

1696204

日本醫療保健分析市場 - 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個工作天內

價格

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簡介目錄

2024 年日本醫療保健分析市場規模達到 24 億美元，預計到 2033 年將達到 151 億美元，在 2025-2033 年預測期內的複合年成長率為 19.8%。

醫療保健分析是指使用資料分析和統計模型來改善決策並最佳化醫療保健結果。它涉及收集、處理和分析各種類型的資料，例如患者記錄、治療結果、營運指標和財務資料，以獲得有助於改善患者護理、降低成本和增強整體醫療保健體驗的見解。

它有兩種類型：描述性規範性、預測分析和其他類型。描述性分析著重於了解歷史趨勢和模式，例如患者人口統計、治療效果和醫院表現。預測分析使用歷史資料和統計技術來預測未來的結果，例如識別有患有特定疾病風險的患者或預測醫院再入院情況。

醫療分析利用人工智慧 (AI)、機器學習和雲端運算等先進技術處理大量資料，在改善臨床實踐、營運效率和醫療管理方面發揮著至關重要的作用。

市場動態：

促進因素與約束因素

技術進步

技術進步是日本醫療分析市場成長的重要催化劑。人工智慧（AI）、機器學習和雲端運算等尖端技術的融合正在徹底改變醫療保健資料的分析。這種轉變使人們能夠更有效率、更準確地了解病患照護、營運流程和財務管理。

人工智慧和機器學習特別增強了預測分析能力，使醫療保健提供者能夠識別高風險患者，預測疾病爆發並最佳化治療計劃。這些技術透過早期介入和客製化治療策略促進了主動的醫療管理。

基於雲端的解決方案在日本也越來越受歡迎，為醫療保健機構提供了擴展其分析能力的靈活性，而無需承擔高昂的基礎設施成本。這種可擴展性允許無縫整合來自各種來源的資料，從而改善決策並增強醫療保健結果。

此外，自然語言處理 (NLP) 等進步正在改善非結構化資料（例如醫療記錄和報告）的分析，從而提供更全面的患者健康狀況視圖。隨著這些技術的不斷發展，日本醫療保健產業可以預期營運效率、成本降低和病患照護的整體品質將進一步提高。

例如，2023 年 3 月，富士通在日本推出了一個新的基於雲端的醫療保健平台，旨在推動個人化醫療保健和藥物開發。該平台利用雲端運算、人工智慧和 HL7 FHIR（快速醫療互通性資源）等互通性標準來增強跨醫療機構的資料可移植性和整合。

此外，2024 年 6 月，軟銀集團與 Tempus AI 成立了一家合資企業，名為 SB TEMPUS，旨在利用人工智慧 (AI) 分析個人醫療資料並制定治療建議。軟銀執行長孫正義在東京的一次簡報會上宣布了這一舉措，這標誌著軟銀在一段時間的相對不活躍之後重新將重點放在人工智慧投資上邁出了重要一步。

資料隱私問題

資料隱私問題是日本醫療分析市場發展的重大限制。由於醫療保健資料高度敏感，此類資料的收集、處理和共享必須符合嚴格的監管標準，例如日本的《個人資訊保護法》（APPI）。保護病患隱私和確保資料安全的需求通常會限制醫療資料的共享和利用，從而阻礙進階分析的充分潛力

此外，人們也擔心資料外洩的風險，這可能會對醫療保健組織造成重大的財務和聲譽損失。隨著雲端解決方案和第三方平台的使用日益增多，這種風險尤其加劇，因為它們容易受到網路攻擊。

這些安全問題可能會阻礙醫療保健提供者採用新技術或完全整合醫療保健資料分析系統。此外，由於公司必須確保符合合規標準，因此遵守這些法律和道德框架的複雜性可能會減緩技術採用和分析工具實施的速度。

市場領導者和先驅者
- 新興先鋒和傑出參與者
- 擁有銷售量最大的品牌的既定領導者
- 擁有成熟產品的市場領導者
CXO 觀點
最新進展與突破
案例研究/正在進行的研究
監管和報銷情況
波特五力分析
供應鏈分析
SWOT 分析
未滿足的需求和差距
市場進入和擴張的推薦策略
情境分析：最佳情況、基本情況和最壞情況預測
定價分析和價格動態
關鍵意見領袖

第 5 章：日本醫療分析市場（按類型）

描述性分析
預測分析
規範分析
診斷分析

第 6 章：日本醫療分析市場（按組成部分）

軟體
服務
硬體

第 7 章：日本醫療分析市場（依交付模式）

本地部署
基於雲端

第 8 章：日本醫療分析市場（按應用）

營運管理
營運管理
財務分析
人口健康管理
臨床分析
其他

第9章：競爭格局與市場定位

競爭概況和主要市場參與者
市佔率分析與定位矩陣
策略夥伴關係、併購
產品組合和創新的關鍵發展
公司基準化分析

第10章：公司簡介

MCKESSON CORPORATION

公司概況
產品組合
- 產品描述
- 產品關鍵績效指標 (KPI)
- 歷史和預測產品銷售量
- 產品銷售量
財務概覽
- 公司收入
- 地區收入佔有率
- 收入預測
關鍵進展
- 合併與收購
- 關鍵產品開發活動
- 監管部門批准等
SWOT 分析

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

第 11 章：假設與研究方法

資料收集方法
數據三角測量
預測技術
數據驗證和確認

第 12 章：附錄

簡介目錄

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