預測疾病分析市場、機會、成長動力、產業趨勢分析與預測，2024-2032 年

全球預測疾病分析市場預計2023 年將價值25 億美元，預計2024 年至2032 年複合年成長率為21.7%。進步的關注。

醫療保健領域對精準醫療和數據驅動決策的需求加速了預測分析解決方案的採用。這些技術使醫療保健提供者能夠透過利用資料預測未來的健康事件來預見患者的結果、完善治療計劃並降低醫療成本。例如，2024 年 4 月，克萊姆森大學的研究人員正在探索用於精準醫療的人工智慧技術，根據患者的基因圖譜檢查藥物機制。

一個顯著的趨勢是基於雲端的解決方案的興起。雲端部署提供可擴展性、靈活性和成本效益，使醫療保健組織能夠管理大量資料並遠端存取分析工具，從而增強資料整合和即時分析。

整個預測疾病分析產業根據組件、部署模式、最終用途和區域進行細分。

軟體部分包括用於健康資料分析和預測見解的工具和平台，到 2023 年將創造 20 億美元的收入。由於對與現有醫療保健系統整合的高級分析的需求，預計該細分市場將保持重要的市場佔有率。資料視覺化、風險評估和結果預測等功能使該軟體對於醫療保健組織至關重要。 2024 年 7 月，Cardio Diagnostics Holdings Inc. 推出了 CDIO.AI 網路解決方案，具有人工智慧驅動的心血管疾病功能。

該市場按部署模式分為本地和雲，到 2023 年，本地細分市場將達到 15 億美元。方面的大量投資。具有嚴格資料隱私要求的組織更喜歡本地解決方案，以保持對敏感健康資訊的控制並確保法規遵循。例如，2018 年 3 月，NVIDIA Healthcare 推出了針對醫療技術、藥物發現和數位健康的生成式 AI 微服務。

北美預測疾病分析市場到2023 年收入將達到9.191 億美元，2024 年至2032 年複合年成長率將達到20.9%。所推動的。預測分析有助於識別高風險患者、最佳化治療計劃並減少不必要的就診。快速的技術進步和對複雜資料分析平台的存取進一步加速了採用，利用人工智慧和機器學習來實現準確的預測和可行的見解。

目錄

第 1 章：方法與範圍

第 2 章：執行摘要

第 3 章：產業洞察

• 產業生態系統分析
• 產業影響力
  • 成長動力
    • 越來越注重簡化醫療流程
    • 對預防性醫療保健的日益關注
    • 人工智慧和機器學習技術的進步以及患者治療效果的改善
  • 產業陷阱與挑戰
    • 資料隱私和安全問題
• 成長潛力分析
• 監管環境
• 創新格局
• 波特的分析
• PESTEL分析
• 未來市場趨勢
• 差距分析

第 4 章：競爭格局

• 介紹
• 公司矩陣分析
• 主要參與者競爭分析
• 競爭定位矩陣
• 戰略儀表板

第 5 章：市場估計與預測：按組成部分，2021 - 2032 年

• 主要趨勢
• 軟體
• 服務

第 6 章：市場估計與預測：按部署模式，2021 - 2032 年

• 主要趨勢
• 本地
• 雲

第 7 章：市場估計與預測：按最終用途，2021 - 2032 年

• 主要趨勢
• 醫療保健付款人
• 醫療保健提供者
• 其他最終用戶

第 8 章：市場估計與預測：按地區分類，2021 - 2032 年

• 主要趨勢
• 北美洲
  • 美國
  • 加拿大
• 歐洲
  • 德國
  • 英國
  • 法國
  • 西班牙
  • 義大利
  • 荷蘭
  • 歐洲其他地區
• 亞太地區
  • 中國
  • 日本
  • 印度
  • 澳洲
  • 韓國
  • 亞太地區其他地區
• 拉丁美洲
  • 巴西
  • 墨西哥
  • 阿根廷
  • 拉丁美洲其他地區
• 中東和非洲
  • 南非
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國
  • 中東和非洲其他地區

第 9 章：公司簡介

• Allscripts Healthcare Solutions Inc.
• Anaconda Inc.
• Apixio Inc.
• Epic System Corporation
• Health Catalyst
• IBM
• McKesson Corporation
• MedeAnalytics, Inc.
• Microsoft Corporation
• Optum
• Oracle
• Philips Healthcare
• SAS
• Siemens Healthineers

The Global Predictive Disease Analytics Market, valued at USD 2.5 billion in 2023, is projected to grow at a CAGR of 21.7% from 2024 to 2032. This growth is driven by a focus on streamlining healthcare processes, preventive healthcare, and advancements in AI and machine learning technologies.

The demand for precision medicine and data-driven decision-making in healthcare accelerates the adoption of predictive analytics solutions. These technologies enable healthcare providers to foresee patient outcomes, refine treatment plans, and reduce healthcare costs by leveraging data to predict future health events. For example, in April 2024, researchers at Clemson University are exploring AI technologies for precision medicine, examining drug mechanisms alongside patients' genetic profiles.

A notable trend is the rise in cloud-based solutions. Cloud deployment offers scalability, flexibility, and cost-effectiveness, allowing healthcare organizations to manage large data volumes and access analytics tools remotely, enhancing data integration and real-time analysis.

The overall predictive disease analytics industry is segmented based on component, deployment mode, end-use, and region.

The software segment, which generated USD 2 billion in 2023, includes tools and platforms for health data analysis and predictive insights. This segment is expected to maintain a significant market share due to the demand for advanced analytics that integrate with existing healthcare systems. Features like data visualization, risk assessment, and outcome prediction make the software essential for healthcare organizations. In July 2024, Cardio Diagnostics Holdings Inc. launched its CDIO.AI web-solution with AI-driven functionalities for cardiovascular diseases.

The market, categorized by deployment mode into on-premises and cloud, saw the on-premises segment leading with USD 1.5 billion in 2023. On-premises deployment, which installs predictive analytics software within an organization's IT environment, offers control and customization but requires significant investment in hardware and maintenance. Organizations with stringent data privacy requirements prefer on-premises solutions to maintain control over sensitive health information and ensure regulatory compliance. For instance, in March 2018, NVIDIA Healthcare introduced generative AI microservices for medtech, drug discovery, and digital health.

North America predictive disease analytics market, with a revenue of USD 919.1 million in 2023, is set to grow at a CAGR of 20.9% from 2024 to 2032. The region's demand for predictive disease analytics is driven by a shift towards value-based healthcare and cost containment. Predictive analytics helps identify high-risk patients, optimize treatment plans, and reduce unnecessary hospital visits. Rapid technological advancements and access to sophisticated data analytics platforms further accelerate adoption, leveraging AI and machine learning for accurate predictions and actionable insights.

Table of Contents

Chapter 1 Methodology and Scope

• 1.1 Market scope and definitions
• 1.2 Research design
  • 1.2.1 Research approach
  • 1.2.2 Data collection methods
• 1.3 Base estimates and calculations
  • 1.3.1 Base year calculation
  • 1.3.2 Key trends for market estimation
• 1.4 Forecast model
• 1.5 Primary research and validation
  • 1.5.1 Primary sources
  • 1.5.2 Data mining sources

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Industry impact forces
  • 3.2.1 Growth drivers
    • 3.2.1.1 Increasing focus on streamlining of healthcare processes
    • 3.2.1.2 Rising focus on preventive healthcare
    • 3.2.1.3 Advancements in AI and machine learning technologies coupled with improved patient outcomes
  • 3.2.2 Industry pitfalls and challenges
    • 3.2.2.1 Data privacy and security concerns
• 3.3 Growth potential analysis
• 3.4 Regulatory landscape
• 3.5 Innovation landscape
• 3.6 Porter's analysis
• 3.7 PESTEL analysis
• 3.8 Future market trends
• 3.9 Gap analysis

Chapter 4 Competitive Landscape, 2023

• 4.1 Introduction
• 4.2 Company matrix analysis
• 4.3 Competitive analysis of major key players
• 4.4 Competitive positioning matrix
• 4.5 Strategy dashboard

Chapter 5 Market Estimates and Forecast, By Component, 2021 - 2032 ($ Mn)

• 5.1 Key trends
• 5.2 Software
• 5.3 Services

Chapter 6 Market Estimates and Forecast, By Deployment Mode, 2021 - 2032 ($ Mn)

• 6.1 Key trends
• 6.2 On-premises
• 6.3 Cloud

Chapter 7 Market Estimates and Forecast, By End-use, 2021 - 2032 ($ Mn)

• 7.1 Key trends
• 7.2 Healthcare payers
• 7.3 Healthcare providers
• 7.4 Other end-users

Chapter 8 Market Estimates and Forecast, By Region, 2021 - 2032 ($ Mn)

• 8.1 Key trends
• 8.2 North America
  • 8.2.1 U.S.
  • 8.2.2 Canada
• 8.3 Europe
  • 8.3.1 Germany
  • 8.3.2 UK
  • 8.3.3 France
  • 8.3.4 Spain
  • 8.3.5 Italy
  • 8.3.6 Netherlands
  • 8.3.7 Rest of Europe
• 8.4 Asia Pacific
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 India
  • 8.4.4 Australia
  • 8.4.5 South Korea
  • 8.4.6 Rest of Asia Pacific
• 8.5 Latin America
  • 8.5.1 Brazil
  • 8.5.2 Mexico
  • 8.5.3 Argentina
  • 8.5.4 Rest of Latin America
• 8.6 Middle East and Africa
  • 8.6.1 South Africa
  • 8.6.2 Saudi Arabia
  • 8.6.3 UAE
  • 8.6.4 Rest of Middle East and Africa

Chapter 9 Company Profiles

• 9.1 Allscripts Healthcare Solutions Inc.
• 9.2 Anaconda Inc.
• 9.3 Apixio Inc.
• 9.4 Epic System Corporation
• 9.5 Health Catalyst
• 9.6 IBM
• 9.7 McKesson Corporation
• 9.8 MedeAnalytics, Inc.
• 9.9 Microsoft Corporation
• 9.10 Optum
• 9.11 Oracle
• 9.12 Philips Healthcare
• 9.13 SAS
• 9.14 Siemens Healthineers