現實世界數據市場報告：趨勢、預測和競爭分析（至 2031 年）

全球真實世界數據 (RWD) 市場前景光明，為製藥和醫療設備公司、醫療保健支付者、醫療保健提供者和政府機構帶來了機會。預計到 2031 年，全球真實世界數據市場規模將達到 29 億美元，2025 年至 2031 年的複合年成長率為 7.70%。該市場的主要驅動力是電子健康記錄的日益普及以及對個人化醫療的日益重視。

• Lucintel 預測，在預測期內，藥物開發和核准將在所有應用中經歷最高的成長。
• 以最終用途來看，藥品和醫療設備預計將達到最高成長。
• 根據地區，預計北美將在預測期內實現最高成長。

現實世界數據市場的策略性成長機會

RWD 市場為各種應用提供了多種策略成長機會。利用這些機會將有助於推動市場擴張並增加 RWD 的影響力。

• 個人化醫療：RWD 在個人化醫療中的應用是一個重要的成長機會。透過利用真實世界的數據根據患者的個人情況量身定做治療方案，醫療保健提供者可以提高治療效果和患者治療效果。
• 藥物開發與研究：RWD 為藥物開發和研究提供了寶貴的見解，包括上市後監測和真實世界療效研究。這使得決策更加明智，並改善了對藥物安全性和有效性的評估。
• 人口健康管理：RWD 擴大用於人口健康管理，以識別健康趨勢和最佳化干涉措施。這使醫療保健組織能夠應對公共衛生挑戰並改善社區的健康狀況。
• 數位健康科技：穿戴式裝置和行動應用等數位健康科技的興起為整合 RWD 提供了成長機會。這些技術提供持續的數據收集和監控，提高真實世界證據的品質和範圍。
• 健康經濟學和結果研究：RWD 對於健康經濟學和結果研究 (HEOR) 很有價值，有助於評估治療的成本效益和價值。這一機會將支持醫療保健領域更好的資源分配和政策制定。

個人化醫療、藥物開發、人口健康管理、數位健康技術和衛生經濟研究等領域的策略性成長機會正在塑造 RWD 市場。利用這些機會可以促進創新並改善醫療保健服務。

現實世界數據市場的促進因素與挑戰

RWD 市場受到各種促進因素​​和挑戰的影響，包括技術進步、經濟因素和監管問題。了解這些因素對於有效駕馭市場至關重要。

現實世界的數據市場受以下因素驅動：

• 技術進步：人工智慧和機器學習等資料收集和分析技術的創新正在推動 RWD 市場的成長。這些進步增強了我們處理和分析大型資料集的能力，為醫療保健提供了寶貴的見解。
• 個人化醫療需求不斷成長：對個人化醫療的日益關注正在推動對 RWD 的需求。真實世界的證據有助於根據個別患者制定治療方案、改善治療效果並推進個人化醫療方法。
• 對使用 RWD 的監管支援：監管機構擴大支持在藥物開發和核准過程中使用 RWD。這種支持將為將真實世界證據（RWE）納入監管決策提供框架，擴大市場潛力。
• 數位健康工具的擴展：穿戴式裝置和行動醫療應用程式等數位健康工具的激增，提供了新的資訊來源。此次擴展將增強數據收集，並提供更多可供分析的真實證據。
• 專注於價值為基礎的照護：向基於價值的照護模式的轉變正在推動使用 RWD 來評估治療效果和成本效益。這項重點支持基於證據的決策並提高醫療保健的價值。

現實世界數據市場的挑戰包括：

資料隱私和安全問題：確保病患資料的隱私和安全是 RWD 市場面臨的關鍵挑戰。遵守資料保護條例和維護資料的機密性對於解決這些問題至關重要。

• 數據整合和品質問題：整合來自不同來源的數據並確保數據品質是一項挑戰。資料格式和完整性的變化會影響 RWD 的可靠性和分析的效用。
• 監管和合規障礙：滿足監管要求和確保遵守不斷發展的準則可能很複雜。監管障礙可能會影響 RWD 在某些應用中的使用速度和可行性。

技術進步、個人化醫療需求、監管支援、數位健康擴展和基於價值的醫療等市場促進因素正在推動 RWD 市場的成長。為了充分利用現實世界資料的潛力並促進市場發展，必須解決資料隱私、整合和法規遵循的挑戰。

目錄

第1章執行摘要

第2章 全球現實世界數據市場：市場動態

• 簡介、背景和分類
• 供應鏈
• 產業驅動力與挑戰

第3章市場趨勢與預測分析（2019-2031）

• 宏觀經濟趨勢（2019-2024）及預測（2025-2031）
• 全球現實世界資料市場趨勢（2019-2024）及預測（2025-2031）
• 全球真實世界數據市場（按組成部分）
  • 服務
  • 資料集
• 全球真實世界數據市場（按應用）
  • 藥物研發與核准
  • 市場進入、報銷/覆蓋決策
  • 上市後監測
  • 臨床研究
  • 其他
• 全球真實世界數據市場（依最終用途分類）
  • 製藥和醫療設備公司
  • 醫療保健付款人
  • 醫療保健提供者
  • 政府

第4章區域市場趨勢與預測分析（2019-2031）

• 全球真實世界數據市場（按地區）
• 北美真實世界數據市場
• 歐洲現實世界數據市場
• 亞太真實世界數據市場
• 其他地區的現實世界數據市場

第5章 競爭分析

• 產品系列分析
• 營運整合
• 波特五力分析

第6章 成長機會與策略分析

• 成長機會分析
  • 全球真實世界數據市場成長機會（按組成部分）
  • 全球真實世界數據市場成長機會（按應用）
  • 全球真實世界數據市場成長機會（按最終用途分類）
  • 全球現實世界數據市場成長機會（按地區）
• 全球現實世界數據市場的新興趨勢
• 戰略分析
  • 新產品開發
  • 擴大全球現實世界數據市場的容量
  • 全球現實世界數據市場的企業合併
  • 認證和許可

第7章主要企業簡介

• IQVIA
• Optum
• Cerner
• Flatiron Health
• IBM
• Tempus Labs
• Syneos Health
• Evidera
• Palantir Technologies
• SAS Institute

The future of the global real world data market looks promising with opportunities in the pharmaceutical and medical device companies, healthcare payers, healthcare providers, and government agencies markets. The global real world data market is expected to reach an estimated $2.9 billion by 2031 with a CAGR of 7.70% from 2025 to 2031. The major drivers for this market are growing adoption of electronic health records and the increasing emphasis on personalized medicine.

• Lucintel forecasts that, within the application category, drug development & approval is expected to witness the highest growth over the forecast period.
• Within the end use category, pharmaceutical & medical device are expected to witness the highest growth.
• In terms of regions, North America is expected to witness the highest growth over the forecast period.

Gain valuable insight for your business decisions with our comprehensive 150+ page report.

Emerging Trends in the Real World Data Market

Emerging trends in the real world data (RWD) market reflect the ongoing evolution of data collection, analysis, and application practices. These trends are reshaping the market and influencing how real-world evidence is utilized across various sectors.

• Integration of AI and Machine Learning: AI and machine learning technologies are increasingly being used to analyze large volumes of RWD, providing deeper insights and predictive analytics. This trend enhances the ability to identify patterns and trends, improve disease management, and personalize treatments based on real-world evidence.
• Expansion of Data Sources: The range of data sources for RWD is expanding beyond traditional EHRs to include wearable devices, mobile health apps, and social media. This trend increases the richness of the data and allows for a more comprehensive analysis of patient behaviors and outcomes.
• Regulatory Embrace of RWD: Regulatory agencies are increasingly recognizing the value of RWD for drug development and post-market surveillance. This trend includes efforts to streamline the use of RWD in regulatory submissions and approvals, making it a more integral part of the drug evaluation process.
• Focus on Data Privacy and Security: As the use of RWD grows, there is a heightened focus on ensuring data privacy and security. This trend involves implementing robust data protection measures and compliance with regulations to safeguard patient information and maintain trust in the data.
• Rise of Patient-Centric Data Collection: There is a growing emphasis on patient-centric approaches to data collection, where patients are actively involved in providing and managing their health data. This trend improves data accuracy and relevance, as well as patient engagement in their healthcare.

Emerging trends such as AI integration, expansion of data sources, regulatory support, data privacy focus, and patient-centric data collection are significantly reshaping the RWD market. These trends enhance the capabilities and applications of RWD, driving innovation and improving healthcare outcomes.

Recent Developments in the Real World Data Market

Recent developments in the real world data (RWD) market reflect advancements in technology and changes in regulatory landscapes. These developments are influencing how RWD is utilized across various applications and sectors.

• Enhanced Data Integration: Advances in technology have improved the integration of RWD from diverse sources, including EHRs, wearables, and patient registries. This development allows for more comprehensive data analysis and better insights into patient health and treatment outcomes.
• Adoption of AI and Machine Learning: The use of AI and machine learning algorithms is becoming more prevalent in analyzing RWD. These technologies enable more sophisticated data processing, predictive modeling, and personalized treatment approaches, enhancing the value of real-world evidence.
• Strengthened Regulatory Frameworks: Regulatory bodies are increasingly incorporating RWD into drug development and approval processes. Recent changes in regulatory frameworks are supporting the use of RWD for evaluating drug safety and efficacy, providing more robust evidence for decision-making.
• Expansion of Data Privacy Measures: With the growth of RWD usage, there is a heightened focus on data privacy and security. New measures and compliance standards are being implemented to protect patient information and ensure that data usage adheres to regulatory requirements.
• Growth in Patient-Reported Outcomes: The integration of patient-reported outcomes (PROs) into RWD collections is gaining traction. This development provides valuable insights into patients' perspectives on their health and treatment experiences, contributing to more patient-centered care.

Key developments such as enhanced data integration, AI adoption, strengthened regulatory frameworks, expanded data privacy measures, and growth in patient-reported outcomes are impacting the RWD market. These advancements improve data utilization and contribute to better healthcare outcomes.

Strategic Growth Opportunities for Real World Data Market

The RWD market offers several strategic growth opportunities across different applications. Capitalizing on these opportunities can drive market expansion and enhance the impact of RWD.

• Personalized Medicine: The use of RWD in personalized medicine is a key growth opportunity. By leveraging real-world data to tailor treatments to individual patient profiles, healthcare providers can improve treatment efficacy and patient outcomes.
• Drug Development and Research: RWD provides valuable insights for drug development and research, including post-market surveillance and real-world effectiveness studies. This opportunity allows for more informed decision-making and better assessment of drug safety and efficacy.
• Population Health Management: RWD is increasingly used in population health management to identify health trends and optimize interventions. This opportunity enables healthcare organizations to address public health challenges and improve community health outcomes.
• Digital Health Technologies: The rise of digital health technologies, such as wearable devices and mobile apps, presents growth opportunities for integrating RWD. These technologies provide continuous data collection and monitoring, enhancing the quality and scope of real-world evidence.
• Health Economics and Outcomes Research: RWD is valuable for health economics and outcomes research (HEOR), helping to assess the cost-effectiveness and value of treatments. This opportunity supports better resource allocation and policy-making in healthcare.

Strategic growth opportunities in areas such as personalized medicine, drug development, population health management, digital health technologies, and health economics research are shaping the RWD market. Leveraging these opportunities can drive innovation and improve healthcare delivery.

Real World Data Market Driver and Challenges

The RWD market is influenced by various drivers and challenges, including technological advancements, economic factors, and regulatory issues. Understanding these elements is crucial for navigating the market effectively.

The factors responsible for driving the real world data market include:

• Technological Advancements: Innovations in data collection and analysis technologies, such as AI and machine learning, are driving the growth of the RWD market. These advancements enhance the ability to process and analyze large datasets, providing valuable insights for healthcare.
• Increased Demand for Personalized Medicine: The growing emphasis on personalized medicine is driving demand for RWD. Real-world evidence helps tailor treatments to individual patients, improving outcomes and advancing personalized healthcare approaches.
• Regulatory Support for RWD Utilization: Regulatory bodies are increasingly supporting the use of RWD in drug development and approval processes. This support provides a framework for incorporating real-world evidence into regulatory decision-making, expanding the market's potential.
• Expansion of Digital Health Tools: The proliferation of digital health tools, such as wearables and mobile health apps, provides new sources of RWD. This expansion enhances data collection and enriches the real-world evidence available for analysis.
• Focus on Value-Based Healthcare: The shift towards value-based healthcare models is driving the use of RWD to assess treatment effectiveness and cost-effectiveness. This focus supports evidence-based decision-making and improves healthcare value.

Challenges in the real world data market are:

Data Privacy and Security Concerns: Ensuring the privacy and security of patient data is a significant challenge in the RWD market. Compliance with data protection regulations and maintaining data confidentiality are critical to addressing these concerns.

• Data Integration and Quality Issues: Integrating data from diverse sources and ensuring data quality can be challenging. Variability in data formats and completeness can impact the reliability of RWD and its usefulness for analysis.
• Regulatory and Compliance Hurdles: Navigating regulatory requirements and ensuring compliance with evolving guidelines can be complex. Regulatory hurdles may impact the speed and feasibility of utilizing RWD in certain applications.

Drivers such as technological advancements, demand for personalized medicine, regulatory support, digital health expansion, and value-based healthcare are fueling the growth of the RWD market. Challenges related to data privacy, integration, and regulatory compliance need to be addressed to fully leverage the potential of real-world data and enhance market development.

List of Real World Data Companies

Companies in the market compete based on product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies, real world data companies cater to increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the real world data companies profiled in this report include-

• IQVIA
• Optum
• Cerner
• Flatiron Health
• IBM
• Tempus Labs
• Syneos Health
• Evidera
• Palantir Technologies
• SAS Institute

Real World Data by Segment

The study includes a forecast for the global real world data market by component, application, end use, and region.

Real World Data Market by Component [Analysis by Value from 2019 to 2031]:

• Services
• Datasets

Real World Data Market by Application [Analysis by Value from 2019 to 2031]:

• Drug Development & Approvals
• Market Access & Reimbursement/Coverage Decisions
• Post-Market Surveillance
• Clinical Research
• Others

Real World Data Market by End Use [Analysis by Value from 2019 to 2031]:

• Pharmaceutical & Medical Device Companies
• Healthcare Payers
• Healthcare Providers
• Government Agencies

Real World Data Market by Region [Analysis by Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the Real World Data Market

The RWD market is evolving rapidly as organizations leverage data from real-world settings to enhance research, healthcare delivery, and decision-making. Innovations in data collection and analysis are transforming how this data is utilized across different regions, including the United States, China, Germany, India, and Japan.

• United States: In the U.S., recent developments in the RWD market include increased integration of electronic health records (EHRs) and patient registries. Advances in data analytics and machine learning are being used to extract actionable insights from large datasets. Additionally, regulatory support from agencies like the FDA is encouraging the use of RWD in clinical trials and post-market surveillance, enhancing the relevance and application of real-world evidence in healthcare decision-making.
• China: China is seeing significant growth in RWD as the government invests in digital health infrastructure. The expansion of EHR systems and patient databases is driving improvements in data quality and accessibility. Chinese companies are also focusing on integrating RWD with artificial intelligence (AI) to develop predictive models for disease management and treatment outcomes. Moreover, regulatory reforms are promoting the use of RWD for evaluating drug safety and efficacy.
• Germany: In Germany, advancements in RWD are driven by initiatives aimed at improving healthcare data interoperability and patient-centered research. The country is enhancing its data-sharing capabilities through national health data networks and platforms. Germany is also focusing on using RWD to support personalized medicine and outcomes-based research, leveraging high-quality health data to tailor treatments and interventions to individual patient needs.
• India: India's RWD market is growing as healthcare providers and researchers increasingly use real-world evidence to address public health challenges. The adoption of digital health tools and telemedicine is expanding the sources of RWD, which are being used to monitor treatment effectiveness and disease prevalence. Indian organizations are also working on improving data collection methodologies and integrating RWD into healthcare policies to enhance overall health outcomes.
• Japan: Japan is experiencing growth in RWD through advancements in digital health technologies and health information systems. The integration of RWD with genomic data is enabling more precise research and personalized treatment approaches. Additionally, Japan is focusing on expanding the use of RWD in clinical trials and regulatory submissions to enhance the robustness of evidence for new therapies and medical interventions.

Features of the Global Real World Data Market

Market Size Estimates: Real world data market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: Real world data market size by component, application, end use, and region in terms of value ($B).

Regional Analysis: Real world data market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different components, applications, end uses, and regions for the real world data market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the real world data market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

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This report answers the following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the real world data market by component (services and datasets), application (drug development & approvals, market access & reimbursement/coverage decisions, post-market surveillance, clinical research, and others), end use (pharmaceutical & medical device companies, healthcare payers, healthcare providers, and government agencies), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global Real World Data Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global Real World Data Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global Real World Data Market by Component
  • 3.3.1: Services
  • 3.3.2: Datasets
• 3.4: Global Real World Data Market by Application
  • 3.4.1: Drug Development & Approvals
  • 3.4.2: Market Access & Reimbursement/Coverage Decisions
  • 3.4.3: Post-Market Surveillance
  • 3.4.4: Clinical Research
  • 3.4.5: Others
• 3.5: Global Real World Data Market by End Use
  • 3.5.1: Pharmaceutical & Medical Device Companies
  • 3.5.2: Healthcare Payers
  • 3.5.3: Healthcare Providers
  • 3.5.4: Government Agencies

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global Real World Data Market by Region
• 4.2: North American Real World Data Market
  • 4.2.1: North American Real World Data Market by Application: Drug Development & Approvals, Market Access & Reimbursement/Coverage Decisions, Post-Market Surveillance, Clinical Research, and Others
  • 4.2.2: North American Real World Data Market by End Use: Pharmaceutical & Medical Device Companies, Healthcare Payers, Healthcare Providers, and Government Agencies
• 4.3: European Real World Data Market
  • 4.3.1: European Real World Data Market by Application: Drug Development & Approvals, Market Access & Reimbursement/Coverage Decisions, Post-Market Surveillance, Clinical Research, and Others
  • 4.3.2: European Real World Data Market by End Use: Pharmaceutical & Medical Device Companies, Healthcare Payers, Healthcare Providers, and Government Agencies
• 4.4: APAC Real World Data Market
  • 4.4.1: APAC Real World Data Market by Application: Drug Development & Approvals, Market Access & Reimbursement/Coverage Decisions, Post-Market Surveillance, Clinical Research, and Others
  • 4.4.2: APAC Real World Data Market by End Use: Pharmaceutical & Medical Device Companies, Healthcare Payers, Healthcare Providers, and Government Agencies
• 4.5: ROW Real World Data Market
  • 4.5.1: ROW Real World Data Market by Application: Drug Development & Approvals, Market Access & Reimbursement/Coverage Decisions, Post-Market Surveillance, Clinical Research, and Others
  • 4.5.2: ROW Real World Data Market by End Use: Pharmaceutical & Medical Device Companies, Healthcare Payers, Healthcare Providers, and Government Agencies

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global Real World Data Market by Component
  • 6.1.2: Growth Opportunities for the Global Real World Data Market by Application
  • 6.1.3: Growth Opportunities for the Global Real World Data Market by End Use
  • 6.1.4: Growth Opportunities for the Global Real World Data Market by Region
• 6.2: Emerging Trends in the Global Real World Data Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global Real World Data Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global Real World Data Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: IQVIA
• 7.2: Optum
• 7.3: Cerner
• 7.4: Flatiron Health
• 7.5: IBM
• 7.6: Tempus Labs
• 7.7: Syneos Health
• 7.8: Evidera
• 7.9: Palantir Technologies
• 7.10: SAS Institute