Global De-identified Health Data Market Size Study, By Type of Data, By Application, By End-use, and Regional Forecasts 2022-2032

Description

The global de-identified health data market was valued at approximately USD 7.42 billion in 2023 and is anticipated to grow at a CAGR of 9.07% over the forecast period of 2024-2032. This expansion is largely attributed to the increasing integration of AI and machine learning in healthcare analytics, which enables organizations to leverage privacy-compliant data for large-scale clinical studies, predictive modeling, and pharmaceutical R&D. The proliferation of electronic health records (EHRs), wearable health devices, and genomic sequencing initiatives has further widened the applications of de-identified datasets, ensuring regulatory compliance while optimizing healthcare delivery and drug development processes.

Regulatory mandates such as HIPAA (Health Insurance Portability and Accountability Act) in the U.S. and GDPR (General Data Protection Regulation) in Europe have compelled healthcare organizations to de-identify patient data while maintaining data utility for research. This has led to significant investments in secure data-sharing platforms and federated learning models, enabling researchers to extract actionable insights without compromising patient confidentiality. For instance, in April 2023, Philips and MIT's Institute for Medical Engineering and Science (IMES) collaborated to develop an enhanced critical care dataset, integrating de-identified ICU patient data to support clinical AI applications and patient outcome improvement.

Moreover, the growing number of partnerships between pharmaceutical firms, research institutions, and health-tech companies is accelerating the adoption of de-identified data for drug discovery and precision medicine. In December 2023, nference partnered with Emory Healthcare to create a federated network of de-identified data aimed at improving disease modeling and enhancing diagnostic precision. The increasing reliance on real-world evidence (RWE) to optimize treatment pathways and reduce trial costs is expected to be a key driver for market growth over the coming years.

North America currently dominates the market, accounting for over 31.53% of the global revenue in 2024, due to the presence of advanced health data infrastructure, AI-driven analytics adoption, and regulatory frameworks supporting data de-identification. Europe follows closely, with strong government-backed initiatives in health data research, while Asia-Pacific is projected to experience the fastest CAGR, driven by digital transformation in healthcare, rising investments in health IT, and an increasing focus on AI-driven medical research.

Major Market Players Included in This Report Are:

IQVIA
Oracle (Cerner Corporation)
Merative (Truven Health Analytics)
Optum, Inc. (UnitedHealth Group)
ICON plc
Veradigm LLC (formerly Allscripts)
IBM
Flatiron Health (F. Hoffmann-La Roche Ltd)
Premier, Inc.
Shaip
Komodo Health, Inc.
Evidation Health, Inc.
Medidata
Clarify Health Solutions
Satori Cyber Ltd.

The Detailed Segments and Sub-Segment of the Market Are Explained Below:

By Type of Data:

Clinical Data
Genomic Data
Patient Demographics
Prescription Data
Claims Data
Behavioral Data
Wearable and Sensor Data
Survey and Patient-Reported Data
Imaging Data
Laboratory Data
Hospital and Provider Data
Social Determinants of Health (SDoH) Data
Pharmacogenomic Data
Biometric Data
Operational and Financial Data
Epidemiological Data
Healthcare Utilization Data
Others

By Application:

Clinical Research and Trials
Public Health
Precision Medicine
Health Economics and Outcomes Research (HEOR)
Population Health Management
Drug Discovery and Development
Healthcare Quality Improvement
Insurance Underwriting and Risk Assessment
Market Access and Commercial Strategy
Business Intelligence and Operational Efficiency
Telemedicine and Remote Monitoring
Patient Engagement and Support Programs
Others

By End-Use:

Pharmaceutical Companies
Biotechnology Firms
Medical Device Manufacturers
Healthcare Providers
Insurance Companies/Healthcare Payers
Research Institutions
Government Agencies
Others

By Region:

North America:

U.S.
Canada
Mexico

Europe:

UK
Germany
France
Italy
Spain
Denmark
Sweden
Norway

Asia-Pacific:

Japan
China
India
Australia
South Korea
Thailand

Latin America:

Brazil
Argentina

Middle East & Africa:

South Africa
Saudi Arabia
UAE
Kuwait

Years Considered for the Study Are as Follows:

Historical Year: 2022-2023
Base Year: 2023
Forecast Period: 2024-2032

Key Takeaways:

Market Estimates & Forecast for 10 years from 2024 to 2032
Annualized revenues and regional-level analysis for each market segment
Detailed analysis of geographical landscape with country-level market insights
Competitive landscape with key company profiling and revenue share analysis
Assessment of key business strategies and investment opportunities in the market
Demand-side and supply-side analysis of de-identified health data solutions

Chapter 1. Global De-identified Health Data Market Executive Summary

1.1. Global De-identified Health Data Market Size & Forecast (2024-2032)
1.2. Regional Summary
1.3. Segmental Summary
- 1.3.1. By Type of Data
- 1.3.2. By Application
- 1.3.3. By End-use
1.4. Key Trends
1.5. Recession Impact
1.6. Analyst Recommendation & Conclusion

Chapter 2. Global De-identified Health Data Market Definition and Research Assumptions

2.1. Research Objective
2.2. Market Definition
2.3. Research Assumptions
- 2.3.1. Inclusion & Exclusion
- 2.3.2. Limitations
- 2.3.3. Supply Side Analysis
  - 2.3.3.1. Availability
  - 2.3.3.2. Infrastructure
  - 2.3.3.3. Regulatory Environment
  - 2.3.3.4. Market Competition
  - 2.3.3.5. Economic Viability (Consumer's Perspective)
- 2.3.4. Demand Side Analysis
  - 2.3.4.1. Regulatory Frameworks
  - 2.3.4.2. Technological Advancements
  - 2.3.4.3. Environmental Considerations
  - 2.3.4.4. Consumer Awareness & Acceptance
2.4. Estimation Methodology
2.5. Years Considered for the Study
2.6. Currency Conversion Rates

Chapter 3. Global De-identified Health Data Market Dynamics

3.1. Market Drivers
- 3.1.1. Rising adoption of AI and machine learning for data analytics
- 3.1.2. Increasing use of real-world evidence (RWE) in clinical trials
- 3.1.3. Regulatory support for privacy-compliant healthcare data sharing
3.2. Market Challenges
- 3.2.1. Stringent data privacy and compliance regulations
- 3.2.2. Ethical concerns regarding patient data use
- 3.2.3. High costs associated with data security infrastructure
3.3. Market Opportunities
- 3.3.1. Expansion of federated learning models for secure data sharing
- 3.3.2. Growing demand for de-identified data in drug discovery
- 3.3.3. Rising integration of de-identified health data in precision medicine

Chapter 4. Global De-identified Health Data Market Industry Analysis

4.1. Porter's 5 Force Model
- 4.1.1. Bargaining Power of Suppliers
- 4.1.2. Bargaining Power of Buyers
- 4.1.3. Threat of New Entrants
- 4.1.4. Threat of Substitutes
- 4.1.5. Competitive Rivalry
- 4.1.6. Futuristic Approach to Porter's 5 Force Model
- 4.1.7. Porter's 5 Force Impact Analysis
4.2. PESTEL Analysis
- 4.2.1. Political
- 4.2.2. Economical
- 4.2.3. Social
- 4.2.4. Technological
- 4.2.5. Environmental
- 4.2.6. Legal
4.3. Top Investment Opportunity
4.4. Top Winning Strategies
4.5. Disruptive Trends
4.6. Industry Expert Perspective
4.7. Analyst Recommendation & Conclusion

Chapter 5. Global De-identified Health Data Market Size & Forecasts by Type of Data 2024-2032

5.1. Segment Dashboard
5.2. Global De-identified Health Data Market: Type of Data Revenue Trend Analysis, 2024 & 2032 (USD Billion)
- 5.2.1. Clinical Data
- 5.2.2. Genomic Data
- 5.2.3. Patient Demographics
- 5.2.4. Prescription Data
- 5.2.5. Claims Data
- 5.2.6. Behavioral Data
- 5.2.7. Wearable and Sensor Data
- 5.2.8. Social Determinants of Health (SDoH) Data
- 5.2.9. Others

Chapter 6. Global De-identified Health Data Market Size & Forecasts by Application 2024-2032

6.1. Segment Dashboard
6.2. Global De-identified Health Data Market: Application Revenue Trend Analysis, 2024 & 2032 (USD Billion)
- 6.2.1. Clinical Research and Trials
- 6.2.2. Public Health
- 6.2.3. Precision Medicine
- 6.2.4. Drug Discovery and Development
- 6.2.5. Health Economics and Outcomes Research (HEOR)
- 6.2.6. Healthcare Quality Improvement
- 6.2.7. Others

Chapter 7. Global De-identified Health Data Market Size & Forecasts by End-use 2024-2032

7.1. Segment Dashboard
7.2. Global De-identified Health Data Market: End-use Revenue Trend Analysis, 2024 & 2032 (USD Billion)
- 7.2.1. Pharmaceutical Companies
- 7.2.2. Biotechnology Firms
- 7.2.3. Medical Device Manufacturers
- 7.2.4. Healthcare Providers
- 7.2.5. Insurance Companies/Healthcare Payers
- 7.2.6. Research Institutions
- 7.2.7. Government Agencies
- 7.2.8. Others

Chapter 8. Global De-identified Health Data Market Size & Forecasts by Region 2024-2032

8.1. North America De-identified Health Data Market
- 8.1.1. U.S. Market Breakdown
- 8.1.2. Canada Market Breakdown
- 8.1.3. Mexico Market Breakdown
8.2. Europe De-identified Health Data Market
- 8.2.1. UK Market Breakdown
- 8.2.2. Germany Market Breakdown
- 8.2.3. France Market Breakdown
- 8.2.4. Italy Market Breakdown
- 8.2.5. Spain Market Breakdown
- 8.2.6. Denmark Market Breakdown
- 8.2.7. Sweden Market Breakdown
- 8.2.8. Norway Market Breakdown
8.3. Asia-Pacific De-identified Health Data Market
- 8.3.1. Japan Market Breakdown
- 8.3.2. China Market Breakdown
- 8.3.3. India Market Breakdown
- 8.3.4. Australia Market Breakdown
- 8.3.5. South Korea Market Breakdown
- 8.3.6. Thailand Market Breakdown
8.4. Latin America De-identified Health Data Market
- 8.4.1. Brazil Market Breakdown
- 8.4.2. Argentina Market Breakdown
8.5. Middle East & Africa De-identified Health Data Market
- 8.5.1. South Africa Market Breakdown
- 8.5.2. Saudi Arabia Market Breakdown
- 8.5.3. UAE Market Breakdown
- 8.5.4. Kuwait Market Breakdown

Chapter 9. Competitive Intelligence

9.1. Key Company SWOT Analysis
- 9.1.1. IQVIA
- 9.1.2. Oracle (Cerner Corporation)
- 9.1.3. Optum, Inc. (UnitedHealth Group)
9.2. Top Market Strategies
9.3. Company Profiles
- 9.3.1. ICON plc
- 9.3.2. Veradigm LLC
- 9.3.3. IBM
- 9.3.4. Flatiron Health
- 9.3.5. Premier, Inc.
- 9.3.6. Shaip
- 9.3.7. Komodo Health, Inc.
- 9.3.8. Evidation Health, Inc.
- 9.3.9. Medidata
- 9.3.10. Clarify Health Solutions

Chapter 10. Research Process

10.1. Research Process
- 10.1.1. Data Mining
- 10.1.2. Analysis
- 10.1.3. Market Estimation
- 10.1.4. Validation
- 10.1.5. Publishing
10.2. Research Attributes