비식별화 의료 데이터 시장 규모, 점유율 및 동향 분석 보고서 : 데이터 유형별, 용도별, 최종 용도별, 지역별, 부문 예측(2026-2033년)

De-identified Health Data Market Summary

The global de-identified health data market size was estimated at USD 8.80 billion in 2025 and is projected to reach USD 17.93 billion by 2033, growing at a CAGR of 9.37% from 2026 to 2033. The market is driven by the increasing integration of data analytics in healthcare, which supports large-scale studies and predictive modeling without breaching patient confidentiality.

Regulatory frameworks such as GDPR and HIPAA further incentivize using de-identified data for compliance. Advancements in AI and machine learning amplify the need for extensive, privacy-compliant datasets to improve diagnostic and therapeutic methods. In addition, the surge in data from wearable devices, sensors, and electronic health records (EHRs) has expanded the scope for de-identified data in secondary applications.

De-identified health data is essential for clinical research as it allows researchers to analyze large datasets while protecting patient privacy. This data identifies trends, evaluates treatment effectiveness, and supports population health studies without compromising individual identities. By leveraging de-identified data, researchers can enhance the quality of their findings and facilitate advancements in medical knowledge and practice.

For instance, in April 2023, Philips and the MIT Institute for Medical Engineering and Science (IMES) collaborated to develop an enhanced critical care dataset to advance clinical research and AI applications in healthcare. This dataset includes de-identified data from ICU patients and integrates comprehensive clinical information to support researchers and educators in gaining insights into critical care and improving patient outcomes. The initiative fosters innovation in AI-driven healthcare solutions, contributing to more accurate diagnostics and personalized treatments.

Furthermore, de-identification facilitates collaboration and innovation within the healthcare sector by enabling secure patient data sharing across various healthcare systems, thereby advancing diagnostic and treatment technologies. Moreover, it provides critical data necessary for training AI systems, enhancing the accuracy and relevance of medical imaging for disease detection and analysis. This approach protects patient privacy and drives improvements in healthcare outcomes.

For instance, in December 2023, nference, Inc., a software company focused on transforming healthcare data for research, partnered with Emory Healthcare, Georgia's largest academic health system, to enhance access to diverse, aggregated, de-identified data. This initiative aims to accelerate research efforts, improve disease diagnosis, and facilitate the development of new treatments. The collaboration reflects a mutual commitment to advancing medical knowledge, promoting innovation, and enhancing the health and well-being of individuals and communities globally.

"This collaboration with nference allows us to join a federated data network of leading institutions that will enable ground-breaking research. Together, we can work to improve lives and provide hope, tackling some of the most critical health care challenges of our time while delivering comprehensive, data-driven insights."

Joe Depa, chief data and analytics officer at Emory Healthcare and Emory University

Global De-identified Health Data Market Report Segmentation

This report forecasts revenue growth and provides at global, regional, and country levels an analysis of the latest trends in each of the sub-segments from 2021 - 2033. For this report, Grand View Research has segmented the global de-identified health data market report based on type of data, application, end use, and region:

• Type of Data Outlook (Revenue, USD Million, 2021 - 2033)
• 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
• Application Outlook (Revenue, USD Million, 2021 - 2033)
• 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
• End Use Outlook (Revenue, USD Million, 2021 - 2033)
• Pharmaceutical Companies
• Biotechnology Firms
• Medical Device Manufacturers
• Healthcare Providers
• Insurance Companies/ Healthcare Payers
• Research Institutions
• Government Agencies
• Others
• Regional Outlook (Revenue, USD Million, 2021 - 2033)
• 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

Table of Contents

Chapter 1. Methodology and Scope

• 1.1. Market Segmentation & Scope
  • 1.1.1. Type of data
  • 1.1.2. End use
  • 1.1.3. Application
  • 1.1.4. Regional scope
  • 1.1.5. Estimates and forecast timeline.
• 1.2. Research Methodology
• 1.3. Information Procurement
  • 1.3.1. Purchased database.
  • 1.3.2. GVR's internal database
  • 1.3.3. Secondary sources
  • 1.3.4. Primary research
  • 1.3.5. Details of primary research
• 1.4. Information or Data Analysis
  • 1.4.1. Data analysis models
• 1.5. Market Formulation & Validation
• 1.6. Model Details
  • 1.6.1. Commodity flow analysis (Model 1)
  • 1.6.2. Approach 1: Commodity flow approach
  • 1.6.3. Volume price analysis (Model 2)
  • 1.6.4. Approach 2: Volume price analysis
• 1.7. List of Secondary Sources
• 1.8. List of Primary Sources
• 1.9. Objectives

Chapter 2. Executive Summary

• 2.1. Market Outlook
• 2.2. Segment Outlook
  • 2.2.1. Type of data outlook
  • 2.2.2. End use outlook
  • 2.2.3. Application outlook
  • 2.2.4. Regional outlook
• 2.3. Competitive Insights

Chapter 3. De-identified Health Data Market Variables, Trends & Scope

• 3.1. Market Lineage Outlook
  • 3.1.1. Parent market outlook
  • 3.1.2. Related/ancillary market outlook
• 3.2. Market Dynamics
  • 3.2.1. Market driver analysis
  • 3.2.2. Market restraint analysis
  • 3.2.3. Market Opportunity analysis
• 3.3. De-identified Health Data Market Analysis Tools
  • 3.3.1. Industry Analysis - Porter's
    • 3.3.1.1. Supplier power
    • 3.3.1.2. Buyer power
    • 3.3.1.3. Substitution threat
    • 3.3.1.4. Threat of new entrant
    • 3.3.1.5. Competitive rivalry
  • 3.3.2. PESTEL Analysis
    • 3.3.2.1. Political landscape
    • 3.3.2.2. Economic landscape
    • 3.3.2.3. Social landscape
    • 3.3.2.4. Technological landscape
    • 3.3.2.5. Environmental landscape
    • 3.3.2.6. Legal landscape

Chapter 4. De-identified Health Data Market: Type of Data Estimates & Trend Analysis

• 4.1. Type of Data Market Share, 2025 & 2033
• 4.2. Segment Dashboard
• 4.3. Global De-identified Health Data Market by Type of Data Outlook
• 4.4. Clinical Data
  • 4.4.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.5. Genomic Data
  • 4.5.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.6. Patient Demographics
  • 4.6.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.7. Prescription Data
  • 4.7.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.8. Claims Data
  • 4.8.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.9. Behavioral Data
  • 4.9.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.10. Wearable and Sensor Data
  • 4.10.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.11. Survey and Patient-Reported Data
  • 4.11.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.12. Imaging Data
  • 4.12.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.13. Laboratory Data
  • 4.13.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.14. Hospital and Provider Data
  • 4.14.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.15. Social Determinants of Health (SDoH) Data
  • 4.15.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.16. Pharmacogenomic Data
  • 4.16.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.17. Biometric Data
  • 4.17.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.18. Operational and Financial Data
  • 4.18.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.19. Epidemiological Data
  • 4.19.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.20. Healthcare Utilization Data
  • 4.20.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 4.21. Others
  • 4.21.1. Market estimates and forecast 2021 - 2033 (USD Million)

Chapter 5. De-identified Health Data Market: End Use Estimates & Trend Analysis

• 5.1. End Use Market Share, 2025 & 2033
• 5.2. Segment Dashboard
• 5.3. Global De-identified Health Data Market by End Use Outlook
• 5.4. Pharmaceutical Companies
  • 5.4.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 5.5. Biotechnology Firms
  • 5.5.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 5.6. Medical Device Manufacturers
  • 5.6.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 5.7. Healthcare Providers
  • 5.7.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 5.8. Insurance Companies/ Healthcare Payers
  • 5.8.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 5.9. Research Institutions
  • 5.9.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 5.10. Government Agencies
  • 5.10.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 5.11. Others
  • 5.11.1. Market estimates and forecast 2021 - 2033 (USD Million)

Chapter 6. De-identified Health Data Market: Application Estimates & Trend Analysis

• 6.1. Application Market Share, 2025 & 2033
• 6.2. Segment Dashboard
• 6.3. Global De-identified Health Data Market by Application Outlook
• 6.4. Clinical Research and Trials
  • 6.4.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.5. Public Health
  • 6.5.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.6. Precision Medicine
  • 6.6.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.7. Health Economics and Outcomes Research (HEOR)
  • 6.7.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.8. Population Health Management
  • 6.8.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.9. Drug Discovery and Development
  • 6.9.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.10. Healthcare Quality Improvement
  • 6.10.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.11. Insurance Underwriting and Risk Assessment
  • 6.11.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.12. Market Access and Commercial Strategy
  • 6.12.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.13. Business Intelligence and Operational Efficiency
  • 6.13.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.14. Telemedicine and Remote Monitoring
  • 6.14.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.15. Patient Engagement and Support Programs
  • 6.15.1. Market estimates and forecast 2021 - 2033 (USD Million)
• 6.16. Others
  • 6.16.1. Market estimates and forecast 2021 - 2033 (USD Million)

Chapter 7. De-identified Health Data Market: Regional Estimates & Trend Analysis, By Type of Data, By End use, By Application

• 7.1. Regional Market Share Analysis, 2025 & 2033
• 7.2. Regional Market Dashboard
• 7.3. Global Regional Market Snapshot
• 7.4. Market Size & Forecasts Trend Analysis, 2021 - 2033:
• 7.5. North America
  • 7.5.1. U.S.
    • 7.5.1.1. Key country dynamics
    • 7.5.1.2. Regulatory framework/ reimbursement structure
    • 7.5.1.3. Competitive scenario
    • 7.5.1.4. U.S. market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.5.2. Canada
    • 7.5.2.1. Key country dynamics
    • 7.5.2.2. Regulatory framework/ reimbursement structure
    • 7.5.2.3. Competitive scenario
    • 7.5.2.4. Canada market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.5.3. Mexico
    • 7.5.3.1. Key country dynamics
    • 7.5.3.2. Regulatory framework/ reimbursement structure
    • 7.5.3.3. Competitive scenario
    • 7.5.3.4. Mexico market estimates and forecasts 2021 - 2033 (USD Million)
• 7.6. Europe
  • 7.6.1. UK
    • 7.6.1.1. Key country dynamics
    • 7.6.1.2. Regulatory framework/ reimbursement structure
    • 7.6.1.3. Competitive scenario
    • 7.6.1.4. UK market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.6.2. Germany
    • 7.6.2.1. Key country dynamics
    • 7.6.2.2. Regulatory framework/ reimbursement structure
    • 7.6.2.3. Competitive scenario
    • 7.6.2.4. Germany market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.6.3. France
    • 7.6.3.1. Key country dynamics
    • 7.6.3.2. Regulatory framework/ reimbursement structure
    • 7.6.3.3. Competitive scenario
    • 7.6.3.4. France market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.6.4. Italy
    • 7.6.4.1. Key country dynamics
    • 7.6.4.2. Regulatory framework/ reimbursement structure
    • 7.6.4.3. Competitive scenario
    • 7.6.4.4. Italy market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.6.5. Spain
    • 7.6.5.1. Key country dynamics
    • 7.6.5.2. Regulatory framework/ reimbursement structure
    • 7.6.5.3. Competitive scenario
    • 7.6.5.4. Spain market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.6.6. Norway
    • 7.6.6.1. Key country dynamics
    • 7.6.6.2. Regulatory framework/ reimbursement structure
    • 7.6.6.3. Competitive scenario
    • 7.6.6.4. Norway market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.6.7. Sweden
    • 7.6.7.1. Key country dynamics
    • 7.6.7.2. Regulatory framework/ reimbursement structure
    • 7.6.7.3. Competitive scenario
    • 7.6.7.4. Sweden market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.6.8. Denmark
    • 7.6.8.1. Key country dynamics
    • 7.6.8.2. Regulatory framework/ reimbursement structure
    • 7.6.8.3. Competitive scenario
    • 7.6.8.4. Denmark market estimates and forecasts 2021 - 2033 (USD Million)
• 7.7. Asia Pacific
  • 7.7.1. Japan
    • 7.7.1.1. Key country dynamics
    • 7.7.1.2. Regulatory framework/ reimbursement structure
    • 7.7.1.3. Competitive scenario
    • 7.7.1.4. Japan market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.7.2. China
    • 7.7.2.1. Key country dynamics
    • 7.7.2.2. Regulatory framework/ reimbursement structure
    • 7.7.2.3. Competitive scenario
    • 7.7.2.4. China market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.7.3. India
    • 7.7.3.1. Key country dynamics
    • 7.7.3.2. Regulatory framework/ reimbursement structure
    • 7.7.3.3. Competitive scenario
    • 7.7.3.4. India market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.7.4. Australia
    • 7.7.4.1. Key country dynamics
    • 7.7.4.2. Regulatory framework/ reimbursement structure
    • 7.7.4.3. Competitive scenario
    • 7.7.4.4. Australia market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.7.5. South Korea
    • 7.7.5.1. Key country dynamics
    • 7.7.5.2. Regulatory framework/ reimbursement structure
    • 7.7.5.3. Competitive scenario
    • 7.7.5.4. South Korea market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.7.6. Thailand
    • 7.7.6.1. Key country dynamics
    • 7.7.6.2. Regulatory framework/ reimbursement structure
    • 7.7.6.3. Competitive scenario
    • 7.7.6.4. Singapore market estimates and forecasts 2021 - 2033 (USD Million)
• 7.8. Latin America
  • 7.8.1. Brazil
    • 7.8.1.1. Key country dynamics
    • 7.8.1.2. Regulatory framework/ reimbursement structure
    • 7.8.1.3. Competitive scenario
    • 7.8.1.4. Brazil market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.8.2. Argentina
    • 7.8.2.1. Key country dynamics
    • 7.8.2.2. Regulatory framework/ reimbursement structure
    • 7.8.2.3. Competitive scenario
    • 7.8.2.4. Argentina market estimates and forecasts 2021 - 2033 (USD Million)
• 7.9. MEA
  • 7.9.1. South Africa
    • 7.9.1.1. Key country dynamics
    • 7.9.1.2. Regulatory framework/ reimbursement structure
    • 7.9.1.3. Competitive scenario
    • 7.9.1.4. South Africa market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.9.2. Saudi Arabia
    • 7.9.2.1. Key country dynamics
    • 7.9.2.2. Regulatory framework/ reimbursement structure
    • 7.9.2.3. Competitive scenario
    • 7.9.2.4. Saudi Arabia market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.9.3. UAE
    • 7.9.3.1. Key country dynamics
    • 7.9.3.2. Regulatory framework/ reimbursement structure
    • 7.9.3.3. Competitive scenario
    • 7.9.3.4. UAE market estimates and forecasts 2021 - 2033 (USD Million)
  • 7.9.4. Kuwait
    • 7.9.4.1. Key country dynamics
    • 7.9.4.2. Regulatory framework/ reimbursement structure
    • 7.9.4.3. Competitive scenario
    • 7.9.4.4. Kuwait market estimates and forecasts 2021 - 2033 (USD Million)

Chapter 8. Competitive Landscape

• 8.1. Recent Developments & Impact Analysis, By Key Market Participants
• 8.2. Company/Competition Categorization
• 8.3. Innovators
• 8.4. Vendor Landscape
  • 8.4.1. List of key distributors and channel partners
  • 8.4.2. Key customers
  • 8.4.3. Key company market share analysis, 2025
  • 8.4.4. IQVIA
    • 8.4.4.1. Company overview
    • 8.4.4.2. Financial performance
    • 8.4.4.3. Technology Type benchmarking
    • 8.4.4.4. Strategic initiatives
  • 8.4.5. Oracle (Cerner Corporation)
    • 8.4.5.1. Company overview
    • 8.4.5.2. Financial performance
    • 8.4.5.3. Technology Type benchmarking
    • 8.4.5.4. Strategic initiatives
  • 8.4.6. Optum, Inc. (UnitedHealth Group)
    • 8.4.6.1. Company overview
    • 8.4.6.2. Financial performance
    • 8.4.6.3. Technology Type benchmarking
    • 8.4.6.4. Strategic initiatives
  • 8.4.7. ICON plc
    • 8.4.7.1. Company overview
    • 8.4.7.2. Financial performance
    • 8.4.7.3. Technology Type benchmarking
    • 8.4.7.4. Strategic initiatives
  • 8.4.8. Veradigm LLC (Formerly known as Allscripts)
    • 8.4.8.1. Company overview
    • 8.4.8.2. Financial performance
    • 8.4.8.3. Technology Type benchmarking
    • 8.4.8.4. Strategic initiatives
  • 8.4.9. IBM
    • 8.4.9.1. Company overview
    • 8.4.9.2. Financial performance
    • 8.4.9.3. Technology Type benchmarking
    • 8.4.9.4. Strategic initiatives
  • 8.4.10. Flatiron Health (F. Hoffmann-La Roche Ltd)
    • 8.4.10.1. Company overview
    • 8.4.10.2. Financial performance
    • 8.4.10.3. Technology Type benchmarking
    • 8.4.10.4. Strategic initiatives
  • 8.4.11. Premier, Inc.
    • 8.4.11.1. Company overview
    • 8.4.11.2. Financial performance
    • 8.4.11.3. Technology Type benchmarking
    • 8.4.11.4. Strategic initiatives
  • 8.4.12. Shaip
    • 8.4.12.1. Company overview
    • 8.4.12.2. Financial performance
    • 8.4.12.3. Technology Type benchmarking
    • 8.4.12.4. Strategic initiatives
  • 8.4.13. Komodo Health, Inc.
    • 8.4.13.1. Company overview
    • 8.4.13.2. Financial performance
    • 8.4.13.3. Technology Type benchmarking
    • 8.4.13.4. Strategic initiatives
  • 8.4.14. Evidation Health, Inc.
    • 8.4.14.1. Company overview
    • 8.4.14.2. Financial performance
    • 8.4.14.3. Technology Type benchmarking
    • 8.4.14.4. Strategic initiatives
  • 8.4.15. Medidata
    • 8.4.15.1. Company overview
    • 8.4.15.2. Financial performance
    • 8.4.15.3. Technology Type benchmarking
    • 8.4.15.4. Strategic initiatives
  • 8.4.16. Clarify Health Solutions
    • 8.4.16.1. Company overview
    • 8.4.16.2. Financial performance
    • 8.4.16.3. Technology Type benchmarking
    • 8.4.16.4. Strategic initiatives
  • 8.4.17. Satori Cyber Ltd.
    • 8.4.17.1. Company overview
    • 8.4.17.2. Financial performance
    • 8.4.17.3. Technology Type benchmarking
    • 8.4.17.4. Strategic initiatives