零售药局去识别化健康数据市场－全球产业规模、份额、趋势、机会和预测（按资料集类型、地区和竞争情况细分，2020-2030 年）

2024 年全球零售药局去识别化健康数据市场价值为 81.1 亿美元，预计到 2030 年将达到 136.9 亿美元，复合年增长率为 9.09%。全球零售药局去识别化健康数据市场正在经历显着成长，这得益于资料分析和真实世界证据在医疗决策中的日益普及。零售药局在处方药配发和非处方药销售过程中会产生大量患者资料，这些数据在去识别化后，成为研究和分析的宝贵资源，同时保护了患者的隐私。这些资料支持个人化医疗，使医疗保健提供者和製药公司能够更好地了解治疗模式、用药依从性和患者结果。向基于价值的护理模式的转变进一步加强了对此类资料的需求，以评估医疗保健效果和优化资源配置。包括电子健康记录和药房管理系统在内的数位健康技术的发展促进了去识别化资料的无缝收集和处理，提高了各利益相关者的可近性。

市场新兴趋势包括人工智慧 (AI) 与机器学习演算法的整合，以从大型复杂资料集中提取可操作的见解。这些技术能够更准确地预测患者行为、药物疗效和不良反应，从而改善临床试验设计和医疗干预措施。零售药局、医疗保健提供者和研究机构之间日益密切的合作促进了资料共享和汇总，拓宽了去识别化健康资料的范围和效用。 HIPAA 和 GDPR 等资料隐私法规强调了去识别化技术的重要性，这些技术正在不断发展以平衡资料效用和病患隐私。远距医疗和数位健康平台的扩展也增加了产生的健康资料的数量和多样性，丰富了可供分析的数据集。

关键市场驱动因素

对真实世界证据的需求不断增长

主要市场挑战

资料隐私和安全问题

主要市场趋势

以价值为基础的照护（VBC）和报销模式的成长

目录

第 1 章：产品概述

第二章：研究方法

第三章：执行摘要

第四章：顾客之声

第五章：全球零售药局去识别化健康数据市场展望

• 市场规模和预测
  • 按价值
• 市场占有率和预测
  • 按资料集类型（DSCSA 资料、市场购物篮资料、事先授权资料、库存资料、偶发资料/药局处方索赔资料）
  • 按公司分类（2024）
  • 按地区
• 市场地图

第六章：北美零售药局去识别化健康数据市场展望

• 市场规模和预测
• 市场占有率和预测
• 北美：国家分析
  • 美国
  • 墨西哥
  • 加拿大

第七章：欧洲零售药局去识别化健康数据市场展望

• 市场规模和预测
• 市场占有率和预测
• 欧洲：国家分析
  • 法国
  • 德国
  • 英国
  • 义大利
  • 西班牙

第八章：亚太零售药局去识别化健康数据市场展望

• 市场规模和预测
• 市场占有率和预测
• 亚太地区：国家分析
  • 中国
  • 印度
  • 韩国
  • 日本
  • 澳洲

第九章：南美洲零售药局去识别化健康数据市场展望

• 市场规模和预测
• 市场占有率和预测
• 南美洲：国家分析
  • 巴西
  • 阿根廷
  • 哥伦比亚

第十章：中东和非洲零售药局去识别化健康数据市场展望

• 市场规模和预测
• 市场占有率和预测
• MEA：国家分析
  • 南非
  • 沙乌地阿拉伯
  • 阿联酋

第 11 章：市场动态

• 驱动程式
• 挑战

第 12 章：市场趋势与发展

• 合併与收购（如有）
• 产品发布（如有）
• 最新动态

第十三章：干扰：衝突、流行病与贸易壁垒

第 14 章：波特五力分析

• 产业竞争
• 新进入者的潜力
• 供应商的力量
• 顾客的力量
• 替代产品的威胁

第 15 章：竞争格局

• CVS Health Corporation
• Walgreens Boots Alliance, Inc.
• Walmart Inc.
• The Kroger Co.
• Albertsons Companies, Inc.
• UnitedHealth Group Incorporated
• Humana Inc.
• BrightSpring Health Services, Inc.
• Costco Wholesale Corporation
• Centene Corporation

第 16 章：策略建议

第17章调查会社について・免责事项

The Global Retail Pharmacy De-identified Health Data Market was valued at USD 8.11 Billion in 2024 and is expected to reach USD 13.69 Billion by 2030 with a CAGR of 9.09%. The Global Retail Pharmacy De-identified Health Data Market is witnessing significant growth driven by the increasing adoption of data analytics and real-world evidence in healthcare decision-making. Retail pharmacies generate vast amounts of patient data during prescription dispensing and over-the-counter medication sales, which, when de-identified, becomes a valuable resource for research and analysis while preserving patient privacy. This data supports personalized medicine, enabling healthcare providers and pharmaceutical companies to better understand treatment patterns, medication adherence, and patient outcomes. The shift toward value-based care models further intensifies the need for such data to evaluate healthcare effectiveness and optimize resource allocation. Growth in digital health technologies, including electronic health records and pharmacy management systems, facilitates the seamless collection and processing of de-identified data, enhancing its accessibility for various stakeholders.

Emerging trends in the market include the integration of artificial intelligence (AI) and machine learning algorithms to extract actionable insights from large, complex datasets. These technologies enable more accurate predictions of patient behavior, drug efficacy, and adverse reactions, improving clinical trial designs and healthcare interventions. The increasing collaboration between retail pharmacies, healthcare providers, and research organizations fosters data sharing and aggregation, broadening the scope and utility of de-identified health data. Data privacy regulations such as HIPAA and GDPR emphasize the importance of de-identification techniques, which are continuously evolving to balance data utility with patient confidentiality. The expansion of telemedicine and digital health platforms is also contributing to the volume and diversity of health data generated, enriching the datasets available for analysis.

Key Market Drivers

Rising Demand for Real-World Evidence

The rising demand for real-world evidence (RWE) is a powerful driver of the Global Retail Pharmacy De-identified Health Data Market, as stakeholders across the healthcare spectrum seek deeper insights beyond controlled clinical environments. Pharmacy claims and dispensing data when de-identified offer invaluable visibility into actual patient medication usage, treatment adherence patterns, and health outcomes. Pharmaceutical companies utilize this data to inform regulatory submissions, post-market safety surveillance, and label expansions, supported by frameworks such as the FDA's Real-World Evidence Program. The U.S. FDA's Center for Drug Evaluation and Research (CDER) recently announced the establishment of the Center for Real-World Evidence Innovation, tasked with coordinating and promoting use of real-world data (RWD) and real-world evidence in regulatory decisions.

Health insurers and payers rely on RWE from pharmacy data to inform reimbursement decisions and design outcomes-focused payment models. Providers and payers leverage these insights for personalizing patient care, pinpointing gaps in medication adherence, and reducing preventable hospital admissions. The data's de-identified status ensures compliance with strict privacy regulations like HIPAA and GDPR, enabling wide yet secure utilization in analytics. Federal support for RWE is evident: in 2023, the FDA awarded additional U01 grants to advance the use of RWD in regulatory decision-making, reinforcing its increasing institutional reliance on real-world evidence.

As chronic conditions and specialty therapies proliferate, pharmacy-derived RWD becomes even more critical, providing continuous, real-time insight into patient outcomes across diverse populations. Enhanced analytical capabilities now enable stakeholders to extract predictive intelligence that informs drug development, population health strategies, and value-based care initiatives. This growing emphasis on real-world evidence underscores the indispensable role of de-identified pharmacy data in shaping modern healthcare decision-making.

Key Market Challenges

Data Privacy and Security Concerns

Data privacy and security concerns present a significant challenge for the Global Retail Pharmacy De-identified Health Data Market due to the sensitive nature of healthcare information, even when de-identified. Although data is stripped of personal identifiers, the risk of re-identification through advanced analytics or cross-referencing with other datasets remains a pressing issue. Stakeholders must comply with stringent regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States, the General Data Protection Regulation (GDPR) in the European Union, and other regional data protection laws that impose strict requirements on handling, storage, and sharing of health-related data. Any breach, unauthorized access, or misuse of such information can lead to legal liabilities, financial penalties, and reputational damage for organizations involved.

The rapid advancement of data analytics, artificial intelligence, and machine learning tools increases the complexity of safeguarding de-identified health data, as these technologies can unintentionally increase the likelihood of re-identification. Building and maintaining robust cybersecurity infrastructure requires significant investments, yet even well-protected systems can be vulnerable to sophisticated cyberattacks or insider threats. As retail pharmacies expand their data-sharing partnerships with pharmaceutical companies, insurers, and research institutions, the number of access points to sensitive datasets grows, compounding the risk of unauthorized data exposure. Trust among consumers, regulatory bodies, and business partners depends heavily on the ability of market participants to uphold the highest data protection standards, making privacy and security challenges a critical barrier to sustained market growth.

Key Market Trends

Growth in Value Based Care (VBC) and Reimbursement Models

Growth in Value-Based Care (VBC) and evolving reimbursement models is becoming a significant trend shaping the Global Retail Pharmacy De-identified Health Data Market. Healthcare systems worldwide are shifting from volume-driven approaches, where providers are paid based on the quantity of services delivered, to value-based frameworks that reward improved patient outcomes, cost efficiency, and care quality. Retail pharmacies are increasingly positioned as critical touchpoints in this transformation, leveraging de-identified health data to demonstrate measurable impacts on patient health and adherence. The availability of large-scale pharmacy data, including prescription fill patterns, medication adherence rates, and therapeutic outcomes, enables payers and providers to align reimbursement strategies with evidence-based performance metrics.

This shift encourages collaborative care models where retail pharmacies, physicians, and payers work together to manage chronic diseases, reduce hospital readmissions, and prevent avoidable complications. De-identified datasets help assess the effectiveness of interventions, allowing stakeholders to refine care pathways and allocate resources more efficiently. The integration of this data into VBC initiatives also drives innovation in patient engagement, targeted medication management programs, and real-time performance monitoring. As reimbursement models continue to prioritize cost savings and improved patient outcomes, demand for de-identified pharmacy data is set to accelerate, reinforcing its strategic importance in value-based healthcare ecosystems.

Key Market Players

• CVS Health Corporation
• Walgreens Boots Alliance, Inc.
• Walmart Inc.
• The Kroger Co.
• Albertsons Companies, Inc.
• UnitedHealth Group Incorporated
• Humana Inc.
• BrightSpring Health Services, Inc.
• Costco Wholesale Corporation
• Centene Corporation

Report Scope:

In this report, the Global Retail Pharmacy De-identified Health Data Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Retail Pharmacy De-identified Health Data Market, By Dataset Type:

• DSCSA Data
  • By Buyer Type
    • Pharmaceutical Manufacturers
    • Drug Distributors
    • Regulatory Tech Vendors
    • Healthcare SaaS Vendors
    • Others
• Market Basket Data
  • By Buyer Type
    • CPG & Pharma Brands
    • Marketing & AdTech Firms
    • Health Insurers & PBMs
    • Retail Analytics Platforms
    • Others
• Prior Authorization Data
  • By Buyer Type
    • Payers & PBMs
    • Pharma Market Access Teams
    • Health IT Providers
    • Consulting & Policy Firms
    • Others
• Inventory Data
  • By Buyer Type
    • Pharma Manufacturers
    • Distributors/Wholesalers
    • AI/ML Inventory Optimization Vendors
    • Others
• Episodic Data/Pharmacy Rx Claims Data
  • By Buyer Type
    • Value-based Payers & ACOs
    • Pharma Outcomes Teams
    • Real-world Evidence Vendors
    • CMS & Government Organizations
    • Others

Retail Pharmacy De-identified Health Data Market, By Region:

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • France
  • United Kingdom
  • Italy
  • Germany
  • Spain
• Asia-Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
• South America
  • Brazil
  • Argentina
  • Colombia
• Middle East & Africa
  • South Africa
  • Saudi Arabia
  • UAE

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Retail Pharmacy De-identified Health Data Market.

Available Customizations:

Global Retail Pharmacy De-identified Health Data Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, and Trends

4. Voice of Customer

5. Global Retail Pharmacy De-identified Health Data Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Dataset Type (DSCSA Data, Market Basket Data, Prior Authorization Data, Inventory Data, Episodic Data/Pharmacy Rx Claims Data)
  • 5.2.2. By Company (2024)
  • 5.2.3. By Region
• 5.3. Market Map

6. North America Retail Pharmacy De-identified Health Data Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Dataset Type
  • 6.2.2. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Retail Pharmacy De-identified Health Data Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Dataset Type
  • 6.3.2. Mexico Retail Pharmacy De-identified Health Data Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Dataset Type
  • 6.3.3. Canada Retail Pharmacy De-identified Health Data Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Dataset Type

7. Europe Retail Pharmacy De-identified Health Data Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Dataset Type
  • 7.2.2. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. France Retail Pharmacy De-identified Health Data Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Dataset Type
  • 7.3.2. Germany Retail Pharmacy De-identified Health Data Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Dataset Type
  • 7.3.3. United Kingdom Retail Pharmacy De-identified Health Data Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Dataset Type
  • 7.3.4. Italy Retail Pharmacy De-identified Health Data Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Dataset Type
  • 7.3.5. Spain Retail Pharmacy De-identified Health Data Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Dataset Type

8. Asia-Pacific Retail Pharmacy De-identified Health Data Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Dataset Type
  • 8.2.2. By Country
• 8.3. Asia-Pacific: Country Analysis
  • 8.3.1. China Retail Pharmacy De-identified Health Data Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Dataset Type
  • 8.3.2. India Retail Pharmacy De-identified Health Data Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Dataset Type
  • 8.3.3. South Korea Retail Pharmacy De-identified Health Data Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Dataset Type
  • 8.3.4. Japan Retail Pharmacy De-identified Health Data Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Dataset Type
  • 8.3.5. Australia Retail Pharmacy De-identified Health Data Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Dataset Type

9. South America Retail Pharmacy De-identified Health Data Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Dataset Type
  • 9.2.2. By Country
• 9.3. South America: Country Analysis
  • 9.3.1. Brazil Retail Pharmacy De-identified Health Data Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Dataset Type
  • 9.3.2. Argentina Retail Pharmacy De-identified Health Data Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Dataset Type
  • 9.3.3. Colombia Retail Pharmacy De-identified Health Data Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Dataset Type

10. Middle East and Africa Retail Pharmacy De-identified Health Data Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Dataset Type
  • 10.2.2. By Country
• 10.3. MEA: Country Analysis
  • 10.3.1. South Africa Retail Pharmacy De-identified Health Data Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Dataset Type
  • 10.3.2. Saudi Arabia Retail Pharmacy De-identified Health Data Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Dataset Type
  • 10.3.3. UAE Retail Pharmacy De-identified Health Data Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Dataset Type

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends & Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Disruptions: Conflicts, Pandemics and Trade Barriers

14. Porters Five Forces Analysis

• 14.1. Competition in the Industry
• 14.2. Potential of New Entrants
• 14.3. Power of Suppliers
• 14.4. Power of Customers
• 14.5. Threat of Substitute Products

15. Competitive Landscape

• 15.1. CVS Health Corporation
  • 15.1.1. Business Overview
  • 15.1.2. Company Snapshot
  • 15.1.3. Products & Services
  • 15.1.4. Financials (As Reported)
  • 15.1.5. Recent Developments
  • 15.1.6. Key Personnel Details
  • 15.1.7. SWOT Analysis
• 15.2. Walgreens Boots Alliance, Inc.
• 15.3. Walmart Inc.
• 15.4. The Kroger Co.
• 15.5. Albertsons Companies, Inc.
• 15.6. UnitedHealth Group Incorporated
• 15.7. Humana Inc.
• 15.8. BrightSpring Health Services, Inc.
• 15.9. Costco Wholesale Corporation
• 15.10. Centene Corporation

16. Strategic Recommendations

17. About Us & Disclaimer