零售藥局去識別化健康數據市場－全球產業規模、佔有率、趨勢、機會和預測（按資料集類型、地區和競爭情況細分，2020-2030 年）

2024 年全球零售藥局去識別化健康數據市場價值為 81.1 億美元，預計到 2030 年將達到 136.9 億美元，複合年成長率為 9.09%。全球零售藥局去識別化健康數據市場正在經歷顯著成長，這得益於資料分析和真實世界證據在醫療決策中的日益普及。零售藥局在處方藥配發和非處方藥銷售過程中會產生大量患者資料，這些數據在去識別化後，成為研究和分析的寶貴資源，同時保護了患者的隱私。這些資料支持個人化醫療，使醫療保健提供者和製藥公司能夠更好地了解治療模式、用藥依從性和患者結果。向基於價值的護理模式的轉變進一步加強了對此類資料的需求，以評估醫療保健效果和最佳化資源配置。包括電子健康記錄和藥房管理系統在內的數位健康技術的發展促進了去識別化資料的無縫收集和處理，提高了各利益相關者的可近性。

市場新興趨勢包括人工智慧 (AI) 與機器學習演算法的整合，以從大型複雜資料集中提取可操作的見解。這些技術能夠更準確地預測患者行為、藥物療效和不良反應，從而改善臨床試驗設計和醫療干預措施。零售藥局、醫療保健提供者和研究機構之間日益密切的合作促進了資料共享和匯總，拓寬了去識別化健康資料的範圍和效用。 HIPAA 和 GDPR 等資料隱私法規強調了去識別化技術的重要性，這些技術正在不斷發展以平衡資料效用和病患隱私。遠距醫療和數位健康平台的擴展也增加了產生的健康資料的數量和多樣性，豐富了可供分析的資料集。

關鍵市場促進因素

對真實世界證據的需求不斷成長

主要市場挑戰

資料隱私和安全問題

主要市場趨勢

以價值為基礎的照護（VBC）和報銷模式的成長

目錄

第 1 章：產品概述

第2章：研究方法

第3章：執行摘要

第4章：顧客之聲

第5章：全球零售藥局去識別化健康數據市場展望

• 市場規模和預測
  • 按價值
• 市場佔有率和預測
  • 按資料集類型（DSCSA 資料、市場購物籃資料、事先授權資料、庫存資料、偶發資料/藥局處方索賠資料）
  • 按公司分類（2024）
  • 按地區
• 市場地圖

第6章：北美零售藥局去識別化健康數據市場展望

• 市場規模和預測
• 市場佔有率和預測
• 北美：國家分析
  • 美國
  • 墨西哥
  • 加拿大

第7章：歐洲零售藥局去識別化健康數據市場展望

• 市場規模和預測
• 市場佔有率和預測
• 歐洲：國家分析
  • 法國
  • 德國
  • 英國
  • 義大利
  • 西班牙

第8章：亞太零售藥局去識別化健康數據市場展望

• 市場規模和預測
• 市場佔有率和預測
• 亞太地區：國家分析
  • 中國
  • 印度
  • 韓國
  • 日本
  • 澳洲

第9章：南美洲零售藥局去識別化健康數據市場展望

• 市場規模和預測
• 市場佔有率和預測
• 南美洲：國家分析
  • 巴西
  • 阿根廷
  • 哥倫比亞

第10章：中東和非洲零售藥局去識別化健康數據市場展望

• 市場規模和預測
• 市場佔有率和預測
• MEA：國家分析
  • 南非
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國

第 11 章：市場動態

• 驅動程式
• 挑戰

第 12 章：市場趨勢與發展

• 合併與收購（如有）
• 產品發布（如有）
• 最新動態

第13章：干擾：衝突、流行病與貿易壁壘

第 14 章：波特五力分析

• 產業競爭
• 新進入者的潛力
• 供應商的力量
• 顧客的力量
• 替代產品的威脅

第 15 章：競爭格局

• 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：策略建議

第17章調查會社について,免責事項

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