小売薬局の非識別化健康データ市場- 世界の産業規模、シェア、動向、機会、予測、データセットタイプ別、地域別、競合別、2020～2030年予測

小売薬局の非識別化健康データの世界市場規模は2024年に81億1,000万米ドルとなり、CAGR 9.09%で2030年には136億9,000万米ドルに達すると予測されています。

小売薬局の非識別化健康データの世界市場は、ヘルスケア意思決定におけるデータ分析と実世界エビデンスの採用増加により、著しい成長を遂げています。小売薬局では、処方箋調剤や市販薬の販売時に膨大な量の患者データが生成されるが、これらのデータは非識別化されると、患者のプライバシーを守りながら調査や分析のための貴重なリソースとなります。このデータは個別化医療をサポートし、ヘルスケアプロバイダや製薬会社が治療パターン、服薬アドヒアランス、患者の転帰をよりよく理解することを可能にします。金額ベースケアモデルへのシフトは、ヘルスケアの有効性を評価し、資源配分を最適化するために、このようなデータの必要性をさらに高めています。電子カルテや薬局管理システムなどのデジタルヘルス技術の成長により、非識別化データのシームレスな収集と処理が容易になり、さまざまな利害関係者がデータにアクセスしやすくなっています。

市場の新たな動向として、大規模で複雑なデータセットから実用的な知見を抽出するための人工知能（AI）や機械学習アルゴリズムの統合が挙げられます。これらの技術により、患者の行動、薬効、副作用をより正確に予測することが可能になり、臨床検査の設計やヘルスケア介入が改善されます。小売薬局、ヘルスケアプロバイダ、研究機関の間で連携が進むことで、データの共有と集約が促進され、非識別化された健康データの範囲と有用性が広がります。HIPAAやGDPRのようなデータプライバシー規制は、非識別化技術の重要性を強調しており、それはデータの有用性と患者の機密性のバランスを取るために絶えず進化しています。遠隔医療やデジタルヘルスプラットフォームの拡大も、生成される健康データの量と多様性に寄与し、分析に利用可能なデータセットを豊かにしています。

主要市場促進要因

実世界のエビデンスに対する需要の高まり

主要市場課題

データプライバシーとセキュリティへの懸念

主要市場動向

バリューベースケア（VBC）と償還モデルの成長

目次

第1章 概要

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 顧客の声

第5章 世界の小売薬局の非識別化健康データ市場展望

• 市場規模・予測
  • 金額別
• 市場シェア・予測
  • データセットのタイプ別（DSCSAデータ、マーケットバスケットデータ、事前承認データ、在庫データ、エピソードデータ/薬局処方箋請求データ）
  • 企業別（2024年）
  • 地域別
• 市場マップ

第6章 北米の小売薬局の非識別化健康データ市場展望

• 市場規模・予測
• 市場シェア・予測
• 北米：国別分析
  • 米国
  • メキシコ
  • カナダ

第7章 欧州の小売薬局の非識別化健康データ市場展望

• 市場規模・予測
• 市場シェア・予測
• 欧州：国別分析
  • フランス
  • ドイツ
  • 英国
  • イタリア
  • スペイン

第8章 アジア太平洋の小売薬局の非識別化健康データ市場展望

• 市場規模・予測
• 市場シェア・予測
• アジア太平洋：国別分析
  • 中国
  • インド
  • 韓国
  • 日本
  • オーストラリア

第9章 南米の小売薬局の非識別化健康データ市場展望

• 市場規模・予測
• 市場シェア・予測
• 南米：国別分析
  • ブラジル
  • アルゼンチン
  • コロンビア

第10章 中東・アフリカの小売薬局の非識別化健康データ市場展望

• 市場規模・予測
• 市場シェア・予測
• 中東・アフリカ：国別分析
  • 南アフリカ
  • サウジアラビア
  • アラブ首長国連邦

第11章 市場力学

• 促進要因
• 課題

第12章 市場動向と発展

• 合併と買収
• 製品上市

第13章 混乱：紛争、パンデミック、貿易障壁

第14章 ポーターのファイブフォース分析

• 産業内の競合
• 新規参入の可能性
• サプライヤーの力
• 顧客の力
• 代替品の脅威

第15章 競合情勢

• 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 戦略的提言

第17章 調査会社について・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