REAL-WORLD DATA (RWD) MARKET SIZE & SHARE ANALYSIS - GROWTH TRENDS AND FORECASTS (2023 - 2030)

The global real world data (RWD) market size is projected to grow from US$ 1.59 billion in 2023 to US$ 4.07 billion by 2030, at a CAGR of 14.4%. The increasing adoption of RWD in drug development and approvals, market access, and post-market surveillance is driving the growth of the market.

RWD is data collected from real-world settings, such as electronic health records (EHRs), claims data, and patient registries. It can be used to generate evidence on the safety and efficacy of drugs and medical devices, as well as to assess the impact of treatments on patient outcomes.

Real-world Data (RWD) Market Regional Insights

• North America is expected to dominate the global RWD market in 2023, with a market share of 42.5%. This is due to the region's well-developed healthcare industry, the increasing prevalence of chronic diseases, and the stringent regulations for drug approvals.
• Europe is expected to be the second-largest market for RWD in 2023, with a market share of 28.5%. This is due to the region's strong focus on innovation and the increasing adoption of big data in healthcare.
• Asia-Pacific is expected to be the fastest-growing market for RWD in 2023, with a CAGR of 10.5%. This is due to the region's large and growing population, the rising prevalence of chronic diseases, and the increasing government support for the use of RWD in healthcare decision-making.

Figure 1. Global Real-world Data (RWD) Market Share (%), by Region, 2023

Real-world Data (RWD) Market Drivers

• Increasing Adoption of Electronic Health Records (EHRs): The widespread adoption of electronic health records by healthcare providers has led to the accumulation of vast amounts of patient data. This data, when aggregated and anonymized, can provide valuable insights into real-world patient outcomes, treatment patterns, and disease progression.
• Growing Demand for Evidence-Based Medicine: There is a growing emphasis on evidence-based medicine, which relies on real-world evidence (RWE) derived from RWD. Stakeholders in healthcare, including regulators, payers, and healthcare providers, are recognizing the importance of using real-world data to make informed decisions about treatment effectiveness, comparative effectiveness, safety, and cost-effectiveness.
• Regulatory Support and Guidance: Regulatory agencies such as the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have recognized the value of real-world evidence in regulatory decision-making. They have provided guidelines and frameworks for the use of RWD and RWE in regulatory submissions, drug approvals, and post-market surveillance, further driving the demand for real-world data.
• Advancements in Data Analytics and Technologies: The advancement of data analytics tools and technologies, such as artificial intelligence (AI), machine learning (ML), and big data analytics, has facilitated the extraction of meaningful insights from large and complex real-world datasets. These technologies enable the analysis of RWD to identify treatment patterns, patient subgroups, adverse events, and other clinically relevant information.

Real-world Data (RWD) Market Opportunities

• Drug Development and Clinical Trials: Real-world data can be leveraged to optimize the drug development process and enhance clinical trial design. RWD can be used to identify target populations, understand disease progression, assess treatment effectiveness, and identify potential safety concerns. By integrating real-world evidence into clinical trials, researchers can enhance trial efficiency, recruit appropriate patients, and generate robust outcomes.
• Comparative Effectiveness Research: Real-world data enables comparative effectiveness research, which focuses on comparing the benefits and risks of different treatment options in real-world settings. RWD allows for the assessment of treatment effectiveness, safety, and patient outcomes across diverse patient populations, thereby providing valuable insights for healthcare decision-making.
• Market Access and Reimbursement: Real-world evidence derived from RWD can be used to demonstrate the value and cost-effectiveness of drugs and medical devices to payers and health technology assessment agencies. This evidence can support market access and reimbursement negotiations, facilitating the inclusion of innovative therapies in healthcare coverage.
• Pharmacovigilance and Drug Safety Monitoring: Real-world data plays a crucial role in post-marketing surveillance and ongoing drug safety monitoring. RWD can help identify and monitor adverse events, drug interactions, and long-term safety profiles of medications. This data can aid regulatory agencies, pharmaceutical companies, and healthcare providers in making informed decisions regarding drug safety and risk mitigation.

Real-world Data (RWD) Market Trends

• Increased Integration of Data Sources: There is a growing trend of integrating multiple data sources to gain a comprehensive view of patient health and outcomes. This includes combining electronic health records (EHRs), claims data, patient registries, wearable devices, social media data, and genomic information. Integrating diverse data sources allows for a more holistic analysis and provides richer insights into real-world patient experiences and outcomes.
• Advancements in Data Analytics and AI: The RWD market is witnessing rapid advancements in data analytics tools and techniques, including artificial intelligence (AI) and machine learning (ML). These technologies enable more sophisticated analysis of large and complex datasets, uncovering patterns, trends, and correlations that may not be apparent with traditional statistical approaches. AI and ML algorithms can assist in data integration, predictive modeling, risk stratification, and decision support.
• Focus on Data Quality and Standardization: Ensuring the quality and standardization of RWD has become a critical focus in the market. Efforts are being made to improve data integrity, completeness, and consistency across different data sources. Standardization initiatives, such as the use of common data models and terminologies, facilitate data interoperability, enhance data quality, and promote the comparability of findings across studies.
• Emphasis on Patient Privacy and Data Security: As the use of RWD increases, ensuring patient privacy and data security is paramount. Stricter regulations, such as the General Data Protection Regulation (GDPR) in Europe and the Health Insurance Portability and Accountability Act (HIPAA) in the United States, govern the collection, use, and sharing of patient data. Stakeholders are adopting robust data protection measures, including de-identification techniques and secure data storage and transfer protocols, to maintain patient confidentiality.

Real-world Data (RWD) Market Restraints

• Data Quality and Completeness: Ensuring the quality, completeness, and reliability of real-world data remains a challenge. RWD is often collected from disparate sources with varying levels of data quality, standardization, and completeness. Inconsistent data collection practices, missing data elements, and data entry errors can impact the reliability and validity of the insights derived from RWD.
• Data Privacy and Regulatory Compliance: The use of real-world data raises concerns about patient privacy and data protection. Regulatory requirements, such as GDPR and HIPAA, impose strict rules on the collection, storage, and use of patient data. Compliance with these regulations adds complexity and cost to RWD initiatives, requiring robust data de-identification and security measures to protect patient privacy.
• Data Fragmentation and Interoperability: Real-world data is often fragmented across various healthcare systems, electronic health record platforms, and research databases. Lack of interoperability and data standardization hinder the seamless integration and analysis of RWD. The need to overcome technical and semantic barriers to data sharing and aggregation poses challenges to deriving meaningful insights from disparate data sources.
• Selection Bias and Generalizability: RWD may suffer from selection bias, as it is typically derived from specific patient populations, healthcare settings, or regions. This may limit the generalizability of findings to broader populations. It is crucial to consider the representativeness of the data and account for potential biases when interpreting and applying insights from RWD.

Recent Developments

New product launches

• Medidata Rave launched a new product called Rave Real-world Evidence. This product helps life sciences companies to collect, manage, and analyze RWD from a variety of sources.
• IQVIA launched a new product called IQVIA Real World Insights. This product provides life sciences companies with access to a large database of RWD, as well as tools to analyze and interpret the data.
• Veeva launched a new product called Veeva Commercial Insights. This product helps life sciences companies to collect, manage, and analyze RWD from their sales and marketing data.

Acquisition and partnerships

• In 2022, IQVIA acquired Enlight Analytics, a provider of RWD solutions for the life sciences industry.
• In 2021, PPD, Inc. (acquired by Thermo Fisher Scientific Inc.) acquired Aetion, a provider of RWD analytics and insights.
• In 2020, Oracle acquired Cerner Corp., a provider of electronic health records (EHRs) that contains a wealth of RWD.
• In 2019, IBM Watson Health acquired Truven Health Analytics, a provider of health data and analytics.

Figure 2. Global Real-world Data (RWD) Market Share (%), by type of application, 2023

Top companies in Real-world Data (RWD) Market

• IQVIA Holdings Inc.
• Optum, Inc. (a subsidiary of UnitedHealth Group)
• Cerner Corporation
• Flatiron Health, Inc. (a subsidiary of Roche)
• IBM Corporation
• Tempus Labs Inc.
• Syneos Health Inc.
• Evidera, Inc.
• Palantir Technologies Inc.
• SAS Institute Inc.

*Definition: The Real-world Data (RWD) market refers to the collection, analysis, and utilization of data derived from real-world sources, such as electronic health records (EHRs), claims databases, patient registries, and other healthcare data sources. This data is often used for research, drug development, clinical trials, post-marketing surveillance, and healthcare decision-making, providing insights into real-world patient outcomes, treatment effectiveness, and safety profiles. The RWD market encompasses various stakeholders, including pharmaceutical companies, healthcare providers, regulatory bodies, and technology providers, who leverage real-world data to improve healthcare delivery and inform evidence-based decision-making.