Bridging Borders: The Role of Real-World Evidence in Shaping International Regulatory Policies

Abstract

This current review process exhaustively analyses several databases and sources to ensure the review is comprehensive and up to date. This review process exhaustively analyses several databases and sources. This article offers a summary of the literature review process in scientific research. Real-world data (RWD) refers to information about patient health and the provision of healthcare services that are obtained from a wide range of sources outside of conventional clinical trials. Summary of this article and origin of actual data as well as the popular models and methods used and analyse it. Finding over the difficulties and prospects of using actual data to make informed choices. The real world has a lot of potential for producing real-world data to help with trial design, execution of confirmatory trials, and answering questions that may not be answered any other way. To use the power of real-world data, the volume and complexity of that data also necessitate the creation of more appropriate, complex, and creative data processing and analysis methods while upholding scientific rigor in research findings and paying attention to data ethics.

Keywords

Introduction

real-world data (RWD) refers to information related to patient health status and the delivery of healthcare services collected from a variety of sources outside traditional clinical trials. Within the healthcare landscape, terms like RWD are often used interchangeably to describe elements of data acquisition, processing, and analytical methodologies connected to patient care and health system performance. The terminology employed typically depends on the specific focus, whether it be the raw data itself, the technological platforms used for its management, or the application of analytical devices to extract meaningful understanding that drive development in patient outcomes and healthcare strategies^ref.no.1.

The widespread adoption of the internet, social media, digital platforms, and mobile technologies, along with billing records, clinical registries, and electronic health records (EHRs), has accelerated the generation and availability of digital real-world data. Innovations in e-health systems, disease tracking tools, and other technology-enabled services—coupled with enhanced data storage capacity—have greatly expanded the volume and utility of RWD^ref.no2. Simultaneously, the rapid advancement of artificial intelligence (AI) and machine learning (ML) has revolutionized the way this data is interpreted and used across multiple sectors, from clinical care to health policy. However, these technological gains also bring with them escalating financial costs and operational complexities.

The inherent limitations of conventional randomized controlled trials (RCTs)—such as prolonged timelines, high expenses, and difficulties in participant enrollment—have underscored the importance of RWD in making clinical research more efficient and applicable to routine medical practice^ref.no.3,4. During the COVID-19 pandemic, RWD proved instrumental in generating timely real-world evidence (RWE) to evaluate treatment outcomes and inform public health responses under rapidly evolving conditions.

Unlike RCTs, which often involve narrow, homogenous cohorts and short study durations, RWD includes diverse patient populations, representing various ages, ethnicities, and those with multiple health conditions, thus offering insights that are more reflective of real-life clinical environments^ref.no.5. This inclusivity enhances the generalizability of findings and supports continuous monitoring of long-term health outcomes and rare side effects—an essential component of post-market surveillance.

Moreover, RWD contributes to health economics and outcomes research (HEOR) by offering valuable information on treatment expenditures, healthcare resource utilization, and patient-centric outcomes. These insights are critical for conducting cost-benefit evaluations and guiding policy decisions related to healthcare financing, coverage, and reimbursement frameworks. Additionally, by incorporating variables such as genetic profiles, lifestyle factors, and co-existing conditions, RWD supports the advancement of personalized medicine, enabling the creation of tailored treatment strategies that address the unique needs of individual patients^ref.no.6.

Post marketing real-world data (RWD):-

    Post marketing real-world data (RWD) refers to health-related data collected after a medical product, such as a drug, biologic, or medical device, has received regulatory approval and entered the market. Unlike data from randomized controlled trials (RCTs), which are conducted under controlled conditions, RWD is derived from routine clinical practice and real-life patient experiences. This type of data is instrumental in complementing clinical trial findings and providing a broader understanding of a product's performance in diverse patient populations.

Sources of Post marketing RWD:-

• Electronic Health Records (EHRs): Patient data recorded during routine care, such as diagnoses, treatments, lab results, and outcomes.
• Claims and Billing Data: Information derived from insurance claims that track healthcare services and costs.
• Patient Registries: Organized systems that collect data on patients with specific diseases or receiving specific treatments.
• Pharmacy and Dispensing Records: Data on prescription fulfilment patterns and medication use.
• Mobile Health (mHealth) Devices and Apps: Wearable technology and apps capturing patient-reported data and health metrics.
• Social Media and Patient Forums: Informal but increasingly relevant sources for tracking patient sentiment and adverse events.

Importance of Post marketing RWD:

1. Safety Monitoring (Pharmacovigilance):-

After market approval, rare or long-term side effects may emerge that were not detected during clinical trials. Post marketing surveillance using RWD enables regulatory agencies and manufacturers to monitor these issues in real time.

2. Effectiveness in Diverse Populations:-

Clinical trials often include highly selected participants. RWD reveals how treatments perform in real-world populations, including the elderly, patients with comorbidities, and those taking multiple medications.

3. Regulatory and Policy Decisions:-

Regulators like the FDA, EMA, and others are increasingly using RWD to inform decisions on label expansions, safety warnings, or additional approvals. For instance, RWD was crucial in the rapid evaluation of COVID-19 vaccines and treatments during the pandemic.

4. Health Economics and Outcomes Research (HEOR):-

RWD is vital for cost-effectiveness analyses, quality of life assessments, and understanding the burden of disease key elements in healthcare reimbursement decisions.

Challenges and Limitations:

• Data Quality and Completeness: Inconsistencies, missing data, and variations in how information is recorded can affect accuracy.
• Bias and Confounding: Without the randomization of clinical trials, RWD is more susceptible to selection bias and confounding variables.
• Data Integration: Merging data from different sources (e.g., EHRs and claims) can be technically complex and require robust data governance frameworks.
• Privacy and Ethics: Protecting patient confidentiality and ensuring ethical use of RWD are critical concerns, especially when dealing with sensitive health information.

Future Directions:

As health systems embrace digital technologies, both the scale and integrity of RWD will see continued enhancement. Artificial intelligence (AI) and machine learning are expected to play key roles in extracting insights from large and complex RWD sets. Moreover, global collaborations are emerging to harmonize RWD standards and improve its use in regulatory science.

Regulatory bodies like the U.S. FDA and the European Medicines Agency (EMA) have established frameworks to guide the use of RWD in supporting regulatory decisions. Initiatives such as the FDA’s Real-World Evidence Program and Europe’s DARWIN EU network reflect this growing emphasis.

National Trends and Major Databases Across 10 Asian Countries:

Taiwan:

stands out as a vibrant democracy with a population of approximately 23.3 million and a robust, high-performing market economy. In 2022, its gross domestic product (GDP) experienced a growth rate of 2.45%. A top national priority in the coming years is the advancement of digital infrastructure within the healthcare sector. Despite relatively modest adoption of electronic medical records (EMRs) or electronic health records (EHRs) in specialty care settings (SCS) — reported at 11.4% (71 out of 623 settings) — a marked increase was observed over a five-year span. Specifically, utilization rose from just 2.8% (1 out of 36) in 2017 to 19.4% (20 out of 103) by 2022, reflecting growing momentum in digital health integration.

Furthermore, Taiwan demonstrates strong commitment to clinical data quality, as evidenced by a high rate of clinical evidence reporting (CER) in SCS, with 65.8% (410 out of 623) of cases exhibiting comprehensive documentation. However, this trend does not extend to complex coordinated care settings (CCCS), where CER was significantly lower at 27.5% (14 out of 51). This discrepancy suggests a gap in data capture and standardization between routine and more integrated, multidisciplinary care models — a challenge Taiwan may address as it continues to enhance its national healthcare information systems.

          Taiwan boasts a well established and effective healthcare system, as evidenced by its strong  performance in real-world data (RWD) publications. Since the launch of the National Health Insurance (NHI) program in 1995, Taiwan has emerged as a regional leader in delivering universal health coverage (UHC).This comprehensive system ensures access to essential medical services and pharmaceuticals for all citizens and residents. Its success was further affirmed when Taiwan ranked fourth globally in the 2023 Legatum Prosperity                         Index for health and healthcare systems, a ranking that also factors in central   centralized claims reporting: nearly all healthcare institutions submit visit data including treatments, prescriptions, procedures, and diagnostic tests directly to the NHI, creating a robust repository of health information.

Singapore:

Singapore has developed a high-performing healthcare system renowned for its efficiency, innovation, and long-term sustainability. Anchored by strong government regulation and a culture of personal accountability, the framework blends state subsidies with compulsory savings via the Central Provident Fund (CPF). This approach empowers citizens to obtain accessible, top-tier medical services. The country consistently ranks among global leaders in health outcomes and system performance. A well-established digital infrastructure underpins the integration of health information, allowing for the real-time exchange and aggregation of patient data across healthcare institutions. This capacity strengthens clinical decision-making and enhances public health monitoring, while also fueling a rising number of real-world data (RWD) studies led by Singaporean academics and health organizations.

In recent years, Singapore has increasingly harnessed digital health technologies and analytical tools to shape healthcare policy and service design. Flagship initiatives like the National Electronic Health Record (NEHR) are aimed at maintaining care continuity by granting medical practitioners access to complete patient medical histories. Furthermore, the government actively fosters digital health innovation through bodies such as the Integrated Health Information Systems (IHiS) and the Health Sciences Authority (HSA)—the latter also carrying Despite considerable progress in digital transformation, persistent issues—such as data protection, technological compatibility, and equal access to digital healthcare tools—remain central to policy discussions as Singapore continues to advance its Smart Nation initiative.

India:

India has a vast and complex healthcare system shaped by its large population, socioeconomic diversity, and federal governance structure. The country has made considerable progress in expanding healthcare access, especially through government initiatives such as Ayushman Bharat, which aims to provide universal health coverage (UHC) and financial protection to millions of low-income families. Despite ongoing disparities between urban and rural areas, public health investments and digital health innovation are on the rise. India’s health ecosystem is increasingly embracing real-world data (RWD) to support research, public health planning, and policy decision-making. National databases like the Health Management Information System (HMIS) and eSanjeevani (India’s telemedicine platform) are critical tools for tracking healthcare delivery and outcomes at scale^ref.no.10.

India has also been investing in its digital infrastructure through the Ashman Bharat Digital Mission (ABDM), which aims to create a nationwide, interoperable health data system. Central to this is the Health ID, which enables individuals to link their medical records across providers and time. The country has also launched the National Digital Health Blueprint (NDHB) to guide this transformation. Moreover, academic and government-backed efforts such as the National Health Innovation Portal, ICMR databases, and the Centre for Health Informatics reflect India's increasing focus on health technology assessment (HTA) and evidence-based policymaking. While challenges persist such as ensuring data quality, privacy, and inclusion in remote regions. India is steadily advancing toward a more data-driven and equitable healthcare future^ref.no19,20.

Hong Kong:

Highly subsidized healthcare services and covers the majority of inpatient care. Despite its compact geography and dense population, Hong Kong maintains high healthcare standards, with life expectancy among the highest globally. The government has invested steadily in health informatics, and the region is known for its Electron The Hospital Authority (HA) manages the public system, which provides ic Health Record Sharing System (eHRSS), which allows healthcare providers across public and private sectors to access and share patients' medical histories. This interconnected framework supports the generation and utilization of real-world data (RWD), aiding clinical research, disease surveillance, and public health decision-making^ref.no.17,18.

In recent years, Hong Kong has embraced digital transformation in healthcare through initiatives such as Smart Hospital development, AI-driven diagnostics, and HealthTech innovation hubs. The government has also established the Health Bureau, which includes a unit for Health Technology Assessment (HTA) to evaluate the effectiveness and efficiency of medical technologies. Additionally, the region’s integration with mainland China's Greater Bay Area opens further opportunities for cross-border health data collaboration and innovation. However, privacy concerns and data security remain critical issues in public discourse. As Hong Kong navigates its future in digital health, it is well-positioned to serve as a model for blending Eastern and Western healthcare practices with cutting-edge technology^ref.no.17,18.

Thailand:

Thailand has earned international recognition for its strides toward universal health coverage (UHC) and public health equity. Since the implementation of the Universal Coverage Scheme (UCS) in 2002, Thailand has significantly expanded access to essential health services, particularly for low-income and rural populations. The country's healthcare system is primarily government-funded and supported by multiple public insurance schemes. Thailand's focus on primary care, community health workers, and preventive services has contributed to improved health outcomes and reduced financial hardship for patients. The nation's growing emphasis on real-world data (RWD) collection—particularly through systems like the Health Data Centre (HDC) operated by the Ministry of Public Health—has enabled better disease monitoring, policy evaluation, and resource planning^Ref.no15,16.

Digitally, Thailand is advancing its eHealth strategy with systems that support nationwide health information exchange, electronic medical records (EMRs), and patient tracking. The government has initiated efforts to build an integrated National Health Information Exchange (HIE) platform, aiming to connect health facilities across regions. Thailand has also shown growing interest in Health Technology Assessment (HTA), institutionalized through the Health Intervention and Technology Assessment Program (HITAP), which plays a central role in informing cost-effective and evidence-based health policy decisions. Despite infrastructure and interoperability challenges, especially in rural provinces, Thailand continues to strengthen its digital health ecosystem with the support of both domestic innovation and international collaboration.

Malaysia:                                                                                                                     

Malaysia, classified as an upper-middle-income economy, is strategically situated in Southeast Asia and is home to an estimated 34 million people. The country has emerged as a regional leader in information and communication technology (ICT) and medical tourism, attracting patients and investors from across the Asia-Pacific region. As part of its broader economic modernization agenda, Malaysia is actively integrating digital technologies across critical sectors—including healthcare—to reinforce its competitive edge in the global economy of the future.

The Malaysian healthcare system operates under a dual-tier model, comprising a tax-supported public sector that provides affordable services and a dynamic private sector catering to more specialized and premium care. In 2019, government expenditure on healthcare represented approximately 52% of total national health spending, underscoring the central role of public health services in the country’s healthcare framework.

In a major step toward digital health reform, the 2023 Health White Paper introduced a strategic roadmap to overhaul Malaysia’s health data ecosystem. This blueprint emphasizes interoperability, data governance, and evidence-based decision-making. A key institution in this effort is the Malaysian Health Technology Assessment Section (MaHTAS), which plays a crucial role in providing reliable, science-based evaluations to inform both health policies and clinical practices.

Malaysia’s use of real-world data (RWD) has, to date, been largely cantered on national disease registries, such as those tracking cancer, dialysis, or cardiovascular conditions. However, the integration of alternative RWD sources—including electronic health records, insurance claims, and digital health apps—remains limited. As Malaysia aligns more closely with international standards in health technology assessment (HTA), a growing proportion of its evaluations are grounded in comparative effectiveness research (CER). In fact, 56% of structured clinical studies (SCS) submitted for HTA in Malaysia were classified under CER, reflecting the country's increasing interest in evaluating how interventions perform under routine, real-world conditions rather than controlled trial settings.

As Malaysia advances its health system digitalization efforts, ongoing challenges include ensuring data quality, standardizing data formats across institutions, and addressing privacy concerns—particularly in the context of expanding digital health services. Nevertheless, these reforms mark an important transition toward a more data-driven, equitable, and responsive healthcare ecosystem.

Indonesia:

Indonesia, the fourth most populous nation globally, is home to over 275 million people spread across an extensive archipelago of more than 17,000 islands. As a lower-middle-income economy and the largest economic power in Southeast Asia, the country plays a vital role in global trade and regional geopolitics With a young demographic profile and a fast-growing digital landscape, Indonesia is making significant strides in areas such as e-commerce, financial technology (fintech), and online service platforms. Despite these advancements, the nation continues to grapple with infrastructure deficits, educational imbalances, and regional disparities in development.

In healthcare, Indonesia operates a national universal health coverage scheme, known as Jaminan Kesehatan Nasional (JKN), initiated in 2014 and overseen by BPJS (Social Security Administration Agency). This system is designed to deliver broad-based medical coverage to a large and diverse population. However, persistent issues related to funding sustainability, access to services, and variability in care quality present ongoing challenges. To enhance healthcare governance and delivery, the government is increasingly integrating digital health strategies and utilizing real-world data (RWD) drawn from national health surveys, insurance claims, and electronic medical records.

The Badan Pusat Statistik (BPS), Indonesia’s Central Statistics Agency, is instrumental in the collection and management of national data across multiple sectors, including health. The nation is actively investing in modernizing its health information infrastructure to enable data-informed policymaking and more effective resource allocation. These initiatives reflect Indonesia’s broader commitment to evidence-based health planning and the digital transformation of its public services.

Vietnam:

Vietnam is a rapidly advancing nation in Southeast Asia, home to an estimated 100 million people. Over recent decades, it has experienced a remarkable socioeconomic transformation, evolving from a centrally planned economy to a more market-driven system. This evolution, catalysed by the “??i M?i” (Renovation) reforms launched in 1986, has spurred robust economic development, positioning Vietnam among the fastest-growing economies in the region. Known for its rich cultural heritage, historical depth, and diverse natural landscapes—from the lush Mekong Delta in the south to the mountainous highlands in the north—the country also boasts key urban centers^ref.no.19,20. Vietnam’s economy is supported by a multifaceted industrial structure, encompassing manufacturing, agriculture, and services. The country is a leading global exporter of rice, coffee, garments, and electronics. Foreign direct investment (FDI) has been instrumental in fuelling its industrial growth, especially in the manufacturing and export-oriented sectors. The Vietnamese government has prioritized trade liberalization and regional economic integration, participating in several international agreements, including the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP). Nonetheless, Vietnam continues to face pressing challenges, such as income disparities, environmental degradation, and the need for sustained infrastructure and educational reform.

In the area of healthcare, Vietnam has made notable advancements, particularly in expanding access to medical services for its population. A cornerstone of national policy is the pursuit of universal health coverage (UHC), aiming to deliver affordable and equitable care for all citizens. While the healthcare infrastructure is steadily improving, regional inequities—especially between urban and rural areas—persist. Increasingly, attention is being directed toward digital health solutions, with growing emphasis on the use of health informatics, electronic medical records, and data-driven systems to enhance clinical outcomes. Vietnam’s dedication to public health is evident in its rising investment in healthcare technologies and its efforts to modernize data collection frameworks, including the adoption of real-world data (RWD) to support evidence-informed policy and decision-making.

Japan:

Japan has increasingly adopted the use of real-world data (RWD) in its healthcare sector to enhance public health outcomes, facilitate evidence-informed policymaking, and address the complex needs of its aging population. With a well-established universal healthcare system and a strong emphasis on preventive medicine, Japan offers a highly suitable environment for leveraging observational health data. Information is gathered from a variety of sources, including electronic health records (EHRs), health insurance claims, hospital-based registries, and patient-reported surveys. These data streams are instrumental in tracking treatment effectiveness, analysing healthcare utilization patterns, and identifying epidemiological trends across the population. RWD is especially valuable in Japan for assessing the real-world performance of novel therapeutics and medical technologies, as well as for conducting health technology assessments (HTAs) that inform resource allocation and policy decisions.

Beyond improving clinical care, the strategic application of RWD plays a pivotal role in regulatory oversight. Moreover, Japan is exploring the integration of big data analytics and artificial intelligence (AI) to enhance the interpretation and application of large-scale health datasets. These initiatives are in line with Japan’s broader commitment to digital health transformation, aiming to optimize patient care delivery, improve health system efficiency, and support data-driven public health management.

Europe:

Real-World Data (RWD) in Europe is increasingly being utilized across the healthcare sector to improve patient outcomes, enhance clinical decision-making, and streamline regulatory processes. European countries, through both public and private healthcare systems, collect RWD from a variety of sources, such as electronic health records (EHRs), insurance claims, patient registries, and national health surveys. This data plays a key role in evaluating the effectiveness and safety of treatments in everyday clinical settings, as opposed to controlled clinical trials. By integrating RWD into their healthcare frameworks, European countries aim to optimize healthcare delivery, reduce inefficiencies, and enable more personalized treatment approaches for patients.

The European Medicines Agency (EMA) and other regulatory bodies in Europe are actively working to incorporate RWD into drug evaluation and approval processes. This is particularly important for assessing the long-term safety and effectiveness of new therapies after they enter the market. For instance, RWD is used to identify rare side effects or to monitor the performance of medical devices once they are widely adopted. Additionally, RWD helps in health technology assessments (HTA), which are used to guide reimbursement and pricing decisions. Several European countries, such as the United Kingdom, Germany, and France, have advanced in integrating RWD into their healthcare systems, often through collaborative projects like EunetHTA and EHDEN (European Health Data & Evidence Network), which aim to standardize data collection and analysis methods across Europe for more robust, evidence-based health decisions.

Authors contribution:

Manuscript are written by Ms.Shraddha Shivde and Mr.Hrishikesh Jadhav. Guided by S. S, designed and performed research by Mr.Hrishikesh Jadhav.

Funding Information:

The authors are declaration the review is conducted absence of any commercial and financial could be constructed as a potential for this project. This literature review is funded by contribution of all authors S. S, H. S, N. K, V. M, H. P, P. S, J. P. The funder plays important role in preparation analysis and composition of manuscript or development of project.

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