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Utilising RWE to reduce burden of noncommunicable diseases

We summarise a recent article, published in Health Services and Outcomes Research Methodology, that explored the power of real-world data (RWD) and real-world evidence (RWE) in helping address the disease burden of noncommunicable diseases.

Noncommunicable diseases

Noncommunicable diseases (NCDs) are the leading cause of mortality globally. They pose a major global health challenge that impacts people across all countries, regardless of their socioeconomic status. Approximately 30% of NCD-related deaths are premature (occurring before the age of 70) and 85% of these occur in low- and middle-income countries. The prevalence of many NCDs increases with age. Due to an ageing population, this prevalence is likely to increase and accentuate disease burden.

The World Health Organisation (WHO) has identified four main types of NCDs that contribute the greatest disease burden. These include cardiovascular diseases (CVDs), cancers, chronic respiratory diseases and diabetes. In addition, neurological conditions and mental health disorders have emerged as major causes of disability.

NCDs are chronic and slow progressing. They are a major cause of morbidity and disability. Those who are socioeconomically disadvantaged are often at a higher risk of developing NCDs. They pose a huge medical and economic burden on society. In the midst of an ongoing pandemic, NCDs pose an even greater threat.

Governments and international organisations across the world are committed to NCD prevention and control. RWD and RWE can play an important role for organisations and governments to help them make informed decisions regarding NCD prevention and control.

Harnessing RWE

There is a lack of RCTs designed to assess the burden and degree of comorbidities occurring with NCDs. Therefore, RWE is the greatest resource available to study this area. Global advances in information technologies and telecommunication infrastructures have enabled a large of amount of RWD to be generated from diverse data sources. Relative to RCTs, generating RWD is low cost and rapid, often being stored and processed in considerable quantities. Pharmaceutical companies are now investing in their RWE programs to increase their capabilities in this area, across all aspects of the drug development and approval process.


RWE is the foundation for understanding disease epidemiology. It plays a key role in quantifying disease burden. It can also be used to detect vulnerable populations and identify the most influential risk factors. More recently, RWE has been used in the regulatory arena for gaining label expansion as well as accelerating drug approvals. Most importantly, RWE provides an opportunity to study diverse populations that are frequently underrepresented in both clinical and observational studies. How patients respond to treatment is important, particularly in areas such as NCDs. For example, several observational RWD studies have found commonly occurring NCDs as frequent comorbidities for COVID-19. This understanding can help deploy preventative strategies. RWE can also be used to measure and evaluate effectiveness and cost-effectiveness of treatments.

Efforts to reduce populations’ risk of NCDs can be supported by RWE to help monitor incidence and prevalence trends and risk factors. It can be used to target prevention measures at populations that are particularly vulnerable to NCDs. RWE also allows a treatment’s effectiveness to be evaluated in real-world practice. Therefore, RWE is important to assess the long-term safety of medications and help identify rare adverse events. It can also provide a more holistic understanding of patients, which can result in more comprehensive disease management.


The availability of RWD is dependent on technology, digitisation, data capture systems and data flow regulations. When using RWD for research, data accuracy, reliability and quality must be taken into account. Given the variety of data sources for RWD, important issues arise around data integrity, access, security, privacy and ethical standards for data use. A key consideration in RWD is informed consent. Informed consent can limit access to certain types of data or information. Advances in blockchain technology however, are enabling dynamic informed consent. Data and privacy protection laws are additional complications that must be carefully considered when utilising data.

A major barrier is access to relevant data as data is often housed in separate repositories. Language differences between countries can also present a common challenge in this regard. Even within the same country, linking patient-level data across various sources can be problematic. Databases can be difficult to standardise, making efforts to harmonise data important in order to improve data reproducibility.


Addressing the substantial burden associated with NCDs is critical. This is even more prominent in the era of COVID-19 given the increased risk of poor clinical outcomes in patients with NCDs who become infected with COVID-19. The authors anticipate that over the coming years, the power of RWD and RWE to address this burden will become apparent. It is important to recognise both the challenges and limitations of RWD and RWE to ensure that they are utilised correctly. In addition, partnerships and collaborations will play a key role in improving the utilisation of RWE and, in turn, benefiting the prevention and management of NCDs.

Image credit: By pikisuperstar –

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