What is real-world data?
Written by Dr Andrea Cowley
Real-world data (RWD) is defined as data derived from a number of sources that are associated with outcomes in a heterogeneous patient population in real-world settings.1,2 Analysis of this data generates real-world evidence that, in turn, can generate meaningful insights into unmet needs, interventional pathways and the clinical and economic impact on patients and healthcare systems (Figure 1).1,3
Figure 1. Real-world data driving meaningful insights for decision-makers.
By providing greater clarity on safety and effectiveness, RWD are able to precisely identify the risk to benefit ratio, efficiently demonstrate product value for economic evaluation and maximise return on investment.1 Hence, it is increasingly sought after by decision-makers across all levels of healthcare, from government to the clinic.
Drivers of real-world data requirements
Payers are transitioning from transaction-based, fee-for-service to a risk-shared, value-based pay system.1,4 As a result, payers are increasingly demanding RWD to better manage uncertainty around interventions’ safety and effectiveness for approval and reimbursement decision-making.1
Unfortunately, due to inherent limitations with the study design, data from randomised controlled trials (RCTs) are inadequate for demonstrating an intervention’s long-term safety and effectiveness or its generalisability.
Furthermore, there is an increasing need for additional insights on epidemiology, compliance, adherence and costs in a realistic environment, which cannot be obtained through RCTs but by using a number of RWD sources (Figure 2).
Figure 2. Sources of real-world data.2
Limitations and challenges with RWD
Despite the increasing reliance on RWD, challenges and limitations exist that complicate the generation, collection and use of this data (Figure 3).
The amalgamation of RWD from multiple sources presents several issues including gaps and inconsistencies in the data arising from differences in the study design and the methodologies for collection and formatting.1 These inconsistencies can also be attributed to disparities in the regulation of RWD collection, use and communication by the biopharmaceutical and medical devices industry compared to other stakeholders.1
Studies generating RWD are considered less statistically rigorous than RCTs with inadvertent biases.1,2,5 Furthermore, there is a significant amount of diversity between geographies with regards to clinical practice and the quality and detail of the data.2 As a result the RWD sets are complicated and difficult to interpret.1
Traditionally, medical consensus on health technologies and clinical practice is developed based on peer-reviewed publication of RCTs, however this process can be slow.1 As the ability of stakeholders to conduct real-world studies increases so too does the pace at which this RWD is generated and this may exceed the rate at which medical consensus is achieved.1
The cost of generating and maintaining RWD is an important limitation, more so for other stakeholders such as patient and professional groups whose funding is less stable and most likely reliant on government bodies.1 Funding of real-world studies may also be affected by issues and concerns with the security and anonymity of the data generated.1 This has not been helped by recent breaches in privacy that have affected patients’ and healthcare professionals’ confidence thus increased their reluctance to be involved in real-world studies.1,6
Figure 3. Challenges with generating robust and usable RWD.1,2
CRC understands the importance of RWD
At CRC we understand RWD and its importance in demonstrating product value for approvals and reimbursements. Using our extensive knowledge of and expertise in the drug development lifecycle and the biopharmaceutical industry we can work with you to strategise, design and manage your clinical trials and real-world studies. We can also assist in patient and HCP recruitment by leveraging our existing key opinion leader networks. We understand that effective communication of RWD is essential and our expert team are ready to help you achieve this goal through innovative and strategic publication planning and management.
- The Network for Excellence in Health Innovation. Real world evidence: A new era for health care innovation. (Cambridge MA, 2015).
- Annemans, L. Aristides, M. & Kubin, M. Real-life data: A growing need. ISPOR Connections. (South Lawrenceville, 2007) https://www.ispor.org/News/articles/Oct07/RLD.asp
- Elton, J. The reality behind real-world data and real-world evidence. (London, 2015). http://social.eyeforpharma.com/column/reality-behind-real-world-data-and-real-world-evidence.
- Optum. Can value-based reimbursement models transform health care? (Eden Prairie, 2013).
- Page, M. Get real: Demonstrating effectiveness with real world evidence. (Cincinnati, Ohio).
- Anderson, S. Medicare dataset pulled after academics find breach of doctor details possible. (Sydney, 2016). http://www.abc.net.au/news/2016-09-29/medicare-pbs-dataset-pulled-over-encryption-concerns/7888686