In today’s atmosphere, Real World Evidence is rapidly drawing attention in the healthcare industry all over the world due to its paramount role in supporting drug development and regulatory decision making. The healthcare system that has been traditionally focused on medical intervention through just episodic conversation with patients is now rapidly transitioning to a new world of patient choice where outcomes and values are captured after the analysis of real world data.
In simpler words, RWE can be explained as a piece of clinical evidence regarding the usage and potential benefits or risks of a medical product that was derived from an analysis of real world data. Data based on factors like genomics, behavior, and social and environmental influences play a critical role in the outcomes and healthcare is finally allowing the technology to capture and analyze such data.
The importance of real-world evidence is helping stakeholders across the entire healthcare value chain which includes physicians, providers, payors, regulatory bodies, and pharmaceutical and medical device manufacturers, by using real-world evidence to guide them in research & development, market access, coverage decisions, and post-market surveillance. However, gaining access to data and analyses and interpreting was difficult previously, given that data was usually locked up in the electronic health record (EHR), often in an unstructured form submitted by healthcare professionals. But today opportunities are growing for real-world evidence research as the technology is maturing, advancements like artificial intelligence (AI) techniques such as natural language processing (NLP) and machine learning are helping clinicians in unlocking this valuable, unstructured information.
Leveraging RWE for everybody’s good
Although randomised controlled trials remain the gold standard of scientific evidence but they only provide a partial view of what might occur within a mass market and today, a growing clamour for a more broad-based approach to accruing scientific evidence is making more rounds in the sector. By using RWE, we can leverage observational insights from a diverse clinical environment which can provide assurance and weight to the findings, as well as reduce the risk of negative outcomes when it enters the marketplace. Factors like these would enable healthcare professionals to determine with increased confidence and quicker understanding as to why differing populations react to treatment, what works best and for who, which will in whole improve clinical and regulatory decision making. By observing how various treatments work across world populations could also have significant cost efficiencies which can be beneficial for the entire healthcare chain.
In addition to its significant benefits in underpinning patient characteristics to drive outcomes, RWE could be a key facilitator in accelerating products to market which ultimately improves the effectiveness of treatments and interventions on a wide scale. Ultimately the more powerful the data is, the more and quicker the statistical confidence there is in the findings.
The value of an end-to-end approach for an accelerated change
Despite some hurdles like the uneven quality of real-world data sources and lack of standardization of RWE analytics, we can see the growing use of real-world datasets. According to Real World Evidence Analytics the RWE analytics market is expected to grow at a CAGR of 15.1% during the forecast period 2022–2029 to reach $2.93 billion by 2029. Even if right now this is occurring in rare disease areas such as oncology, there are some early signs that RWE is starting to be accepted by regulators, physicians, and patients for benefits decisions. While some are recognizing the need for RWE, a greater strategic direction is needed to maximize its impact on health outcomes and commercial success. Strategic coordination among local markets, global organizations and external collaborators will not only raise data quality standards but also build international confidence in the planning, generation and communication of RWE.