Real-world evidence is being used by the health care sector to support the safe development of new medical interventions including devices, services and biopharmaceuticals. Before, it was only considered in the post-approval phase when bringing a new therapy to market, but now, it is being considered earlier in the clinical trial process. What is real-world evidence, how is it used, why is it important, and how can you start harnessing it?
What is Real World Evidence?
Evidence obtained from analyzing real-world data (RWD) is referred to as real-world evidence (RWE). To generate RWE, the RW data must be analyzed. Different statistical analysis can be done through modeling, or by performing a variety of different studies. Technology, like IBM’s Watson, can also be used for data analysis where it aggregates and reports on insights derived from multifaceted real-world data sets.
This real-world data comes from routine delivery of medical care. For example, RWD can come from clinical data such as electronic health records (EHRs) and electronic Case Report Forms (eCRFs). Patient generated data including medical charts, data gathered from mobile devices or wearables, and Patient Reported Outcomes (PRO). PROs are completed by patients and give researchers firsthand patient perspectives and an understanding of events that go on outside of appointments, operations, and hospital stays. Available public health data such as disease registries, prescription habits, and the use of healthcare services, can give data for the general population. Lastly, cost data in the form of claims or billing activities can provide a monetary indicator for healthcare spending. Patient identity markers are expressly removed to maintain patient privacy. The RWE extracted from these data sources provide insight into elements that are not included in randomized clinical trials (RCT).
How is RWE used?
Real-world evidence enables researchers to assess the efficacy of medical treatments or interventions while considering other circumstances and variables not always accounted for with RCTs. A randomized controlled trial (RCT) enrolls a small subset of the population and examines how different groups react to a novel therapy in a controlled setting. While RCTs are considered ‘the gold standard’ in clinical testing, they are expensive and take a long time to complete. Rather than using RCTs alone, RWE can provide a more comprehensive insight of how a new treatment option will work in the “real world” and for a more diverse population. By supplementing RCTs with RWE, researchers can gain a better understanding of what works for different sub-populations.
RCT suffer from a narrow pool of trial participants and are not truly representative of the general population. Because RCTs have strict inclusion and exclusion criteria for enrollment, certain populations are expressly not represented in the trial, one such example is pregnant women. It is also the case that trials struggle to recruit candidates from certain ethnic populations, as is common for Hispanic communities. With a lack of diverse representation in clinical trials, the results from RCT do not consider all patient characteristics including age, gender, ethnicity, pregnancy, medical history, etc. However, using RWE can fill in some of these gaps.
Why is RWE important?
Real-world evidence can provide insights into how medicines work in certain patient subgroups that may not have been investigated in RCTs. RWE, for example, can allow researchers to investigate how novel medicines function in patients within specific age ranges, or specific socio-demographic groupings. Real-world evidence can also help researchers comprehend what occurs to a patient over the course of his or her life, not only during the RCT period, to assess the treatment’s effectiveness. How people use a product, what symptoms it does improve, side effects — all of that can be different from what is observed in a controlled trial in a clinic. The healthcare industry is constantly working on improving patient outcomes and reducing hospitalization rates. One way to achieve this is to work on more tailored therapies and personalized medicine. Because RWE insights are so valuable, the FDA employs real-world data and RWE to monitor post-market safety and adverse occurrences, and to support regulatory decisions.
RWE also helps improve healthcare decisions and is used in health economics and outcomes research (HEOR). HEOR measures the outcomes of healthcare interventions and the effect they have on patients to provide data and insights for healthcare decision makers. These decision makers include clinicians, governments, payers, health ministries, patients, to name a few. For these stakeholders, real-world data collection, analysis and reporting is essential.
How to collect and use RWE?
With so many varied data sources (clinical data, patient generated data, public health data, cost data) healthcare stakeholders may choose to use clinical trial and data science services. Evident IQ provides researchers with software to collect real-world data and can provide support to analyze RWD to generate and report on RWE.
As part of clinical trial data collection services, EvidentIQ offers eCRF Setup which simplifies electronic data collection forms, design branching questions, develop in-form and cross-form validations and edit checks to maximize data cleaning at the field level. They also provide configuration support for multilingual eCRF forms, and any localization support needed to configure the application workflow to align with the site’s local processes. Their Patient Reported Outcome (PRO) surveys collect a multitude of data points including treatment preference, quality of life, value of health, disease/treatment burden, and unmet needs. This data is then subject to sophisticated methodologies used to generate unique RWE. Data Linkage is one such method. Data Linkage helps match and merge records from different sources to get a richer dataset and more valuable evidence. EvidentIQ uses significant clinical data expertise, data science analysis, and access to Carenity patient platform, to successfully conduct state of the art data linkage studies. Their innovative data linkage capabilities combine unique self-patient reported data with biomarkers collected by a wearable/sensor through continuous monitoring, bringing RWE to the next level.
Real-world evidence is growing in popularity. Before it was only considered in the post-approval period, but now, it is being considered earlier in the clinical trial process. Using RWE at an early stage in treatment development is a critical consideration for healthcare stakeholders and is driving the trend of gathering more RWE and ultimately improving the safety and effectiveness of medical therapies.