Real-World-Evidence – Opportunities of Big Data
RWE generally describes „the representation of the reality of (health-)care through mass data sources“ (Behrendt, 2019). A cornerstone of this is the collection of meaningful data on drug efficacy in practice. To date, RWE generation has been limited to registry data. Registry data are data sets that are collected for various purposes and systematically stored in databases. Mostly, they are data sets that are used for billing drug therapies.
These data sets include, among others, insured person master data (gender, age, highest qualification level…), ICD diagnosis data and inpatient stays in hospitals. Clinical staff collect these data manually and transmit them to the respective registers, i.e. the database of the collecting institution (e.g. health insurance companies). Since this is a more or less voluntary, non-standardized survey, the completeness of these data is relatively low. Another problem is that these data are originally collected for the purpose of billing services and drug monitoring, which is very different from the intended use of research. Visibly, voices from the healthcare industry are growing louder for a uniform, standardized data collection.
In addition to the main method of generating RWE, the FDA proposes these other methods:
- Data from electronic health records
- Data from product and disease registries
- Data privately generated by the patient, eg. data from other sources that can provide information about health status, such as mobile devices
MEDIKURA takes a major step forward, by providing an innovative communication platform through which high-quality data from real-world care settings on the effects and side effects of drug therapies are collected. The primary goal is to standardize the data sets and make them available in real time to all affected individuals as well as medical professionals and research companies.
This will provide another information base, through Patient Reported Outcomes (PRO), in drug therapy decisions. After all, Big Data is not much use if it is neither structured, nor accessible. Monitoring the effectiveness of drug therapies is thus to be digitized, simplified and made more cost-effective. At the same time, the large amount of data increases the possibility of applying precision medicine, which will become increasingly important in the future. In this way, treatment strategies and therapies can be individually tailored. Of course, under the strictest data protection and in compliance with all regulations of the DSGVO.
RWE is ideal for shaping the future of evidence-based medicine alongside time-tested research approaches (RCTs) for the reasons outlined above. For example, the time and money involved in RCT studies is not always appropriate.
RCTs are the gold standard for clinical trials. Randomized controlled treatment groups are used. A randomly selected treatment group receives either the drug or a placebo. This study design, conducted as an experiment, is, in evidence-based medicine, particularly suitable for obtaining causality, i.e. an unambiguous answer from an unambiguous question.
However, in addition to these advantages, RCTs also have serious disadvantages, which is why they are not appropriate in some cases. RCTs are often associated with high financial and time costs. In addition, high inclusion criteria reduce the external validity, i.e. the agreement of the results with the overall population. In addition, there is a tight time limit. This is particularly the case for orphan drugs.
Even at the present time, the issue is more topical than ever, now that the first vaccines against the corona virus have been approved. The rapid, conditional approval of the vaccines by the EMA often raises questions about the safety of these vaccines. Because of the limited approval, manufacturers of these pharmaceuticals must ensure in-use data collection. Ie, pharmaceutical manufacturers must continuously collect data from patients taking a drug to monitor for potential side effects. The collection of real-world evidence, e.g. through MEDIKURA’s ImpactMonitor, promises to be an innovative way to solve this problem. Thus, the previously mentioned multitude of data collected from a wide variety of groups of people represent an important advantage of collecting RWE. RWE collected in a complementary manner to RCT studies can significantly condense the final data set. Following market approval, as soon as possible, can provide clear evidence on the benefit-risk profile of drug therapies in young and old, young and old and men and women.
Real-world evidence, which can be generated e.g. via ImpactMonitor, will play a major role in many areas of evidence-based medicine in the future. For example, it helps drug manufacturers to learn more quickly about drug effects and side effects. By seamlessly integrating the ImpactMonitor into existing processes, we support research institutes and manufacturers in collecting the necessary data. In addition, real-world evidence can be collected more quickly when RCT studies on new drugs are not appropriate, e.g. due to time limitations. Thus, our platform makes a significant contribution to drug safety and targeted individual drug prescription to patients.
Behrendt, C.A. Was ist die Realität hinter der Real-World-Evidenz?. Gefässchirurgie 24, 7–8 (2019). Accessed at: https://link.springer.com/article/10.1007/s00772-018-0474-9; Last accessed 04.01.2021
Gliklich, Leavy, Dreyer. Registries for Evaluating Patient Outcomes: A User’s Guide (2020). Accessed at: https://effectivehealthcare.ahrq.gov/sites/default/files/pdf/registries-evaluating-patient-outcomes-4th-edition.pdf; Last accessed 04.01.2021
U.S. Food & Drug Administration. Real-World Evidence (2020). Accessed at: https://www.fda.gov/science-research/science-and-research-special-topics/real-world-evidence; Last accessed 04.01.2021