REAL WORLD EVIDENCE (RWE) IN CLINICAL DECISION MAKING
JR Snyman (MBChB, MPharmMed, MD)
Agility Holdings Pty Ltd
With the availability of big data, RWE in research has become a reality, even more so with the recent Covid-19 pandemic which clearly illustrated the speed of evidence development. An example is hydroxychloroquine which, in one moment, would save the world but is then found to have no merit whatsoever in clinical practice.
WHAT IS REAL WORLD EVIDENCE AND IS IT SUFFICIENT TO BASE CLINICAL TREATMENT DECISIONS ON THIS TYPE OF DATA?
Phase 3 clinical drug trials are typically well controlled and have explicit inclusion and exclusion criteria which also drives adherence to protocol for the duration of the study. However, this differs vastly from clinical day-to-day practice, with the most common variations including:
Patients not necessarily adhering to care
Clinicians not applying prescription criteria a strictly as the clinical trial
Patients recruiting additional comorbid conditions that may have been excluded in the Phase 3 studies
As a result, some doubt exists on the ability to extrapolate all Phase 3 trial outcomes to clinical practice. In recognition of this dilemma, the Food and Drug Administration (FDA) agency has included RWE and Real World Data (RWD) as part of their assessment criteria, especially continuous data requirements post registration of medicinal products (refer the 21st Century Cures Act, passed in 2016).
Examples of clinical outcomes in practice that differ from study outcomes are common and, as described above, due to clinical practice not necessarily adhering to Phase 3 study protocols.
For instance, in multiple sclerosis Real World Evidence largely contributes to our understanding of the long-term outcomes of different molecules not immediately obvious during Phase 3 studies (further reading: Multiple sclerosis in the real world: A systematic review of fingolimod as a case study). This new information will assist not only clinical decision making, but also funding guidelines as the perspective of cost-effectiveness may change (further reading, as accessed 15 April 2021: click here).
A MEDICAL SCHEME PERSPECTIVE & CASE STUDY
Medical schemes can play a pivotal role by using their large databases to assess clinical outcomes of interventions over time. This will allow for new insights into treatment outcomes and, as a direct result, the cost effectiveness and fundability of certain products and / or other interventions like medicinal products, diagnostic procedures, or even managed care interventions.
Agility has long embraced this approach of evidence collection and bases its funding decisions not only on published Phase 3 studies, but also additional RWE collected via the Schemes under its administration. Data published or collected elsewhere is also incorporated to further ensure best practice outcomes for Client Scheme members.
In one such study Agility demonstrated that adherence to prescribed medicine and treatment by the clinician is often more important than the price of the prescribed medicine, as the event rate reduction (i.e. reduction in hospital admissions) greatly reduces the total cost exposure.
This outcome now informs the Agility formulary process and has demonstrated significant clinical outcome improvements, as well as cost savings outcomes. Treating patients with type 2 diabetes mellitus (Figure 1 below) with a more flexible formulary, combined with targeted strategies to drive adherence, demonstrated a large benefit in reducing hospitalisation costs while medicine spend remained relatively static. (AJCOR 2017; 1:1 (19-22))
CONCLUSION
As data becomes more readily available, RWE will play an increasingly prominent role in decision making. The recent Covid-19 serves as perfect example where the speed in which quality data can be collected with collaborative efforts was reemphasised.