By David Thompson, Ph.D.
Manufacturers generally plan Phase II-III research with great care, but too often view Real World Evidence Generation (RWE) as a ‘tick the box’ activity. It is a mistake. Real-world research design is more complicated than clinical trial design, its complexity due to a multitude of factors including the different evidence needs of various stakeholders in the health system, different outcome measures available to meet these needs and the different methodological approaches that can be used to collect clinical, economic and real-world data.
The most frequently used study designs for phase IV research include:
- Retrospective analyzes of computerized health records (administrative complaints and / or EHR)
- Manual card review
- Prospective observational studies and registers
- Pragmatic clinical trials
- Randomized controlled trials
- Economic modeling
Selecting the most suitable and profitable research design can be quite difficult. This is especially the case when stakeholders are not involved early in the process. But even with strong stakeholder engagement from the start, identifying the most appropriate study design remains a challenge due to the multiple factors (data sources, methodologies, outcome measures, etc.) that must be taken into account. To facilitate this process, we have developed and tested an algorithm that has been found to be useful in structuring decision making in real world research design.