Manufacturers typically plan Phase II-III research with the utmost care, but all too often regard real-world evidence (RWE) generation as a “check-the-box” activity. This is a mistake. Real-world research design is more complicated than clinical trial design, its complexity due to a multitude of factors including the differing evidentiary needs of diverse healthcare system stakeholders, the differing outcome measures available to meet those needs, and the differing methodologic approaches that can be used to collect clinical, economic and real-world data.
The most frequently utilized study designs for Phase IV research include:
- Retrospective analyses of computerized health records (administrative claims and/or EHRs)
- Manual chart review
- Prospective observational studies and registries
- Pragmatic clinical trials
- Randomized controlled trials
- Economic modeling
Selecting the most appropriate and cost-effective research design can be quite challenging. This is especially the case when stakeholders are not engaged at the beginning of the process. But even with robust stakeholder engagement from the start, identifying the most appropriate study design is still a challenge because of the multiple factors (data sources, methodologies, outcome measures, etc.) that must be considered. To facilitate this process, we have developed and tested an algorithm that has proven to be useful in structuring decision-making in the design of real-world research.
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