Strategies for Working With Real World Data
And because it’s so abundant, RWD is being mined everywhere, from the local country level to the ivory towers of academia. The result? Competitors, regulators and payers often know more about medicine usage than the companies that created them. In fact, pharma-generated RWD has influenced more than 25 percent of observed decisions relating to pricing and positioning.
How should pharma respond? In Strategies for Working with Real World Data, FirstWord makes a strong case for pharma-payer collaborations, as seen in the compelling work done between Merck and the Regenstrief Institute. Based on expert interviews, wide-ranging research and case studies, this report examines how the use of RWD is transforming the industry. It reveals what works—what doesn’t—and what pharma needs to do to stay ahead of the game.
Key Report Features
- Detailed overview of the dynamics driving RWD uptake by payers, providers and pharma
- Analysis of the application of RWD to decision making in 10 countries Case studies of pharma-payer collaborations
- Interview with Dr. Jon Duke of the Regenstreif Institute about a five-year RWD collaboration with Merck
- Why should the pharmaceutical industry take up RWD?
- How can RWD be mined to optimise decision-making strategies?
- Where does RWD exist and who gathers it?
- How can companies organise their RWD efforts?
- What is the future of RWD in ‘reality healthcare’?
Pharma companies are well aware of the growing importance of RWD. According to a recent in-depth survey of 36 life science professionals from a range of functions within 14 companies, two-thirds of respondents cited the use of RWD as critical and the remaining one-third as important. The survey, conducted by technology company Computer Science Corporation (CSC), tried to answer basic questions thrown up as pharma companies expand their capacity to use RWD. These include the top reasons for using RWD, the level of adoption of RWD in the product lifecycle, which data sources to use and how best to go about leveraging this information across the enterprise.
There are two basic overall strategies with regard to RWD. The first is perhaps best described as going-it-alone, the default position whereby companies source data off-the-shelf as and when they need it. This brings huge inefficiencies in terms of using disparate data sets or paying for the same one several times over as different departments work with it. They are all different, containing different data sourced from different healthcare systems or insurance companies and using different coding systems. As the late Harry Guess, a pioneer in the use of RWD, once wisely said, “If you’ve seen one database you’ve seen one database.”The most important thing is to know how and why they have been created.
The second is to work collaboratively with the people, usually the payers, who have the data. Most of the larger companies are moving from the first to the second, devoting more resources to sourcing data, understanding the strengths and weaknesses of that data and also keeping abreast of the various methodologies that are evolving for making sense of it.
In the transition period, validation of research questions for RWD projects that might emanate from drug safety, R&D, medical affairs or the HEOR team, might be conducted centrally to ensure the right database and robust analytics are brought to bear to ensure the design and approach can best answer those questions.
Before being in a position to select partners with whom to work it is important to take a few critical steps. McKinsey & Co recommend the following steps in formulating an initial strategy. These are similar to those articulated by CSC but are worth repeating.
