At BHE, we spend a lot of time speaking with leaders in the field of real world data about the ways in which they go about generating robust, reliable evidence for use with key stakeholders both internally and externally. Fundamentally, it is the unique way that companies combine database experts, processes, and technology that provides the best indication of success. Below are a few of my thoughts on this topic based on conversations with our clients and industry stakeholders in 2016.
Expansion of Internal Analytics Teams
Along with the growing trend of bringing large datasets in-house, many life science companies are expanding their internal analytics teams to better serve stakeholders who rely on advanced analytics for decision making. The traditional outsourcing model, while still important, is no longer efficient or cost-effective enough to handle the large volume of requests that health economics, epidemiology, drug safety, and commercial analytics groups receive. To deal with this paradigm shift, companies are building centralized functions in the form of Real World Evidence (RWE) or Centers of Excellence (CoE) teams. These teams typically have three main responsibilities:
- Centralize Real World Data (RWD) assets and tools for analysis
- Reduce the friction between groups to generate efficient results
- Develop and implement standard methodologies
Finding Talent Is a Challenge
The one thing all the companies I’ve spoken to agree on is that finding talent is extremely difficult. An effectively run data and analytics group requires prioritizing talent who know and understand data, technology, and informatics. However, these skill sets may not apply to many graduates of epidemiology and health economics programs.
Technology Is Key to CoE Success
Technology also plays a key role in any centralized analytics group, especially as expectations increase. One company I recently spoke with anticipates that the number of projects their analytics group is expected to complete will triple in the next three years. Traditional methods of programming become bottlenecks to productivity as the queues for analytics teams continue to grow. Scaling with hard-to-find analysts alone, may not be the entire solution to growth in demand for real-world evidence.
Looking Forward in 2017
Our work with RWE groups provides us with a unique window into industry trends. We look forward to sharing our knowledge and also learning from others, as new opportunities arise with the 21st Century Cures Act and the proliferation of new, exciting data sources that can be brought to life via technologic advances.