Researchers also identified potential drivers of RI system performance from data extracted from written sources and key informant interviews, using the following criteria:

1. Association with RI system performance—is there improved system performance or improved outcomes?
2. Frequency of the evidence or occurrence of the driver—how often does this driver area emerge?
3. Triangulation of data sources—is this driver emerging from one or more data source?
4. Strength of evidence—is the evidence categorized as 3 or 4 (using ARISE definitions)?
5. How driver resonates with the experience of technical team—is it plausible or known to be important for positive performance?

Researchers recorded each potential driver that emerged in a “driver journal,” which documented evidence and project thinking about the particular driver area. From that exhaustive list, a short list of drivers that have both a theoretical basis, suggesting importance, and those that that emerged from a larger and more rigorous evidence base, was derived.