  The development and approval of new treatments generates large volumes of
results, such as summaries of efficacy and safety. However, it is commonly
overlooked that analyzing clinical study data also produces data in the form of
results. For example, descriptive statistics and model predictions are data.
Although integrating and putting findings into context is a cornerstone of
scientific work, analysis results are often neglected as a data source. Results
end up stored as "data products" such as PDF documents that are not machine
readable or amenable to future analysis. We propose a solution to "calculate
once, use many times" by combining analysis results standards with a common
data model. This analysis results data model re-frames the target of analyses
from static representations of the results (e.g., tables and figures) to a data
model with applications in various contexts, including knowledge discovery.
Further, we provide a working proof of concept detailing how to approach
analyses standardization and construct a schema to store and query analysis
results.
