Rx Data Integrity Review
Description
The current process for conducting the Rx Data Integrity review is time intensive and requires reviewers to manually review online formularies in a condensed timeline. The purpose of this proposal is to develop a new process, which will automate as much of the review as possible, using existing language models as well as large language models (LLM) to introduce efficiencies and increase data accuracy.
Detailed example
automate as much of the review as possible, and increase data accuracy
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
A Python-based automation pipeline will download PDFs and extract required Rx information in appropriate format for review
Controls / human review
ATO: Not reported; PIA: Not published