CI5: Development and refinement of toolkits for routine use in the EHR and claims Data Partner network
Description
This project is designed to solve the problem of inconsistent or inefficient data analysis capabilities across the EHR and claims Data Partner network. It aims to create standardized, reliable analytical tools that can be routinely deployed across different data partners to improve the consistency, quality, and efficiency of pharmacoepidemiologic analyses within the Sentinel System.
Detailed example
Regularized machine learning tools (e.g., Least Absolute Shrinkage and Selection Operator (LASSO)-based models) combined with targeted learning methods for improved large-scale covariate adjustment
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
improved confounding control when using Electronic Health Record (EHR) data for drug safety studies, leading to more reliable conclusions about medication risks and benefits in real-world populations.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Electronic Health Record (EHR) Data Elements