rEHR

rEHR extracts, cleans, and analyzes structured Electronic Health Record (EHR) data to enable reproducible clinical and epidemiological analyses.

Key Features:

• Rapid Data Access: An import function connects directly to database backends to accelerate data access.
• Efficient Data Extraction: Provides generic query functions for extracting complex datasets.
• Longitudinal Data Processing: Supports extraction of longitudinal data with a single command and leverages parallel processing to expedite computationally intensive tasks.
• Data Manipulation Functions: Includes functions for cutting data by time-varying covariates, matching controls to cases, unit conversion, and constructing clinical code lists.
• Synthesis of Dummy EHRs: Generates synthetic dummy EHR datasets for testing and validation.

Scientific Applications:

• Primary care EHR research (CPRD): Prepares research-ready datasets from large-scale primary care EHR databases such as the Clinical Practice Research Datalink (CPRD) to support longitudinal analyses and control-matched cohort studies.

Methodology:

rEHR connects to database backends via an import function, exposes generic query functions, supports single-command longitudinal extraction, leverages parallel processing, and provides a common interface to multiple EHR systems.