rdrugtrajectory

rdrugtrajectory analyzes drug prescriptions in electronic health care records (EHRs) from the UK Clinical Practice Research Datalink (CPRD) to enable longitudinal, cohort-level, and survival analyses of prescription patterns.

Key Features:

• Demographic and patient-level analysis: Extracts demographic and patient-level characteristics associated with drug prescriptions from EHR data.
• First drug prescriptions analysis: Identifies and analyzes initiation of first drug prescriptions across cohorts.
• Cohort-wide prescription information: Aggregates comprehensive prescription data across entire cohorts for population-level analysis.
• Cumulative drug prescription events: Examines cumulative prescription events to assess longitudinal prescription burden.
• Longitudinal trajectory analysis: Tracks changes in medication regimens and prescription trajectories over extended periods.
• Survival analysis timeline builder: Constructs survival analysis timelines to evaluate risks associated with switching between drug prescriptions.
• Mean Cumulative Function (MCF) plotting: Generates data structures required for mean cumulative function analyses across multiple groups, enabling visualization of prescription burden by socio-demographic factors such as social deprivation scores or whole cohorts.

Scientific Applications:

• Pharmacoepidemiology: Supports population-level studies of drug utilization, patterns, and safety using CPRD EHR data.
• Healthcare informatics: Facilitates analysis of prescription patterns to inform patient-care decision-making and clinical research.
• Drug discovery support: Provides supplementary prescription-pattern analyses that can inform drug development and repositioning efforts.
• Health services research: Enables evaluation of prescription practices for studies addressing national healthcare processes and policy.

Methodology:

Operates on Clinical Practice Research Datalink (CPRD) Gold datasets (clinical, referral, and therapy data) and implements analysis of first-prescription events, cumulative prescription events, cohort-wide prescription aggregation, longitudinal trajectory analysis, construction of survival analysis timelines, and generation of data structures for mean cumulative function (MCF) analyses.