Analyzes Real-World Treatment Patterns of a Study Population of Interest

Computes treatment patterns within a given cohort using the Observational Medical Outcomes Partnership (OMOP) common data model (CDM). As described in Markus, Verhamme, Kors, and Rijnbeek (2022) .

TreatmentPatterns

Supported Databases

Database	DatabaseConnector (JDBC)	CDMConnector (ODBC)
PostgreSQL
SQL Server
Snowflake
Oracle
Redshift
Spark
Iris	*
BigQuery

*Faulty Test Environment

Markus A, Verhamme K, Kors J, Rijnbeek P (2022). “TreatmentPatterns: An R package to facilitate the standardized development and analysis of treatment patterns across disease domains.” Computer Methods and Programs in Biomedicine.

This R package contains the resources for performing a treatment pathway analysis of a study population of interest in observational databases. The package partially relies on the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), but the main parts of the package are also usable with different data formats.

Features

• Compatible with JSON, SQL, or CapR cohorts.
• Compatible with DatabaseConnector, CohortGenerator, and CDMConnector.
• Stratification by age, sex, and index year.
• Treatment type agnostic.
• Full control over treatment pathway definition:
  1. Duration of treatments
  2. Overlap of treatments
  3. Gaps between treatments
• Intermediate patient level results can be reviewed, aggregate data can be shared.
• Easily integrate Sankey diagrams and sunburst plots (htmlWidget) into ShinyApps or web-pages.

Installation

You can install the most recently released CRAN version of TreatmentPatterns with:

install.packages("TreatmentPatterns")

Or from GitHub with:

remotes::install_github("darwin-eu-dev/TreatmentPatterns")

You can install the development version of TreatmentPatterns from GitHub with:

install.packages("remotes")
remotes::install_github("darwin-eu-dev/TreatmentPatterns@dev")