Published

June 28, 2025

Packages

Our packages

Oxinfer developed several packages to work with the OMOP Common Data Model:

omopgenerics

Methods and Classes for the OMOP Common Data Model

Provides definitions of core classes and methods used by analytic pipelines that query the OMOP (Observational Medical Outcomes Partnership) common data model.

PatientProfiles

Identify Characteristics of Patients in the OMOP Common Data Model

Identify the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model.

CohortConstructor

Build and Manipulate Study Cohorts Using a Common Data Model

Create and manipulate study cohorts in data mapped to the Observational Medical Outcomes Partnership Common Data Model.

CodelistGenerator

Identify Relevant Clinical Codes and Evaluate Their Use

Generate a candidate code list for the Observational Medical Outcomes Partnership (OMOP) common data model based on string matching. For a given search strategy, a candidate code list will be returned.

visOmopResults

Graphs and Tables for OMOP Results

Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.

IncidencePrevalence

Estimate Incidence and Prevalence using the OMOP Common Data Model

Calculate incidence and prevalence using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Incidence and prevalence can be estimated for the total population in a database or for a stratification cohort.

DrugUtilisation

Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model

Summarise patient-level drug utilisation cohorts using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. New users and prevalent users cohorts can be generated and their characteristics, indication and drug use summarised.

CohortCharacteristics

Summarise and Visualise Characteristics of Patients in the OMOP CDM

Summarise and visualise the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model (CDM).

CohortSurvival

Estimate Survival from Common Data Model Cohorts

Estimate survival using data mapped to the Observational Medical Outcomes Partnership common data model. Survival can be estimated based on user-defined study cohorts.

CohortSymmetry

Sequence Symmetry Analysis Using the Observational Medical Outcomes Partnership Common Data Model

Calculating crude sequence ratio, adjusted sequence ratio and confidence intervals using data mapped to the Observational Medical Outcomes Partnership Common Data Model.

OmopSketch

Characterise Tables of an OMOP Common Data Model Instance

Summarises key information in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Assess suitability to perform specific epidemiological studies and explore the different domains to obtain feasibility counts and trends.

PhenotypeR

Assess Study Cohorts Using a Common Data Model

Phenotype study cohorts in data mapped to the Observational Medical Outcomes Partnership Common Data Model. Diagnostics are run at the database, code list, cohort, and population level to assess whether study cohorts are ready for research.

omock

Creation of Mock Observational Medical Outcomes Partnership Common Data Model

Creates mock data for testing and package development for the Observational Medical Outcomes Partnership common data model. The package offers functions crafted with pipeline-friendly implementation, enabling users to effortlessly include only the necessary tables for their testing needs.

OmopConstructor

What the Package Does (One Line, Title Case)

What the package does (one paragraph).

OmopViewer

Visualise OMOP Results using ‘shiny’ Applications

Visualise results obtained from analysing data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model using ‘shiny’ applications.