README.md

In OHDSI/CemConnector: OHDSI Common Evidence Model (CEM) Connector

CemConnector

CemConnector is built on top of HADES.

Introduction

This is an API and client for the Common Evidence Model that takes in data from clinical trials, spontaneous reports, labels and literature.

Features

• Plumber API that sits on top of CEM database to allow access to common evidence model data
• Database and Web backends that have equivalent functionality
• Fast, programmatic way of getting negative controls from CEM
• Get all related data for sets of standard conceptsets

Example

library(CemConnector)
cemConnectorUrl <- "https://cem.ohdsi.org"
cemConnection <- createCemConnection(apiUrl = cemConnectorUrl)

myExposureConceptSet <- data.frame(conceptId = 1201620, includeDescendants = 1, isExcluded = 0)

# Get 50 negative control concepts for this exposure
cemConnection$getSuggestedControlCondtion(myExposureConceptSet)

# Get any related evidence for this exposure and an outcome of interest
myOutcomeConceptSet <- data.frame(conceptId = 4149320, includeDescendants = 1, isExcluded = 0)
cemConnection$getRelationships(myExposureConceptSet, myOutcomeConceptSet, conditionSiblingLookupLevels = 1)

For instructions on building good concept sets see PHEOBE.

Technology

CemConnector is an R package.

System Requirements

Requires R. Libraries used in CemConnector require Java.

Getting Started

1. See the instructions here for configuring your R environment, including Java.

2. In R, use the following commands to download and install CemConnector:

r install.packages("remotes") remotes::install_github("ohdsi/CemConnector")

User Documentation

Support

• Developer questions/comments/feedback: OHDSI Forum
• We use the GitHub issue tracker for all bugs/issues/enhancements

Contributing

Read here how you can contribute to this package.

License

CemConnector is licensed under Apache License 2.0

Development

CemConnector is being developed in R Studio and PyCharm (with R plugins).

OHDSI/CemConnector documentation built on Aug. 5, 2023, 2:47 p.m.