PatientLevelPrediction

Introduction

An R package for building patient level predictive models using data in Common Data Model format.

Features

• Takes a cohort and outcome of interest as input.
• Extracts the necessary data from a database in OMOP Common Data Model format.
• Uses a large set of covariates including for example all drugs, diagnoses, procedures, as well as age, comorbidity indexes, etc.
• Large scale regularized regression to fit the predictive models.
• Includes function for evaluating predictive models
• Supported outcome models are logistic, Poisson, and survival (time to event).

Screenshots

Calibration plot	ROC plot

Technology

PatientLevelPrediction is an R package, with some functions implemented in C++.

System Requirements

Requires R (version 3.1.0 or higher). Installation on Windows requires RTools. Libraries used in PatientLevelPrediction require Java.

Dependencies

• Cyclops
• DatabaseConnector
• SqlRender

Getting Started

1. On Windows, make sure RTools is installed.
2. The DatabaseConnector and SqlRender packages require Java. Java can be downloaded from http://www.java.com.
3. In R, use the following commands to download and install PatientLevelPrediction:

install.packages("devtools")
library(devtools)
install_github("ohdsi/SqlRender") 
install_github("ohdsi/DatabaseConnector") 
install_github("ohdsi/Cyclops") 
install_github("ohdsi/PatientLevelPrediction") 

Getting Involved

• Vignette: Building patient-level predictive models
• Package manual: PatientLevelPrediction.pdf
• Developer questions/comments/feedback: OHDSI Forum
• We use the GitHub issue tracker for all bugs/issues/enhancements

License

PatientLevelPrediction is licensed under Apache License 2.0

Development

PatientLevelPrediction is being developed in R Studio.

###Development status Beta

Acknowledgements

• This project is supported in part through the National Science Foundation grant IIS 1251151.