Benjamin S. Glicksberg 2018-19
PatientExploreR is an extensible application built on the R/Shiny framework to interface with the Observational Health Data Sciences and Informatics (OHDSI) OMOP Common Data Model. Briefly, OMOP is a standardized relational database schema for Electronic Health Record (EHR) or Electronic Medical Record (EMR) data (i.e., patient data collected during clinical visits to a health system). The main benefit of a standardized schema is that it allows for interoperability between institutions, even if the underlying EHR vendors are disparate.
For a detailed description of the OMOP common data model, please visit this helpful wiki.
In its backend, OMOP relies on standardized data ontologies and metathesaureses, such as the Unified Medical Language System (UMLS). Much of the underlying logic of the app for interfacing with OMOP data is adapted from our ROMOP package (further description and details can be found in ROMOP's GitHub page).
Glicksberg BS, Oskotsky B, Thangaraj PM, Giangreco N, Badgeley MA, Johnson KW, Datta D, Rudrapatna VA, Rappoport N, Shervey MM, Miotto R. PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model. Bioinformatics. 2019 Nov 1;35(21):4515-8.
The Centers for Medicare and Medicaid Services (CMS) have released a synthetic clinical dataset DE-SynPUF) in the public domain with the aim of being reflective of the patient population but containing no protected health information. The OHDSI group has underwent the task of converting these data into the OMOP CDM format. Users are certainly able to set up this configuration on their own system following the instructions on the GitHub page. We obtained all data files from the OHDSI FTP server (accessed June 17th, 2018) and created the CDM (DDL and indexes) according to their official instructions, but modified for MySQL. For space considerations, we only uploaded one million rows of each of the data files. The sandbox server is a Rshiny server running as an Elastic Compute Cloud (EC2) instance on Amazon Web Services (AWS) querying a MySQL database server (AWS Aurora MySQL).
As the DE-SynPUF data does not contain patient measurement results, we generated a profile for a patient with Chron'€™s Disease with representative clinical data (e.g., disease codes and lab test results) for illustrative purposes. Users can recreate this example patient using the script contained in the "data/new_pt_insert_commands.txt" file. The script is formatted for a MySQL database.
- Personal Computer or Server with connection to internet
- R
- All required packages (see Install.R)
- Database software (either: MySQL, PostgreSQL, Amazon Redshift, Microsoft SQL Server, Microsoft Parallel Data Warehouse, Google BigQuery
- Access to Electronic Health Record data (recommended for use with a de-identified version) that is properly formatted to OMOP Common Data Model v5
- Install renv
- Clone the repo and
cdinto it - At the R prompt, run
renv::restore()to create and activate an environment form the renv.lock file
- Download app from GitHub
- Navigate to directory and run Install.R (Rscript Install.R) to install all required packages
- Open app using either Rstudio (Run App) or from command line: R -e "shiny::runApp('PatientExploreR.R')"
You must set the following environment variables (substituting in your values as appropriate)
export EXPLORER_PATH_TO_DRIVER='/path/to/dir/containing/drivers/'
export EXPLORER_DBMS='postgresql'
export EXPLORER_USERNAME='myuser@myhost'
export EXPLORER_PASSWORD='mytopsecretpassword'
export EXPLORER_HOSTNAME='mydb.mydomain.org'
export EXPLORER_DBNAME='postgres'
export EXPLORER_PORT=5432
Full instructions on these connection parameters can be found from the OHDSI consortium's Database Connector GitHub page.