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ReviewR is a portable Shiny tool to help you explore patient-level electronic health record data and perform chart review in a single integrated framework. It is is distributed as an R package using the golem framework.
This tool supports browsing clinical data in many different formats including multiple versions of the OMOP common data model as well as the MIMIC-III data model. If you are using a different data format, ReviewR can be easily customized to support your use case (see Support a Custom Data Model vignette).
At present ReviewR supports data stored in Google BigQuery or Postgres, although it can be easily customized to access any database supported by dbplyr (see Support a New Relational Database Management System vignette).
To record chart review data, ReviewR supports connections to REDCap (Research Electronic Data Capture).
Full documentation available at reviewr.thewileylab.org.
Install ReviewR from CRAN:
install.packages('ReviewR')First ensure you have the library devtools installed. If
you do not, please install using:
install.packages('devtools')Then install the latest development release of ReviewR using:
devtools::install_github('thewileylab/ReviewR')To run the application from your local computer simply run:
ReviewR::run_app()If you would like to deploy ReviewR on a server, see the Shiny Server Deployment vignette. If you will be connecting to clinical data using Google BigQuery please see Google BigQuery Deployment vignette.
Once the app has loaded, please navigate to the ‘Setup’ tab (found in the left navigation menu).
First, in the left panel, select which type of database you would like to connect to (e.g., Google BigQuery). You may also choose to select the Demo SQLite module to access synthetic clinical data in order to explore how ReviewR works without connecting to your own database. For BigQuery connections, simply press “Sign in with Google” and you will be redirected to authenticate with Google and then return to the application.
Once you have successfully connected to a patient database, navigate to the ‘Patient Search’ tab, located in the left sidebar. On this tab you can see basic demographic information about each patient record. Select a particular patient ID you would like to view and the ‘Chart Review’ tab will open. The top left panel includes the same demographic information found in the ‘Patient Search’ table, while the bottom panel contains the clinical information available for that record with tabs for different data types. You can filter any individual column by typing in the text box beneath each column name, or you can search across all columns using the search bar in the upper right corner of the panel. Note that both regular text as well as regular expression based searches are supported. If you would like to move to another patient you can use the patient navigation panel in the upper right corner. You can navigate to a specific patient using the dropdown selector or simply move to the next or previous patient records using the buttons.
Once the app has loaded, please navigate to the ‘Setup’ tab (found in the left navigation menu). On the setup tab, enter your institution’s REDCap URL and an API token for a REDCap project. This project may contain multiple REDCap instruments for data collection which are selectable from the Setup interface. Once connected, please select the REDCap field that contains your patient information as well as the field that will contain reviewer information. Enter your name to keep track of who has completed the review.
First, in the left panel, select which type of database you would like to connect to (e.g., Google BigQuery). You may also choose to select the Demo SQLite module to access synthetic clinical data in order to explore how ReviewR works without connecting to your own database. For BigQuery connections, simply press “Sign in with Google” and you will be redirected to authenticate with Google and then return to the application.
Next, you will want to connect to a REDCap project to store the results of your chart review. In the right panel of the ‘Setup’ tab, enter your institution’s REDCap URL and the API token for your desired REDCap project and then click ‘Connect to REDCap’. Next, configure your REDCap instrument by selecting which variable in your collection instrument will store the Patient ID value, ReviewR will automatically populate this question with the chart you are viewing. If you also want to record who is performing the chart review you can configure the question that identifies the chart reviewer and enter the name so it can also be auto-entered for each review session. If you do not want to record the reviewer identifier just select ‘(Not Applicable)’. When you have completed both selects click ‘Configure REDCap Instrument’. Congratulations - you are ready to perform your chart review!
You can now navigate to the ‘Patient Search’ tab, located in the left sidebar. On this tab you can see basic demographic information about each patient record as well as the review status for the record (e.g., “Review Not Started”, “Complete”, etc.). If you have enabled support for multiple reviewers, then the review status of all other reviewers is provided in addition to the status of the configured reviewer. Select a particular patient ID you would like to view and the ‘Chart Review’ tab will open. The top left panel includes the same demographic and review status information found in the ‘Patient Search’ table, while the bottom left panel contains the clinical information available for that record with tabs for different data types. You can filter any individual column by typing in the text box beneath each column name, or you can search across all columns using the search bar in the upper right corner of the panel. Note that both regular text as well as regular expression based searches are supported. Chart review data can be entered into the middle right panel. This panel contains each of the questions in your REDCap project. If your project has multiple instruments, use the drop down to select the instrument you would like to use. You’ll notice that the questions identifying the patient and reviewer identifier are pre-filled in and not editable. Once you have finished with your entry for a record, set the REDCap status in the lower right panel and click ‘Save to REDCap’. You must click ‘Save to REDCap’ or the data will not be saved in the app or uploaded to REDCap! If you would like to move to another patient you can use the patient navigation panel in the upper right corner. You can navigate to a specific patient using the dropdown selector or simply move to the next or previous patient records using the buttons.
Please note that while our tool is designed to be as secure as your local computer or server environment, you should check with your clinical data warehouse and/or IT departments to make sure that you are authorized to use our tool with real patient data. We make no guarantee of security or privacy.
If you encounter bugs, errors, issues or other general unpleasantness, please let us know on GitHub.
Please note that the ReviewR project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.