Title:	A Light-Weight, Portable Tool for Reviewing Individual Patient Records
Version:	2.3.10
Description:	A portable Shiny tool to explore patient-level electronic health record data and perform chart review in a single integrated 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. In addition, chart review information is captured and stored securely via the Shiny interface in a 'REDCap' (Research Electronic Data Capture) project using the 'REDCap' API. See the 'ReviewR' website for additional information, documentation, and examples.
License:	BSD_3_clause + file LICENSE
URL:	https://reviewr.thewileylab.org/, https://github.com/thewileylab/ReviewR/
BugReports:	https://github.com/thewileylab/ReviewR/issues
Depends:	R (≥ 3.5.0)
Imports:	bigrquery (≥ 1.2.0), config, DBI, dbplyr, dplyr (≥ 1.0.0), DT, gargle, glue, golem, httr, jsonlite, magrittr, purrr, redcapAPI, REDCapR, rlang (≥ 0.4.7), RPostgres, RSQLite, shiny (≥ 1.5.0), shinycssloaders (≥ 1.0.0), shinydashboard, shinydashboardPlus (≥ 2.0.0), shinyjs, shinyWidgets (≥ 0.6.0), snakecase, stringr, tibble, tidyr (≥ 1.1.0)
Suggests:	fs, gt, here, htmltools, knitr, pkgload, processx, readr, rmarkdown, rstudioapi, spelling, testthat (≥ 2.1.0), usethis
VignetteBuilder:	knitr
Encoding:	UTF-8
Language:	en-US
LazyData:	true
RoxygenNote:	7.2.3
NeedsCompilation:	no
Packaged:	2023-09-01 14:12:26 UTC; MayerDav
Author:	Laura Wiley [aut], Luke Rasmussen [aut], David Mayer [cre, aut], The Wiley Lab [cph, fnd]
Maintainer:	David Mayer <david.mayer@cuanschutz.edu>
Repository:	CRAN
Date/Publication:	2023-09-01 15:50:11 UTC

ReviewR: A Light-Weight, Portable Tool for Reviewing Individual Patient Records

Description

A portable Shiny tool to explore patient-level electronic health record data and perform chart review in a single integrated 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. In addition, chart review information is captured and stored securely via the Shiny interface in a 'REDCap' (Research Electronic Data Capture) project using the 'REDCap' API. See the 'ReviewR' website for additional information, documentation, and examples.

Author(s)

Maintainer: David Mayer david.mayer@cuanschutz.edu (ORCID)

Authors:

• Laura Wiley laura.wiley@cuanschutz.edu (ORCID)

• Luke Rasmussen luke.rasmussen@northwestern.edu (ORCID)

Other contributors:

• The Wiley Lab [copyright holder, funder]

See Also

Useful links:

• https://reviewr.thewileylab.org/

• https://github.com/thewileylab/ReviewR/

• Report bugs at https://github.com/thewileylab/ReviewR/issues

ReviewR Chart Review Tab

Description

This function contains all of the elements that control the layout of the Chart Review Tab.

Usage

chart_review()

Value

shiny::renderUI Output containing the Chart Review Tab

See Also

Other layout: homepage(), patient_search(), setup()

Database Table Function: All Patients Table Template

Description

A character vector containing a function template for creating the 'All Patients' table as displayed on the "Patient Search" Tab

Usage

db_function_all_patients_table_template

Format

A character vector with 22 elements

See Also

Other Development Templates: db_function_subject_table_template, db_module_template

Database Table Function: Subject Table Template

Description

A character vector containing a function template for creating the 'Subject Filtered' tables as displayed on the "Chart Review" Tab

Usage

db_function_subject_table_template

Format

A character vector with 15 elements

See Also

Other Development Templates: db_function_all_patients_table_template, db_module_template

Database Module Template

Description

A character vector containing a database module template

Usage

db_module_template

Format

A character vector with 52 elements

See Also

Other Development Templates: db_function_all_patients_table_template, db_function_subject_table_template

Develop Data Model Table Functions

Description

This function will assist in adding support for a new data model to ReviewR. A schema file, supplied as a CSV, will be added to the package namespace such that upon connection to a database containing the new data model, ReviewR can identify and display it through the database detection module.

Users will be prompted to identify which table in the new data model contains a list of all patients. Additionally, users will be asked to select which field uniquely identifies each patient. This field must be present across all tables in the new data model for best results.

Once selections are captured, a database_tables.R file will be populated and opened for editing in RStudio. Basic table skeletons are created based on the provided schema and user selections.

Note: If the identifier field is not present across all tables, care must be taken to adjust the database_tables.R file to appropriately represent the new data model structure.

Usage

dev_add_data_model(csv)

Arguments

Value

A .R file populated with basic database table functions

See Also

Other Development Functions: dev_add_database_module()

Develop A Database Module

Description

This function will create a database module skeleton with required elements already populated, based on user inputs. Common database module packages are imported automatically, but developers should add imports to the roxygen skeleton as necessary to both the UI and server functions to collect user info and create a DBI connection object, respectively.

Usage

dev_add_database_module(mod_name = NULL, display_name = NULL)

Arguments

Value

A .R file populated with a database module skeleton

See Also

Other Development Functions: dev_add_data_model()

DT to Viewer

Description

Save a temporary DT::datatable as a self contained HTML file to display in the RStudio Viewer Pane. Used to provided users with choices when prompted for action by a dev function.

Usage

dt_2_viewer(.data, file = NULL)

Arguments

Value

This function returns a temporary HTML file displayed in the RStudio Viewer Pane

OMOP Get Concept

Description

This function assists with transforming OMOP concept_ids to interpretable strings by retrieving the requested concepts from the appropriate OMOP concept table.

Usage

get_concept(
  table_map,
  db_connection,
  concept_table,
  concept_id,
  concept_name,
  table,
  joinable_id,
  table_concept_id,
  col_name,
  subject_id_field = NULL,
  selected_subject = NULL
)

Arguments

Value

The desired OMOP concept based on the user data model for all subjects

ReviewR Homepage Tab

Description

This function contains all of the elements that control the layout of the Homepage Tab.

Usage

homepage()

Value

shiny::renderUI Output containing the Homepage Tab

See Also

Other layout: chart_review(), patient_search(), setup()

Installed App

Description

Invisibly returns an OAuth app.

Usage

installed_app()

Value

An Invisible OAuth consumer application, produced by httr::oauth_app()

MIMIC-III Tables

Description

A collection of functions to create prearranged views of MIMIC-III patient data when supplied with database connection information and a mapping of the connected database.

Usage

mimic3_table_all_patients(table_map, db_connection)

mimic3_table_admissions(table_map, db_connection, subject_id)

mimic3_table_callout(table_map, db_connection, subject_id)

mimic3_table_chart_events(table_map, db_connection, subject_id)

mimic3_table_cpt_events(table_map, db_connection, subject_id)

mimic3_table_diagnoses_icd(table_map, db_connection, subject_id)

mimic3_table_drg_codes(table_map, db_connection, subject_id)

mimic3_table_icu_stays(table_map, db_connection, subject_id)

mimic3_table_lab_events(table_map, db_connection, subject_id)

mimic3_table_microbiology_events(table_map, db_connection, subject_id)

mimic3_table_note_events(table_map, db_connection, subject_id)

mimic3_table_prescriptions(table_map, db_connection, subject_id)

mimic3_table_procedure_events(table_map, db_connection, subject_id)

mimic3_table_procedures_icd(table_map, db_connection, subject_id)

mimic3_table_services(table_map, db_connection, subject_id)

mimic3_table_transfers(table_map, db_connection, subject_id)

Arguments

Value

A dplyr::tibble containing pre-coordinated patient information from the connected database.

Abstraction Module Selector

Description

This module allows the user to select an available ReviewR abstraction module from a dropdown list. It dynamically returns the abstraction setup and instrument user interfaces as well as collected chart abstraction information from the selected module.

This module consists of the following components:

Module UI functions

• abstraction_setup_ui: A tagList with a dropdown selector containing available abstraction modules.

• abstraction_instrument_ui: A uiOutput containing the data collection instrument UI from the selected chart abstraction module.

Module Server function

• abstraction_setup_server: Processes user selection and dynamically returns uiOutputs for the selected abstraction module's setup and data collection instrument user interfaces. Any returns from the configured abstraction module are captured and returned.

Usage

abstraction_setup_ui(id)

abstraction_instrument_ui(id)

abstraction_setup_server(id, subject_id)

Arguments

Value

abstraction_setup_ui:

abstraction_instrument_ui:

abstraction_setup_server:

Google BigQuery Database Module

Description

This module is designed to guide a user through the process of authenticating with Google BigQuery. It is responsible for retrieving:

• An OAuth 2.0 authorization token

• A list of GCP projects that are available to the authenticated user

• A list of BigQuery datasets contained within available projects

The user is visually guided through the authentication process. Once authenticated, the user is presented with project/dataset selections and once configured a DBI::dbConnect() object is returned.

This module consists of the following components:

Module UI function

• bigquery_setup_ui: A uiOutput responsible for guiding a user through the Google OAuth 2.0 authorization flow and graphically selecting a Google Big Query project/dataset.

Module Server function

• bigquery_setup_server: The logic that controls the graphical user interface, including redirecting to Google, receiving an authorization code, requesting an authorization token, and authenticating the application. Ultimately responsible for returning public Google user information and a DBI::dbconnect() object used to connect to the configured BigQuery database.

Usage

bigquery_setup_ui(id)

bigquery_setup_server(id, secrets_json = NULL)

Arguments

Value

bigquery_setup_ui:

bigquery_setup_server:

Data Model Detection Module

Description

This module will interrogate a user connected database, comparing it with known common data models to determine the both the data model and version (when applicable) of the user's database.

It informs the rest of the application how to interpret and display the data stored in the connected database, when possible. If an unsupported data model is detected, the user is informed and given the opportunity to connect to a different database.

This module consists of the following components:

Module UI functions

These functions return a Shiny tagList containing various UI elements of the ReviewR application. UI components are calculated by the data_model_detection_server function of this module.

• data_model_detection_ui: A server defined uiOutput describing the detected data model and version.

• patient_chart_ui: The "Patient Chart," with the appropriate display elements based on the detected data model. Appears on the "Chart Review" tab of ReviewR.

Module Server function

The server function of this module is responsible for calculating the display elements included in the UI functions of this module as well as returning a reactiveValues object containing various other objects used by other modules.

• data_model_detection_server: Contains the data model detection logic and calculates UI elements. Returns a reactiveValues object containing variables used in other modules.

Usage

data_model_detection_ui(id)

patient_chart_ui(id)

data_model_detection_server(id, database_vars, navigation_vars, parent_session)

Arguments

Value

data_model_detection_ui:

patient_chart_ui:

data_model_detection_server:

Database Module Selector

Description

This module allows the user to select an available ReviewR database module from a dropdown list. It dynamically returns the database setup UI and user configured database connection information from the selected module.

See vignette("customize_support_new_rdbms", package = "ReviewR") for more information on database modules and how to add support for additional databases.

This module consists of the following components:

Module UI function

• database_setup_ui: A tagList with a dropdown selector containing available database modules.

Module Server function

• database_setup_server: Processes user selection and dynamically returns a uiOutput for the selected database module's setup UI. Any returns from the configured database connection module are captured and returned.

Usage

database_setup_ui(id)

database_setup_server(id)

Arguments

Value

database_setup_ui:

database_setup_server:

Demo SQLite Database Module

Description

This module will create an in memory SQLite database with demo data from the CMS 2008-2010 Data Entrepreneurs’ Synthetic Public Use File (DE-SynPUF) from OHDSI. It will allow you to preview the functionality of ReviewR if you do not have access to a database of patient information.

This module consists of the following components:

Module UI function

• demo_sqlite_setup_ui: A uiOutput that allows users to connect to the demonstration database.

Module Server function

• demo_sqlite_setup_server: The logic that creates the demonstration SQLite database and returns a DBI::dbConnect() object used to connect to the demo database.

Usage

demo_sqlite_setup_ui(id)

demo_sqlite_setup_server(id)

Arguments

Value

demo_sqlite_setup_ui:

demo_sqlite_setup_server:

Chart Review Interface Module

Description

This module determines if "View" or "Review" interface is needed based on presence or absence of a configured abstraction module. When an abstraction module is configured on the "Setup" tab of ReviewR, a column will be created to the right of the patient chart for the abstraction data collection instrument. Otherwise, the patient chart will take up the full view.

This module consists of the following components:

Module UI function

• chartreview_ui: A uiOutput containing the View or Review interface

Module Server function

• chartreview_server: The logic that controls the layout of the "Chart Review" tab in ReviewR. "View" if no abstraction module is configured. "Review" if abstraction module configured.

Usage

chartreview_ui(id)

chartreview_server(id, database_vars, abstract_vars)

Arguments

Value

chartreview_ui:

chartreview_server:

Patient Navigation Module

Description

This module will render the "all patients" dataTable (DT) located on the 'Patient Search' tab of ReviewR and will display demographic information about subjects in the connected database. The subject id of the selections made on this tab are extracted and passed to other ReviewR modules. As selections are made using the DT or the navigation buttons on the 'Chart Review' tab, the selected patient in the DT is kept in sync by this module.

Additionally, demographic and (optionally) abstraction status information about the selected patient are extracted and placed into a header on the 'Chart Review' tab.

This module consists of the following components:

Module UI functions

• navigation_message: A uiOutput to display a placeholder message when no database is connected.

• all_patient_search_dt: A uiOutput containing the "all patients" dataTable with patient demographic information from the connected database.

• chart_review_subject_info: A uiOutput containing the selected subject's demographic information to display on the 'Chart Review' tab.

• chart_review_navigation: A uiOutput containing the "Jump to Subject ID' dropdown and previous and next buttons used to navigate through patient data on the 'Chart Review' tab.

Module Server function

• navigation_server: Provides all of the logic associated with displaying patient demographic information, selecting a patient to review, and navigating through the connected patient database. Returns user selected patient information for use by other modules.

Keyboard Shortcuts

This module also provides keyboard shortcuts to assist with navigating through patient data. The "meta" key refers to "ctrl" on Windows and "Cmd" on Mac.

• Next Patient: “alt + meta + >”

• Prev Patient: “alt + meta + <”

Usage

navigation_message(id)

all_patient_search_dt(id)

chart_review_subject_info(id)

chart_review_navigation(id)

navigation_server(
  id,
  database_vars,
  data_model_vars,
  abstract_vars,
  parent_session
)

Arguments

Value

navigation_message:

all_patient_search_dt:

chart_review_subject_info:

chart_review_navigation:

navigation_server:

PostgreSQL Database Module

Description

This module is designed to guide a user through the process of authenticating with a PostgreSQL database. The user is visually prompted for typical PostgreSQL connection parameters. User entered information is verified and once authenticated, a DBI::dbConnect() object is returned.

This module consists of the following components:

Module UI function

• postgresql_setup_ui: A uiOutput that allows users to connect to provide connection parameters required to connect to a PostgreSQL database.

Module Server function

• postgresql_setup_server: The logic that controls the graphical user interface, validates user inputs, and returns a DBI::dbconnect() object used to connect to the desired PostgreSQL database.

Usage

postgresql_setup_ui(id)

postgresql_setup_server(id)

Arguments

Value

postgresql_setup_ui:

postgresql_setup_server:

REDCap Abstraction Module

Description

This module allows users to interact with REDCap Projects from within a Shiny application. REDCap instruments are translated into native Shiny controls/widgets and allow for the capture of abstracted information from within the R Shiny environment. Additionally, error prone fields such as MRN and reviewer information are populated automatically, based on user configured information, thus reducing the potential for error in abstracted information.

This module consists of the following components:

Module UI functions

• redcap_setup_ui: The REDCap setup/configuration UI

• redcap_instrument_ui: A shiny representation of a REDCap Instrument

Module Server function

• redcap_server: The logic

Keyboard Shortcuts

This module also provides a keyboard shortcut to assist with saving abstracted patient data. The "meta" key refers to "ctrl" on Windows and "Cmd" on Mac.

• Save current instrument data: “alt + meta + s”

Usage

redcap_setup_ui(id)

redcap_instrument_ui(id)

redcap_server(id, subject_id)

Arguments

Value

redcap_setup_ui:

redcap_instrument_ui:

redcap_server:

OMOP Tables

Description

Collection of functions to create prearranged views of OMOP patient data when supplied with database connection information and a mapping of the connected database.

Usage

omop_table_all_patients(table_map, db_connection)

omop_table_condition_era(table_map, db_connection, subject_id)

omop_table_condition_occurrence(table_map, db_connection, subject_id)

omop_table_death(table_map, db_connection, subject_id)

omop_table_device_exposure(table_map, db_connection, subject_id)

omop_table_dose_era(table_map, db_connection, subject_id)

omop_table_drug_era(table_map, db_connection, subject_id)

omop_table_drug_exposure(table_map, db_connection, subject_id)

omop_table_measurement(table_map, db_connection, subject_id)

omop_table_note(table_map, db_connection, subject_id)

omop_table_observation(table_map, db_connection, subject_id)

omop_table_observation_period(table_map, db_connection, subject_id)

omop_table_payer_plan_period(table_map, db_connection, subject_id)

omop_table_procedure_occurrence(table_map, db_connection, subject_id)

omop_table_specimen(table_map, db_connection, subject_id)

omop_table_visit_occurrence(table_map, db_connection, subject_id)

Arguments

Value

A dplyr::tibble containing pre-coordinated patient information from the connected database.

ReviewR Patient Search Tab

Description

This function contains all of the elements that control the layout of the Patient Search Tab.

Usage

patient_search()

Value

shiny::renderUI Output containing the Patient Search Tab

See Also

Other layout: chart_review(), homepage(), setup()

REDCap Connection

Description

Overview

A 'safe' wrapper for redcapAPI::redcapConnection(). Will return diagnostic error codes in case incorrect URL or token are provided instead of failing outright.

REDCap API Security

It is good practice to ensure that SSL certs are validated when utilizing the REDCap API. To ensure this happens, set the CURLOPT_SSL_VERIFYPEER' option to TRUE to avoid potential man in the middle attacks.

The redcapAPI package utilizes the httr package to perform operations using the REDCap API. Configuration options can be passed directly to httr via the config option in the redcapAPI::redcapConnection function. Here, we set 'ssl_verifypeer = 1L' to ensure cert checking is enabled.

• https://search.r-project.org/CRAN/refmans/redcapAPI/html/redcapConnection.html

• https://httr.r-lib.org/reference/httr_options.html

Usage

redcap_connection(url, token)

Arguments

Value

A redcapAPI connection object if the URL and API token are correct ( See: redcapAPI::redcapConnection ). Else, return diagnostic error.

REDCap Survey Complete

Description

A dataset containing valid REDCap "Survey Complete" Values.

Usage

redcap_survey_complete

Format

A data frame with 2 rows and 2 variables:

redcap_survey_complete_names

The human readable "Survey Complete" Responses

redcap_survey_complete_values

REDCap API values for "Survey Complete" Responses

...

REDCap Widget Map

Description

A dataset that maps REDCap question types and common validations to native shiny widgets through custom functions.

Usage

redcap_widget_map

Format

A data frame with 9 rows and 3 variables:

redcap_field_type

A REDCap Question Type

redcap_field_validation

Custom REDCap Question Type Validation

shinyREDCap_widget_function

shinyREDCap function to use when mapping to native Shiny widget

...

Render REDCap Instrument

Description

This function will select the appropriate shiny widget translation function based on the provided parameters. Used to loop over REDCap project information to create an entire data collection instrument which may consist of multiple questions/question types.

Usage

render_redcap_instrument(
  shinyREDCap_type,
  id,
  field_label,
  required,
  choices,
  current_subject_data = NULL,
  ...
)

Arguments

Value

A shiny input widget for the UI

ReviewR DataTable

Description

This is a wrapper function around DT::datatable which applies common extensions, options and default values used throughout the ReviewR application.

Usage

reviewr_datatable(.data, dom = "ftip", column_filter = "top", search_term = "")

Arguments

Value

A DT::datatable

Run Application

Description

Start the ReviewR Application in a browser on port 1410.

 __________            .__              __________ 
 \______   \ _______  _|__| ______  _  _\______   \
  |       _// __ \  \/ /  |/ __ \ \/ \/ /|       _/
  |    |   \  ___/\   /|  \  ___/\     / |    |   \
  |____|_  /\___  >\_/ |__|\___  >\/\_/  |____|_  /
         \/     \/             \/               \/ 
                                      by WileyLab

Making manual record review fun since 2019!

authors:  Laura Wiley, Luke Rasmussen, David Mayer

Usage

run_app(...)

Arguments

Value

No return value, called to start the ReviewR Shiny Application!

REDCap Safe Export Records

Description

A safe wrapper around redcapAPI::exportRecords that does not fail when records are requested from an empty REDCap project. In the event of an empty project, field names are used to create an empty data structure.

Usage

safe_exportRecords(rc_con, rc_field_names)

Arguments

Value

A data frame containing existing REDCap records, or an empty data frame with the structure of what the records would look like.

Safe File Exists

Description

A "safe" wrapper around base::file.exists that returns a FALSE if no file path is supplied as an argument, instead of an error.

Usage

safe_file.exists(...)

Arguments

Value

Logical, true/false if file path is provided or NULL if not supplied with any input.

ReviewR Setup Tab

Description

This function contains all of the elements that control the layout of the Setup Tab.

Usage

setup()

Value

shiny::renderUI Output containing the Setup Tab

See Also

Other layout: chart_review(), homepage(), patient_search()

Shiny Widget Translation

Description

A collection of functions to map REDCap question types as exported by the REDCap API to native Shiny widgets.

Usage

shinyREDCap_textInput(id, field_label, value = NULL, placeholder = NULL, ...)

shinyREDCap_dateInput(id, field_label, value = NULL, ...)

shinyREDCap_dropdown(id, field_label, required, choices, value = NULL, ...)

shinyREDCap_truefalse(id, field_label, required, value = NULL, ...)

shinyREDCap_yesno(id, field_label, required, value = NULL, ...)

shinyREDCap_radio(id, field_label, required, choices, value = NULL, ...)

shinyREDCap_checkbox(id, field_label, choices, value = NULL, ...)

shinyREDCap_notes(id, field_label, value = NULL, ...)

shinyREDCap_integer(id, field_label, value = NULL, ...)

Arguments

Value

A shiny input widget for the UI

Supported Data Model Schemas

Description

A dataset containing data model information along with the corresponding version and nested schema information.

Usage

supported_data_models

Format

A data frame with 12 rows and 4 variables:

data_model

Data model name

model_version

Version of the data model

data

Nested database schemas, including included table and field mappings

file_path

Where schema was imported from

...

Source

https://github.com/OHDSI/CommonDataModel/

https://github.com/MIT-LCP/mimic-code

synPUF

Description

Overview

This dataset contains a 10 person subset of the CMS 2008-2010 Data Entrepreneurs’ Synthetic Public Use File (DE-SynPUF) from OHDSI.

Details

• Information on the SynPUF data source is available here

• CDM 5.2.2 DDL for the OHDSI supported DBMSs is available here

• Notes Obtained from MTSamples.com

Usage

synPUF

Format

A data frame with 23 rows and 2 variables:

table_name

character: The table name in OMOP v5.2.2

table_data

list: The table data, in OMOP v5.2.2

...

Source

• https://github.com/thewileylab/synPUF/releases/tag/0.0.1.10

• https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/SynPUFs/DE_Syn_PUF

• https://github.com/OHDSI/CommonDataModel/blob/v5.2.2/PostgreSQL/OMOP%20CDM%20ddl%20-%20PostgreSQL.sql

• https://www.mtsamples.com/

user_field

Description

user_field

Usage

user_field(table_map, desired_cdm_table, desired_cdm_field)

Arguments

Value

A string containing the user database field pertaining to the standard data model field

user_table

Description

user_table

Usage

user_table(table_map, db_con, desired_cdm_table)

Arguments

Value

A SQL data source dplyr::tbl, ie. tbl(db_con, user_table), that connects to the user table that corresponds to the standard data model table.