`, etc.) that has more than one element. Defaults to 1 (for ``).
- getTopLevel: function($scope) {
- for (var i = 1; i <= 6; i++) {
- var $headings = this.findOrFilter($scope, 'h' + i);
- if ($headings.length > 1) {
- return i;
- }
- }
-
- return 1;
- },
-
- // returns the elements for the top level, and the next below it
- getHeadings: function($scope, topLevel) {
- var topSelector = 'h' + topLevel;
-
- var secondaryLevel = topLevel + 1;
- var secondarySelector = 'h' + secondaryLevel;
-
- return this.findOrFilter($scope, topSelector + ',' + secondarySelector);
- },
-
- getNavLevel: function(el) {
- return parseInt(el.tagName.charAt(1), 10);
- },
-
- populateNav: function($topContext, topLevel, $headings) {
- var $context = $topContext;
- var $prevNav;
-
- var helpers = this;
- $headings.each(function(i, el) {
- var $newNav = helpers.generateNavItem(el);
- var navLevel = helpers.getNavLevel(el);
-
- // determine the proper $context
- if (navLevel === topLevel) {
- // use top level
- $context = $topContext;
- } else if ($prevNav && $context === $topContext) {
- // create a new level of the tree and switch to it
- $context = helpers.createChildNavList($prevNav);
- } // else use the current $context
-
- $context.append($newNav);
-
- $prevNav = $newNav;
- });
- },
-
- parseOps: function(arg) {
- var opts;
- if (arg.jquery) {
- opts = {
- $nav: arg
- };
- } else {
- opts = arg;
- }
- opts.$scope = opts.$scope || $(document.body);
- return opts;
- }
- },
-
- // accepts a jQuery object, or an options object
- init: function(opts) {
- opts = this.helpers.parseOps(opts);
-
- // ensure that the data attribute is in place for styling
- opts.$nav.attr('data-toggle', 'toc');
-
- var $topContext = this.helpers.createChildNavList(opts.$nav);
- var topLevel = this.helpers.getTopLevel(opts.$scope);
- var $headings = this.helpers.getHeadings(opts.$scope, topLevel);
- this.helpers.populateNav($topContext, topLevel, $headings);
- }
- };
-
- $(function() {
- $('nav[data-toggle="toc"]').each(function(i, el) {
- var $nav = $(el);
- Toc.init($nav);
- });
- });
-})();
diff --git a/docs/_site/docsearch.css b/docs/_site/docsearch.css
deleted file mode 100644
index e5f1fe1d..00000000
--- a/docs/_site/docsearch.css
+++ /dev/null
@@ -1,148 +0,0 @@
-/* Docsearch -------------------------------------------------------------- */
-/*
- Source: https://github.com/algolia/docsearch/
- License: MIT
-*/
-
-.algolia-autocomplete {
- display: block;
- -webkit-box-flex: 1;
- -ms-flex: 1;
- flex: 1
-}
-
-.algolia-autocomplete .ds-dropdown-menu {
- width: 100%;
- min-width: none;
- max-width: none;
- padding: .75rem 0;
- background-color: #fff;
- background-clip: padding-box;
- border: 1px solid rgba(0, 0, 0, .1);
- box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
-}
-
-@media (min-width:768px) {
- .algolia-autocomplete .ds-dropdown-menu {
- width: 175%
- }
-}
-
-.algolia-autocomplete .ds-dropdown-menu::before {
- display: none
-}
-
-.algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
- padding: 0;
- background-color: rgb(255,255,255);
- border: 0;
- max-height: 80vh;
-}
-
-.algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
- margin-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion {
- padding: 0;
- overflow: visible
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--category-header {
- padding: .125rem 1rem;
- margin-top: 0;
- font-size: 1.3em;
- font-weight: 500;
- color: #00008B;
- border-bottom: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
- float: none;
- padding-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
- float: none;
- width: auto;
- padding: 0;
- text-align: left
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content {
- float: none;
- width: auto;
- padding: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content::before {
- display: none
-}
-
-.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
- padding-top: .75rem;
- margin-top: .75rem;
- border-top: 1px solid rgba(0, 0, 0, .1)
-}
-
-.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
- display: block;
- padding: .1rem 1rem;
- margin-bottom: 0.1;
- font-size: 1.0em;
- font-weight: 400
- /* display: none */
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--title {
- display: block;
- padding: .25rem 1rem;
- margin-bottom: 0;
- font-size: 0.9em;
- font-weight: 400
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--text {
- padding: 0 1rem .5rem;
- margin-top: -.25rem;
- font-size: 0.8em;
- font-weight: 400;
- line-height: 1.25
-}
-
-.algolia-autocomplete .algolia-docsearch-footer {
- width: 110px;
- height: 20px;
- z-index: 3;
- margin-top: 10.66667px;
- float: right;
- font-size: 0;
- line-height: 0;
-}
-
-.algolia-autocomplete .algolia-docsearch-footer--logo {
- background-image: url("data:image/svg+xml;utf8,");
- background-repeat: no-repeat;
- background-position: 50%;
- background-size: 100%;
- overflow: hidden;
- text-indent: -9000px;
- width: 100%;
- height: 100%;
- display: block;
- transform: translate(-8px);
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--highlight {
- color: #FF8C00;
- background: rgba(232, 189, 54, 0.1)
-}
-
-
-.algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight {
- box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5)
-}
-
-.algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content {
- background-color: rgba(192, 192, 192, .15)
-}
diff --git a/docs/_site/docsearch.js b/docs/_site/docsearch.js
deleted file mode 100644
index b35504cd..00000000
--- a/docs/_site/docsearch.js
+++ /dev/null
@@ -1,85 +0,0 @@
-$(function() {
-
- // register a handler to move the focus to the search bar
- // upon pressing shift + "/" (i.e. "?")
- $(document).on('keydown', function(e) {
- if (e.shiftKey && e.keyCode == 191) {
- e.preventDefault();
- $("#search-input").focus();
- }
- });
-
- $(document).ready(function() {
- // do keyword highlighting
- /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */
- var mark = function() {
-
- var referrer = document.URL ;
- var paramKey = "q" ;
-
- if (referrer.indexOf("?") !== -1) {
- var qs = referrer.substr(referrer.indexOf('?') + 1);
- var qs_noanchor = qs.split('#')[0];
- var qsa = qs_noanchor.split('&');
- var keyword = "";
-
- for (var i = 0; i < qsa.length; i++) {
- var currentParam = qsa[i].split('=');
-
- if (currentParam.length !== 2) {
- continue;
- }
-
- if (currentParam[0] == paramKey) {
- keyword = decodeURIComponent(currentParam[1].replace(/\+/g, "%20"));
- }
- }
-
- if (keyword !== "") {
- $(".contents").unmark({
- done: function() {
- $(".contents").mark(keyword);
- }
- });
- }
- }
- };
-
- mark();
- });
-});
-
-/* Search term highlighting ------------------------------*/
-
-function matchedWords(hit) {
- var words = [];
-
- var hierarchy = hit._highlightResult.hierarchy;
- // loop to fetch from lvl0, lvl1, etc.
- for (var idx in hierarchy) {
- words = words.concat(hierarchy[idx].matchedWords);
- }
-
- var content = hit._highlightResult.content;
- if (content) {
- words = words.concat(content.matchedWords);
- }
-
- // return unique words
- var words_uniq = [...new Set(words)];
- return words_uniq;
-}
-
-function updateHitURL(hit) {
-
- var words = matchedWords(hit);
- var url = "";
-
- if (hit.anchor) {
- url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor;
- } else {
- url = hit.url + '?q=' + escape(words.join(" "));
- }
-
- return url;
-}
diff --git a/docs/_site/index.html b/docs/_site/index.html
deleted file mode 100644
index 80f06db2..00000000
--- a/docs/_site/index.html
+++ /dev/null
@@ -1,305 +0,0 @@
-
-
-
-
-
-
-
-Execute and View Data Quality Checks on OMOP CDM Database • DataQualityDashboard
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-The goal of the Data Quality Dashboard (DQD) project is to design and develop an open-source tool to expose and evaluate observational data quality.
-
-
-
-Introduction
-This package will run a series of data quality checks against an OMOP CDM instance (currently supports v5.3.1 and v5.2.2). It systematically runs the checks, evaluates the checks against some pre-specified threshold, and then communicates what was done in a transparent and easily understandable way.
-
-
-
-Overview
-The quality checks were organized according to the Kahn Framework1 which uses a system of categories and contexts that represent stratgies for assessing data quality. ##TODO for an introduction to the kahn framework please click [here] link.
-Using this framework, the Data Quality Dashboard takes a systematic-based approach to running data quality checks. Instead of writing thousands of individual checks, we use “data quality check types”. These “check types” are more general, parameterized data quality checks into which OMOP tables, fields, and concepts can be substituted to represent a singular data quality idea. For example, one check type might be written as
-
-The number and percent of records with a value in the cdmFieldName field of the cdmTableName table less than plausibleValueLow.
-
-This would be considered an atemporal plausibility verification check because we are looking for implausibly low values in some field based on internal knowledge. We can use this check type to substitute in values for cdmFieldName, cdmTableName, and plausibleValueLow to create a unique data quality check. If we apply it to PERSON.YEAR_OF_BIRTH here is how that might look:
-
-The number and percent of records with a value in the year_of_birth field of the PERSON table less than 1850.
-
-And, since it is parameterized, we can similarly apply it to DRUG_EXPOSURE.days_supply:
-
-The number and percent of records with a value in the days_supply field of the DRUG_EXPOSURE table less than 0.
-
-Version 1 of the tool includes 20 different check types organized into Kahn contexts and categories. Additionally, each data quality check type is considered either a table check, field check, or concept-level check. Table-level checks are those evaluating the table at a high-level without reference to individual fields, or those that span multiple event tables. These include checks making sure required tables are present or that at least some of the people in the PERSON table have records in the event tables. Field-level checks are those related to specific fields in a table. The majority of the check types in version 1 are field-level checks. These include checks evaluating primary key relationship and those investigating if the concepts in a field conform to the specified domain. Concept-level checks are related to individual concepts. These include checks looking for gender-specific concepts in persons of the wrong gender and plausible values for measurement-unit pairs. ##TODO The below table lists all check types, the check level (table, field, concept), a description of the check, and Kahn category and context it fits into. Remove table, click here for more information on the checks included
-After systematically applying the 20 check types to an OMOP CDM version approximately 3,351 individual data quality checks are resolved, run against the database, and evaluated based on a pre-specified threshold ##TODO [more about thresholds here]. The R package then creates a json object that is read into an RShiny application to view the results.
-
-
-
-
-Features
-
-- Utilizes configurable data check thresholds
-- Analyzes data in the OMOP Common Data Model format for all data checks
-- Produces a set of data check results with supplemental investigation assets.
-
-
-
-
-
-System Requirements
-Requires R (version 3.2.2 or higher). Requires DatabaseConnector and SqlRender.
-
-
-
-R Installation
-install.packages("devtools")
-devtools::install_github("OHDSI/DataQualityDashboard")
-
-
-
-Executing Data Quality Checks
-
-# fill out the connection details -----------------------------------------------------------------------
-connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "",
- user = "",
- password = "",
- server = "",
- port = "",
- extraSettings = "")
-
-cdmDatabaseSchema <- "yourCdmSchema" # the fully qualified database schema name of the CDM
-resultsDatabaseSchema <- "yourResultsSchema" # the fully qualified database schema name of the results schema (that you can write to)
-cdmSourceName <- "Your CDM Source" # a human readable name for your CDM source
-
-# determine how many threads (concurrent SQL sessions) to use ----------------------------------------
-numThreads <- 1 # on Redshift, 3 seems to work well
-
-# specify if you want to execute the queries or inspect them ------------------------------------------
-sqlOnly <- FALSE # set to TRUE if you just want to get the SQL scripts and not actually run the queries
-
-# where should the logs go? -------------------------------------------------------------------------
-outputFolder <- "output"
-
-# logging type -------------------------------------------------------------------------------------
-verboseMode <- FALSE # set to TRUE if you want to see activity written to the console
-
-# write results to table? ------------------------------------------------------------------------------
-writeToTable <- TRUE # set to FALSE if you want to skip writing to a SQL table in the results schema
-
-# if writing to table and using Redshift, bulk loading can be initialized -------------------------------
-
-# Sys.setenv("AWS_ACCESS_KEY_ID" = "",
-# "AWS_SECRET_ACCESS_KEY" = "",
-# "AWS_DEFAULT_REGION" = "",
-# "AWS_BUCKET_NAME" = "",
-# "AWS_OBJECT_KEY" = "",
-# "AWS_SSE_TYPE" = "AES256",
-# "USE_MPP_BULK_LOAD" = TRUE)
-
-# which DQ check levels to run -------------------------------------------------------------------
-checkLevels <- c("TABLE", "FIELD", "CONCEPT")
-
-# which DQ checks to run? ------------------------------------
-
-checkNames <- c() # Names can be found in inst/csv/OMOP_CDM_v5.3.1_Check_Desciptions.csv
-
-# run the job --------------------------------------------------------------------------------------
-DataQualityDashboard::executeDqChecks(connectionDetails = connectionDetails,
- cdmDatabaseSchema = cdmDatabaseSchema,
- resultsDatabaseSchema = resultsDatabaseSchema,
- cdmSourceName = cdmSourceName,
- numThreads = numThreads,
- sqlOnly = sqlOnly,
- outputFolder = outputFolder,
- verboseMode = verboseMode,
- writeToTable = writeToTable,
- checkLevels = checkLevels,
- checkNames = checkNames)
-
-# inspect logs ----------------------------------------------------------------------------
-ParallelLogger::launchLogViewer(logFileName = file.path(outputFolder, cdmSourceName,
- sprintf("log_DqDashboard_%s.txt", cdmSourceName)))
-
-# (OPTIONAL) if you want to write the JSON file to the results table separately -----------------------------
-jsonFilePath <- ""
-DataQualityDashboard::writeJsonResultsToTable(connectionDetails = connectionDetails,
- resultsDatabaseSchema = resultsDatabaseSchema,
- jsonFilePath = jsonFilePath)
-
-
-
-Viewing Results
-Launching Dashboard as Shiny App
-DataQualityDashboard::viewDqDashboard(jsonPath = file.path(getwd(), outputFolder, cdmSourceName, sprintf("results_%s.json", cdmSourceName)))
-Launching on a web server
-If you have npm installed:
-
-- Install http-server:
-
-npm install -g http-server
-
-Rename the json file to results.json and place it in inst/shinyApps/www
Go to inst/shinyApps/www, then run:
-http-server
-A results JSON file for the Synthea synthetic dataset will be shown. You can view your results by replacing the results.json file with your file (with name results.json).
-
-
-
-View checks
-To see description of checks using R, execute the command bellow:
-View(read.csv(system.file("csv","OMOP_CDMv5.3.1_Check_Descriptions.csv",package="DataQualityDashboard"),as.is=T))
-
-
-
-Support
-
-- Developer questions/comments/feedback: OHDSI Forum
-
-- We use the GitHub issue tracker for all bugs/issues/enhancements
-
-
-
-
-
-Acknowledgements
-This project is supported in part through the National Science Foundation grant IIS 1251151.
-1 Kahn, M.G., et al., A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data. EGEMS (Wash DC), 2016. 4(1): p. 1244. ↩︎
-
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diff --git a/docs/_site/link.svg b/docs/_site/link.svg
deleted file mode 100644
index 88ad8276..00000000
--- a/docs/_site/link.svg
+++ /dev/null
@@ -1,12 +0,0 @@
-
-
-
diff --git a/docs/_site/pkgdown.css b/docs/_site/pkgdown.css
deleted file mode 100644
index c01e5923..00000000
--- a/docs/_site/pkgdown.css
+++ /dev/null
@@ -1,367 +0,0 @@
-/* Sticky footer */
-
-/**
- * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/
- * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
- *
- * .Site -> body > .container
- * .Site-content -> body > .container .row
- * .footer -> footer
- *
- * Key idea seems to be to ensure that .container and __all its parents__
- * have height set to 100%
- *
- */
-
-html, body {
- height: 100%;
-}
-
-body {
- position: relative;
-}
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-body > .container {
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- height: 100%;
- flex-direction: column;
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-body > .container .row {
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- padding: 35px 0 36px;
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- color: #666;
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-footer p {
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-footer div {
- flex: 1;
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-footer .pkgdown {
- text-align: right;
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-footer p {
- margin-bottom: 0;
-}
-
-img.icon {
- float: right;
-}
-
-img {
- max-width: 100%;
-}
-
-/* Fix bug in bootstrap (only seen in firefox) */
-summary {
- display: list-item;
-}
-
-/* Typographic tweaking ---------------------------------*/
-
-.contents .page-header {
- margin-top: calc(-60px + 1em);
-}
-
-dd {
- margin-left: 3em;
-}
-
-/* Section anchors ---------------------------------*/
-
-a.anchor {
- margin-left: -30px;
- display:inline-block;
- width: 30px;
- height: 30px;
- visibility: hidden;
-
- background-image: url(./link.svg);
- background-repeat: no-repeat;
- background-size: 20px 20px;
- background-position: center center;
-}
-
-.hasAnchor:hover a.anchor {
- visibility: visible;
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- .hasAnchor:hover a.anchor {
- visibility: hidden;
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-
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-
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-.dropdown-submenu {
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-.dropdown-submenu:hover>a:after {
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-
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-
-#pkgdown-sidebar {
- margin-top: 30px;
- position: -webkit-sticky;
- position: sticky;
- top: 70px;
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- font-size: 1.5em;
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- margin-bottom: 0.5em;
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-
-/* bootstrap-toc tweaks ------------------------------------------------------*/
-
-/* All levels of nav */
-
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- padding: 4px 20px 4px 6px;
- font-size: 1.5rem;
- font-weight: 400;
- color: inherit;
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-nav[data-toggle='toc'] .nav > li > a:hover,
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- padding-bottom: 10px;
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- padding-left: 16px;
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-
-.orcid {
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-.ref-index th {font-weight: normal;}
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-/* mark.js ----------------------------*/
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- border-bottom: 2px solid rgba(255, 153, 51, 0.3);
- padding: 1px;
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-.html-widget {
- margin-bottom: 10px;
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-/* fontawesome ------------------------ */
-
-.fab {
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diff --git a/docs/_site/pkgdown.js b/docs/_site/pkgdown.js
deleted file mode 100644
index 7e7048fa..00000000
--- a/docs/_site/pkgdown.js
+++ /dev/null
@@ -1,108 +0,0 @@
-/* http://gregfranko.com/blog/jquery-best-practices/ */
-(function($) {
- $(function() {
-
- $('.navbar-fixed-top').headroom();
-
- $('body').css('padding-top', $('.navbar').height() + 10);
- $(window).resize(function(){
- $('body').css('padding-top', $('.navbar').height() + 10);
- });
-
- $('[data-toggle="tooltip"]').tooltip();
-
- var cur_path = paths(location.pathname);
- var links = $("#navbar ul li a");
- var max_length = -1;
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- for (var i = 0; i < links.length; i++) {
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diff --git a/docs/_site/link.svg b/docs/_site/link.svg
deleted file mode 100644
index 88ad8276..00000000
--- a/docs/_site/link.svg
+++ /dev/null
@@ -1,12 +0,0 @@
-
-
-
diff --git a/docs/_site/pkgdown.css b/docs/_site/pkgdown.css
deleted file mode 100644
index c01e5923..00000000
--- a/docs/_site/pkgdown.css
+++ /dev/null
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-/* Sticky footer */
-
-/**
- * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/
- * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
- *
- * .Site -> body > .container
- * .Site-content -> body > .container .row
- * .footer -> footer
- *
- * Key idea seems to be to ensure that .container and __all its parents__
- * have height set to 100%
- *
- */
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-/* Fix bug in bootstrap (only seen in firefox) */
-summary {
- display: list-item;
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-.contents .page-header {
- margin-top: calc(-60px + 1em);
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-dd {
- margin-left: 3em;
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-/* Section anchors ---------------------------------*/
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-a.anchor {
- margin-left: -30px;
- display:inline-block;
- width: 30px;
- height: 30px;
- visibility: hidden;
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- background-image: url(./link.svg);
- background-repeat: no-repeat;
- background-size: 20px 20px;
- background-position: center center;
-}
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-.hasAnchor:hover a.anchor {
- visibility: visible;
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- .hasAnchor:hover a.anchor {
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- }
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-/* Fixes for fixed navbar --------------------------*/
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-.contents h1, .contents h2, .contents h3, .contents h4 {
- padding-top: 60px;
- margin-top: -40px;
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-/* Navbar submenu --------------------------*/
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-.dropdown-submenu {
- position: relative;
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-.dropdown-submenu>.dropdown-menu {
- top: 0;
- left: 100%;
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- border-style: solid;
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-.dropdown-submenu.pull-left {
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-.dropdown-submenu.pull-left>.dropdown-menu {
- left: -100%;
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-/* Sidebar --------------------------*/
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-#pkgdown-sidebar {
- margin-top: 30px;
- position: -webkit-sticky;
- position: sticky;
- top: 70px;
-}
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-#pkgdown-sidebar h2 {
- font-size: 1.5em;
- margin-top: 1em;
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-#pkgdown-sidebar h2:first-child {
- margin-top: 0;
-}
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-#pkgdown-sidebar .list-unstyled li {
- margin-bottom: 0.5em;
-}
-
-/* bootstrap-toc tweaks ------------------------------------------------------*/
-
-/* All levels of nav */
-
-nav[data-toggle='toc'] .nav > li > a {
- padding: 4px 20px 4px 6px;
- font-size: 1.5rem;
- font-weight: 400;
- color: inherit;
-}
-
-nav[data-toggle='toc'] .nav > li > a:hover,
-nav[data-toggle='toc'] .nav > li > a:focus {
- padding-left: 5px;
- color: inherit;
- border-left: 1px solid #878787;
-}
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-nav[data-toggle='toc'] .nav > .active > a,
-nav[data-toggle='toc'] .nav > .active:hover > a,
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- padding-left: 5px;
- font-size: 1.5rem;
- font-weight: 400;
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- border-left: 2px solid #878787;
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-/* Nav: second level (shown on .active) */
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-nav[data-toggle='toc'] .nav .nav {
- display: none; /* Hide by default, but at >768px, show it */
- padding-bottom: 10px;
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- padding-left: 16px;
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-.orcid {
- font-size: 16px;
- color: #A6CE39;
- /* margins are required by official ORCID trademark and display guidelines */
- margin-left:4px;
- margin-right:4px;
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- margin-bottom: 10px;
-}
-
-/* fontawesome ------------------------ */
-
-.fab {
- font-family: "Font Awesome 5 Brands" !important;
-}
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-/* source: https://stackoverflow.com/a/10781533 */
-@media print {
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- content: "";
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diff --git a/docs/_site/pkgdown.js b/docs/_site/pkgdown.js
deleted file mode 100644
index 7e7048fa..00000000
--- a/docs/_site/pkgdown.js
+++ /dev/null
@@ -1,108 +0,0 @@
-/* http://gregfranko.com/blog/jquery-best-practices/ */
-(function($) {
- $(function() {
-
- $('.navbar-fixed-top').headroom();
-
- $('body').css('padding-top', $('.navbar').height() + 10);
- $(window).resize(function(){
- $('body').css('padding-top', $('.navbar').height() + 10);
- });
-
- $('[data-toggle="tooltip"]').tooltip();
-
- var cur_path = paths(location.pathname);
- var links = $("#navbar ul li a");
- var max_length = -1;
- var pos = -1;
- for (var i = 0; i < links.length; i++) {
- if (links[i].getAttribute("href") === "#")
- continue;
- // Ignore external links
- if (links[i].host !== location.host)
- continue;
-
- var nav_path = paths(links[i].pathname);
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- var length = prefix_length(nav_path, cur_path);
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- max_length = length;
- pos = i;
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- // Add class to parent
-
-
-
-
-
-
-
-
-
-
-
-
-
-The goal of the Data Quality Dashboard (DQD) project is to design and develop an open-source tool to expose and evaluate observational data quality.
-
-
--Introduction
-This package will run a series of data quality checks against an OMOP CDM instance (currently supports v5.3.1 and v5.2.2). It systematically runs the checks, evaluates the checks against some pre-specified threshold, and then communicates what was done in a transparent and easily understandable way.
-
-
--Overview
-The quality checks were organized according to the Kahn Framework1 which uses a system of categories and contexts that represent stratgies for assessing data quality. ##TODO for an introduction to the kahn framework please click [here] link.
-Using this framework, the Data Quality Dashboard takes a systematic-based approach to running data quality checks. Instead of writing thousands of individual checks, we use “data quality check types”. These “check types” are more general, parameterized data quality checks into which OMOP tables, fields, and concepts can be substituted to represent a singular data quality idea. For example, one check type might be written as
---The number and percent of records with a value in the cdmFieldName field of the cdmTableName table less than plausibleValueLow.
-
This would be considered an atemporal plausibility verification check because we are looking for implausibly low values in some field based on internal knowledge. We can use this check type to substitute in values for cdmFieldName, cdmTableName, and plausibleValueLow to create a unique data quality check. If we apply it to PERSON.YEAR_OF_BIRTH here is how that might look:
---The number and percent of records with a value in the year_of_birth field of the PERSON table less than 1850.
-
And, since it is parameterized, we can similarly apply it to DRUG_EXPOSURE.days_supply:
---The number and percent of records with a value in the days_supply field of the DRUG_EXPOSURE table less than 0.
-
Version 1 of the tool includes 20 different check types organized into Kahn contexts and categories. Additionally, each data quality check type is considered either a table check, field check, or concept-level check. Table-level checks are those evaluating the table at a high-level without reference to individual fields, or those that span multiple event tables. These include checks making sure required tables are present or that at least some of the people in the PERSON table have records in the event tables. Field-level checks are those related to specific fields in a table. The majority of the check types in version 1 are field-level checks. These include checks evaluating primary key relationship and those investigating if the concepts in a field conform to the specified domain. Concept-level checks are related to individual concepts. These include checks looking for gender-specific concepts in persons of the wrong gender and plausible values for measurement-unit pairs. ##TODO The below table lists all check types, the check level (table, field, concept), a description of the check, and Kahn category and context it fits into. Remove table, click here for more information on the checks included
-After systematically applying the 20 check types to an OMOP CDM version approximately 3,351 individual data quality checks are resolved, run against the database, and evaluated based on a pre-specified threshold ##TODO [more about thresholds here]. The R package then creates a json object that is read into an RShiny application to view the results.
-
-
-
--Features
--
-
- Utilizes configurable data check thresholds -
- Analyzes data in the OMOP Common Data Model format for all data checks -
- Produces a set of data check results with supplemental investigation assets. -
-
--System Requirements
-Requires R (version 3.2.2 or higher). Requires DatabaseConnector and SqlRender.
-
-
-
--R Installation
-install.packages("devtools") -devtools::install_github("OHDSI/DataQualityDashboard")
-
-
--Executing Data Quality Checks
--# fill out the connection details ----------------------------------------------------------------------- -connectionDetails <- DatabaseConnector::createConnectionDetails(dbms = "", - user = "", - password = "", - server = "", - port = "", - extraSettings = "") - -cdmDatabaseSchema <- "yourCdmSchema" # the fully qualified database schema name of the CDM -resultsDatabaseSchema <- "yourResultsSchema" # the fully qualified database schema name of the results schema (that you can write to) -cdmSourceName <- "Your CDM Source" # a human readable name for your CDM source - -# determine how many threads (concurrent SQL sessions) to use ---------------------------------------- -numThreads <- 1 # on Redshift, 3 seems to work well - -# specify if you want to execute the queries or inspect them ------------------------------------------ -sqlOnly <- FALSE # set to TRUE if you just want to get the SQL scripts and not actually run the queries - -# where should the logs go? ------------------------------------------------------------------------- -outputFolder <- "output" - -# logging type ------------------------------------------------------------------------------------- -verboseMode <- FALSE # set to TRUE if you want to see activity written to the console - -# write results to table? ------------------------------------------------------------------------------ -writeToTable <- TRUE # set to FALSE if you want to skip writing to a SQL table in the results schema - -# if writing to table and using Redshift, bulk loading can be initialized ------------------------------- - -# Sys.setenv("AWS_ACCESS_KEY_ID" = "", -# "AWS_SECRET_ACCESS_KEY" = "", -# "AWS_DEFAULT_REGION" = "", -# "AWS_BUCKET_NAME" = "", -# "AWS_OBJECT_KEY" = "", -# "AWS_SSE_TYPE" = "AES256", -# "USE_MPP_BULK_LOAD" = TRUE) - -# which DQ check levels to run ------------------------------------------------------------------- -checkLevels <- c("TABLE", "FIELD", "CONCEPT") - -# which DQ checks to run? ------------------------------------ - -checkNames <- c() # Names can be found in inst/csv/OMOP_CDM_v5.3.1_Check_Desciptions.csv - -# run the job -------------------------------------------------------------------------------------- -DataQualityDashboard::executeDqChecks(connectionDetails = connectionDetails, - cdmDatabaseSchema = cdmDatabaseSchema, - resultsDatabaseSchema = resultsDatabaseSchema, - cdmSourceName = cdmSourceName, - numThreads = numThreads, - sqlOnly = sqlOnly, - outputFolder = outputFolder, - verboseMode = verboseMode, - writeToTable = writeToTable, - checkLevels = checkLevels, - checkNames = checkNames) - -# inspect logs ---------------------------------------------------------------------------- -ParallelLogger::launchLogViewer(logFileName = file.path(outputFolder, cdmSourceName, - sprintf("log_DqDashboard_%s.txt", cdmSourceName))) - -# (OPTIONAL) if you want to write the JSON file to the results table separately ----------------------------- -jsonFilePath <- "" -DataQualityDashboard::writeJsonResultsToTable(connectionDetails = connectionDetails, - resultsDatabaseSchema = resultsDatabaseSchema, - jsonFilePath = jsonFilePath)
-
-
--Viewing Results
-Launching Dashboard as Shiny App
-DataQualityDashboard::viewDqDashboard(jsonPath = file.path(getwd(), outputFolder, cdmSourceName, sprintf("results_%s.json", cdmSourceName)))
Launching on a web server
-If you have npm installed:
--
-
- Install http-server: -
npm install -g http-server-
-
Rename the json file to results.json and place it in inst/shinyApps/www
-Go to inst/shinyApps/www, then run:
-
http-serverA results JSON file for the Synthea synthetic dataset will be shown. You can view your results by replacing the results.json file with your file (with name results.json).
-
-
--View checks
-To see description of checks using R, execute the command bellow:
-View(read.csv(system.file("csv","OMOP_CDMv5.3.1_Check_Descriptions.csv",package="DataQualityDashboard"),as.is=T))
-
-
--Support
--
-
- Developer questions/comments/feedback: OHDSI Forum - -
- We use the GitHub issue tracker for all bugs/issues/enhancements -
-
-
- -Acknowledgements
-This project is supported in part through the National Science Foundation grant IIS 1251151.
-1 Kahn, M.G., et al., A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data. EGEMS (Wash DC), 2016. 4(1): p. 1244. ↩︎
-
