2019-08-28 15:02:47 +00:00
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<!DOCTYPE html>
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2020-04-27 20:35:41 +00:00
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<html>
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2019-08-28 15:02:47 +00:00
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<head>
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<meta charset="utf-8" />
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<meta name="generator" content="pandoc" />
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2020-04-27 20:35:41 +00:00
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<meta http-equiv="X-UA-Compatible" content="IE=EDGE" />
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2019-08-28 15:02:47 +00:00
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<title>OMOP CDM Frequently Asked Questions</title>
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2023-02-08 20:04:22 +00:00
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<script src="site_libs/header-attrs-2.16/header-attrs.js"></script>
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2022-01-13 18:59:03 +00:00
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<script src="site_libs/jquery-3.6.0/jquery-3.6.0.min.js"></script>
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2019-08-28 15:02:47 +00:00
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<link href="site_libs/bootstrap-3.3.5/css/cosmo.min.css" rel="stylesheet" />
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<script src="site_libs/bootstrap-3.3.5/js/bootstrap.min.js"></script>
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<script src="site_libs/bootstrap-3.3.5/shim/html5shiv.min.js"></script>
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<script src="site_libs/bootstrap-3.3.5/shim/respond.min.js"></script>
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2022-01-13 18:59:03 +00:00
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<style>h1 {font-size: 34px;}
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h1.title {font-size: 38px;}
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h2 {font-size: 30px;}
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h3 {font-size: 24px;}
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h4 {font-size: 18px;}
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h5 {font-size: 16px;}
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h6 {font-size: 12px;}
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code {color: inherit; background-color: rgba(0, 0, 0, 0.04);}
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pre:not([class]) { background-color: white }</style>
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2022-04-22 19:12:19 +00:00
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<script src="site_libs/jqueryui-1.11.4/jquery-ui.min.js"></script>
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<link href="site_libs/tocify-1.9.1/jquery.tocify.css" rel="stylesheet" />
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<script src="site_libs/tocify-1.9.1/jquery.tocify.js"></script>
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2019-08-28 15:02:47 +00:00
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<script src="site_libs/navigation-1.1/tabsets.js"></script>
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<link href="site_libs/highlightjs-9.12.0/default.css" rel="stylesheet" />
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<script src="site_libs/highlightjs-9.12.0/highlight.js"></script>
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<link href="site_libs/font-awesome-5.1.0/css/all.css" rel="stylesheet" />
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<link href="site_libs/font-awesome-5.1.0/css/v4-shims.css" rel="stylesheet" />
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<link rel='shortcut icon' type='image/x-icon' href='favicon.ico' />
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2021-01-06 15:52:57 +00:00
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<style type="text/css">
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code{white-space: pre-wrap;}
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span.smallcaps{font-variant: small-caps;}
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span.underline{text-decoration: underline;}
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div.column{display: inline-block; vertical-align: top; width: 50%;}
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div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
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ul.task-list{list-style: none;}
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</style>
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2019-08-28 15:02:47 +00:00
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<style type="text/css">code{white-space: pre;}</style>
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<script type="text/javascript">
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if (window.hljs) {
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hljs.configure({languages: []});
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hljs.initHighlightingOnLoad();
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if (document.readyState && document.readyState === "complete") {
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window.setTimeout(function() { hljs.initHighlighting(); }, 0);
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}
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}
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</script>
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2021-01-06 15:52:57 +00:00
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2022-04-22 19:12:19 +00:00
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2019-08-28 15:02:47 +00:00
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<link rel="stylesheet" href="style.css" type="text/css" />
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<style type = "text/css">
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.main-container {
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max-width: 940px;
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margin-left: auto;
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margin-right: auto;
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}
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img {
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max-width:100%;
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}
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.tabbed-pane {
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padding-top: 12px;
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}
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.html-widget {
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margin-bottom: 20px;
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}
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button.code-folding-btn:focus {
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outline: none;
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}
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summary {
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display: list-item;
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}
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2022-04-22 19:12:19 +00:00
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details > summary > p:only-child {
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display: inline;
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}
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2022-01-13 18:59:03 +00:00
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pre code {
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padding: 0;
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}
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2019-08-28 15:02:47 +00:00
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</style>
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<style type="text/css">
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.dropdown-submenu {
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position: relative;
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}
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.dropdown-submenu>.dropdown-menu {
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top: 0;
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left: 100%;
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margin-top: -6px;
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margin-left: -1px;
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border-radius: 0 6px 6px 6px;
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}
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.dropdown-submenu:hover>.dropdown-menu {
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display: block;
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}
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.dropdown-submenu>a:after {
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display: block;
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content: " ";
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float: right;
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width: 0;
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height: 0;
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border-color: transparent;
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border-style: solid;
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border-width: 5px 0 5px 5px;
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border-left-color: #cccccc;
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margin-top: 5px;
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margin-right: -10px;
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}
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.dropdown-submenu:hover>a:after {
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2022-01-13 18:59:03 +00:00
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border-left-color: #adb5bd;
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2019-08-28 15:02:47 +00:00
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}
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.dropdown-submenu.pull-left {
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float: none;
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}
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.dropdown-submenu.pull-left>.dropdown-menu {
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left: -100%;
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margin-left: 10px;
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border-radius: 6px 0 6px 6px;
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}
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</style>
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2022-01-13 18:59:03 +00:00
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<script type="text/javascript">
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2019-08-28 15:02:47 +00:00
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// manage active state of menu based on current page
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$(document).ready(function () {
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// active menu anchor
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href = window.location.pathname
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href = href.substr(href.lastIndexOf('/') + 1)
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if (href === "")
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href = "index.html";
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var menuAnchor = $('a[href="' + href + '"]');
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2023-02-08 20:04:22 +00:00
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// mark the anchor link active (and if it's in a dropdown, also mark that active)
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var dropdown = menuAnchor.closest('li.dropdown');
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if (window.bootstrap) { // Bootstrap 4+
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menuAnchor.addClass('active');
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dropdown.find('> .dropdown-toggle').addClass('active');
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} else { // Bootstrap 3
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menuAnchor.parent().addClass('active');
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dropdown.addClass('active');
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}
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2022-01-13 18:59:03 +00:00
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// Navbar adjustments
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var navHeight = $(".navbar").first().height() + 15;
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var style = document.createElement('style');
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var pt = "padding-top: " + navHeight + "px; ";
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var mt = "margin-top: -" + navHeight + "px; ";
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var css = "";
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// offset scroll position for anchor links (for fixed navbar)
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for (var i = 1; i <= 6; i++) {
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css += ".section h" + i + "{ " + pt + mt + "}\n";
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}
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style.innerHTML = "body {" + pt + "padding-bottom: 40px; }\n" + css;
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document.head.appendChild(style);
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2019-08-28 15:02:47 +00:00
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});
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</script>
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<!-- tabsets -->
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<style type="text/css">
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.tabset-dropdown > .nav-tabs {
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display: inline-table;
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max-height: 500px;
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min-height: 44px;
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overflow-y: auto;
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border: 1px solid #ddd;
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border-radius: 4px;
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}
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.tabset-dropdown > .nav-tabs > li.active:before {
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content: "";
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font-family: 'Glyphicons Halflings';
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display: inline-block;
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padding: 10px;
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border-right: 1px solid #ddd;
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}
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.tabset-dropdown > .nav-tabs.nav-tabs-open > li.active:before {
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content: "";
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border: none;
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}
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.tabset-dropdown > .nav-tabs.nav-tabs-open:before {
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content: "";
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font-family: 'Glyphicons Halflings';
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display: inline-block;
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padding: 10px;
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border-right: 1px solid #ddd;
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}
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.tabset-dropdown > .nav-tabs > li.active {
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display: block;
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}
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.tabset-dropdown > .nav-tabs > li > a,
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.tabset-dropdown > .nav-tabs > li > a:focus,
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.tabset-dropdown > .nav-tabs > li > a:hover {
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border: none;
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display: inline-block;
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border-radius: 4px;
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2020-04-27 20:35:41 +00:00
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background-color: transparent;
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2019-08-28 15:02:47 +00:00
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}
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.tabset-dropdown > .nav-tabs.nav-tabs-open > li {
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display: block;
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float: none;
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}
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.tabset-dropdown > .nav-tabs > li {
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display: none;
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}
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</style>
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2020-04-27 20:35:41 +00:00
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<!-- code folding -->
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2019-08-28 15:02:47 +00:00
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2022-04-22 19:12:19 +00:00
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<style type="text/css">
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#TOC {
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margin: 25px 0px 20px 0px;
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}
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@media (max-width: 768px) {
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#TOC {
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position: relative;
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width: 100%;
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}
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}
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@media print {
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.toc-content {
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/* see https://github.com/w3c/csswg-drafts/issues/4434 */
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float: right;
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}
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}
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.toc-content {
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padding-left: 30px;
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padding-right: 40px;
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}
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div.main-container {
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max-width: 1200px;
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}
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div.tocify {
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width: 20%;
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max-width: 260px;
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max-height: 85%;
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}
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@media (min-width: 768px) and (max-width: 991px) {
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div.tocify {
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width: 25%;
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}
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}
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@media (max-width: 767px) {
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div.tocify {
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width: 100%;
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max-width: none;
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}
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}
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.tocify ul, .tocify li {
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line-height: 20px;
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}
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.tocify-subheader .tocify-item {
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Background
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Conventions
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CDM Versions
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<a href="https://github.com/OHDSI/CommonDataModel/issues?q=is%3Aopen+is%3Aissue+label%3AProposal">Under Review</a>
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<a href="https://github.com/OHDSI/CommonDataModel/issues/252">Region_concept_id</a>
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2021-09-22 19:39:44 +00:00
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How to
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<a href="download.html">Download the DDL</a>
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2021-09-22 19:39:44 +00:00
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<a href="cdmRPackage.html">Use the CDM R Package</a>
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<a href="drug_dose.html">Calculate Drug Dose</a>
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2020-04-27 20:35:41 +00:00
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<a href="cdmDecisionTree.html">Help! My Data Doesn't Fit!</a>
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<a href="faq.html">FAQ</a>
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<a href="sqlScripts.html">SQL Scripts</a>
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<a href="contribute.html">Ask a Question</a>
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2019-10-31 19:06:09 +00:00
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</div><!--/.container -->
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</div><!--/.navbar -->
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2022-01-13 18:59:03 +00:00
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<div id="header">
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<h1 class="title toc-ignore">OMOP CDM Frequently Asked Questions</h1>
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</div>
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2023-02-08 20:04:22 +00:00
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<p><strong>1. I understand that the common data model (CDM) is a way of
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organizing disparate data sources into the same relational database
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design, but how can it be effective since many databases use different
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coding schemes?</strong></p>
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<p>During the extract, transform, load (ETL) process of converting a
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data source into the OMOP common data model, we standardize the
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structure (e.g. tables, fields, data types), conventions (e.g. rules
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that govern how source data should be represented), and content
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(e.g. what common vocabularies are used to speak the same language
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across clinical domains). The common data model preserves all source
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data, including the original source vocabulary codes, but adds the
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standardized vocabularies to allow for network research across the
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entire OHDSI research community.</p>
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<p><strong>2. How does my data get transformed into the common data
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model?</strong></p>
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<p>You or someone in your organization will need to create a process to
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build your CDM. Don’t worry though, you are not alone! The open nature
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of the community means that much of the code that other participants
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have written to transform their own data is available for you to use. If
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you have a data license for a large administrative claims database like
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IBM MarketScan® or Optum’s Clinformatics® Extended Data Mart, chances
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are that someone has already done the legwork. Here is one example of a
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full builder freely available on <a
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href="https://github.com/OHDSI/ETL-CDMBuilder">github</a> that has been
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written for a variety of data sources.</p>
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<p>The <a href="http://forums.ohdsi.org/">community forums</a> are also
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a great place to ask questions if you are stuck or need guidance on how
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to represent your data in the common data model. Members are usually
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very responsive!</p>
|
2019-08-28 15:02:47 +00:00
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<p><strong>3. Are any tables or fields optional?</strong></p>
|
2023-02-08 20:04:22 +00:00
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<p>It is expected that all tables will be present in a CDM though it is
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not a requirement that they are all populated. The two mandatory tables
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are:</p>
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<ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<li><a
|
|
|
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|
href="https://github.com/OHDSI/CommonDataModel/wiki/person">Person</a>:
|
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|
|
Contains records that uniquely identify each patient in the source data
|
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|
|
|
|
who is at-risk to have clinical observations recorded within the source
|
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|
|
systems.</li>
|
|
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|
<li><a
|
|
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|
href="https://github.com/OHDSI/CommonDataModel/wiki/observation_period">Observation_period</a>:
|
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|
|
|
Contains records which uniquely define the spans of time for which a
|
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|
|
Person is at-risk to have clinical events recorded within the source
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|
systems.</li>
|
2019-08-28 15:02:47 +00:00
|
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|
</ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>It is then up to you which tables to populate, though the core event
|
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|
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|
|
tables are generally agreed upon to be <a
|
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|
href="https://github.com/OHDSI/CommonDataModel/wiki/CONDITION_OCCURRENCE">Condition_occurrence</a>,
|
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|
<a
|
|
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|
href="https://github.com/OHDSI/CommonDataModel/wiki/PROCEDURE_OCCURRENCE">Procedure_occurrence</a>,
|
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|
<a
|
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|
href="https://github.com/OHDSI/CommonDataModel/wiki/DRUG_EXPOSURE">Drug_exposure</a>,
|
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|
<a
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|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/MEASUREMENT">Measurement</a>,
|
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|
and <a
|
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|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/OBSERVATION">Observation</a>.
|
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|
Each table has certain required fields, a full list of which can be
|
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|
found on the Common Data Model <a
|
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|
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|
href="https://github.com/OHDSI/CommonDataModel/wiki/">wiki page</a>.</p>
|
|
|
|
|
|
<p><strong>4. Does the data model include any derived information? Which
|
|
|
|
|
|
tables or values are derived?</strong></p>
|
|
|
|
|
|
<p>The common data model stores verbatim data from the source across
|
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|
|
|
various clinical domains, such as records for conditions, drugs,
|
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|
|
|
procedures, and measurements. In addition, to assist the analyst, the
|
|
|
|
|
|
common data model also provides some derived tables, based on commonly
|
|
|
|
|
|
used analytic procedures. For example, the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/CONDITION_ERA">Condition_era</a>
|
|
|
|
|
|
table is derived from the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/CONDITION_OCCURENCE">Condition_occurrence</a>
|
|
|
|
|
|
table and both the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/DRUG_ERA">Drug_era</a>
|
|
|
|
|
|
and <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/DOSE_ERA">Dose_era</a>
|
|
|
|
|
|
tables are derived from the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/DRUG_EXPOSURE">Drug_exposure</a>
|
|
|
|
|
|
table. An era is defined as a span of time when a patient is assumed to
|
|
|
|
|
|
have a given condition or exposure to a particular active ingredient.
|
|
|
|
|
|
Members of the community have written code to create these tables and it
|
|
|
|
|
|
is out on the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/tree/master/CodeExcerpts/DerivedTables">github</a>
|
|
|
|
|
|
if you choose to use it in your CDM build. It is important to reinforce,
|
|
|
|
|
|
the analyst has the opportunity, but not the obligation, to use any of
|
|
|
|
|
|
the derived tables and all of the source data is still available for
|
|
|
|
|
|
direct use if the analysis calls for different assumptions.</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
<p><strong>5. How is age captured in the model?</strong></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>Year_of_birth, month_of_birth, day_of_birth and birth_datetime are
|
|
|
|
|
|
all fields in the Person table designed to capture some form of date of
|
|
|
|
|
|
birth. While only year_of_birth is required, these fields allow for
|
|
|
|
|
|
maximum flexibility over a wide range of data sources.</p>
|
|
|
|
|
|
<p><strong>6. How are gender, race, and ethnicity captured in the model?
|
|
|
|
|
|
Are they coded using values a human reader can understand?</strong></p>
|
|
|
|
|
|
<p>Standard Concepts are used to denote all clinical entities throughout
|
|
|
|
|
|
the OMOP common data model, including gender, race, and ethnicity.
|
|
|
|
|
|
Source values are mapped to Standard Concepts during the extract,
|
|
|
|
|
|
transform, load (ETL) process of converting a database to the OMOP
|
|
|
|
|
|
Common Data Model. These are then stored in the Gender_concept_id,
|
|
|
|
|
|
Race_concept_id and Ethnicity_concept_id fields in the Person table.
|
|
|
|
|
|
Because the standard concepts span across all clinical domains, and in
|
|
|
|
|
|
keeping with Cimino’s ‘Desiderata for Controlled Medical Vocabularies in
|
|
|
|
|
|
the Twenty-First Century’, the identifiers are unique, persistent
|
|
|
|
|
|
nonsematic identifiers. Gender, for example, is stored as either 8532
|
|
|
|
|
|
(female) or 8507 (male) in gender_concept_id while the original value
|
|
|
|
|
|
from the source is stored in gender_source_value (M, male, F, etc).</p>
|
|
|
|
|
|
<p><strong>7. Are there conditions/procedures/drugs or other domains
|
|
|
|
|
|
that should be masked or hidden in the CDM?</strong></p>
|
|
|
|
|
|
<p>The masking of information related to a person is dependent on the
|
|
|
|
|
|
organization’s privacy policies and may vary by data asset (<a
|
|
|
|
|
|
href="https://github.com/OHDSI/Themis/issues/21">THEMIS issue
|
|
|
|
|
|
#21</a>).</p>
|
|
|
|
|
|
<p><strong>8. How is time-varying patient information such as location
|
|
|
|
|
|
of residence addressed in the model?</strong></p>
|
|
|
|
|
|
<p>The OMOP common data model has been pragmatically defined based on
|
|
|
|
|
|
the desired analytic use cases of the community, as well as the
|
|
|
|
|
|
available types of data that community members have access to. Prior to
|
|
|
|
|
|
CDM v6.0, each person record had associated demographic attributes which
|
|
|
|
|
|
are assumed to be constant for the patient throughout the course of
|
|
|
|
|
|
their periods of observation, like location and primary care provider.
|
|
|
|
|
|
With the release of CDM v6.0, the Location_History table is now
|
|
|
|
|
|
available to track the movements of people, care sites, and providers
|
|
|
|
|
|
over time. Only the most recent location_id should be stored in the
|
|
|
|
|
|
Person table to eliminate duplication, while the person’s movements are
|
|
|
|
|
|
stored in Location_History.</p>
|
|
|
|
|
|
<p>Something like marital status is a little different as it is
|
|
|
|
|
|
considered to be an observation rather than a demographic attribute.
|
|
|
|
|
|
This means that it is housed in the Observation table rather than the
|
|
|
|
|
|
Person table, giving the opportunity to store each change in status as a
|
|
|
|
|
|
unique record.</p>
|
|
|
|
|
|
<p>If someone in the community had a use case for time-varying location
|
|
|
|
|
|
of residence and also had source data that contains this information,
|
|
|
|
|
|
we’d welcome participation in the CDM workgroup to evolve the model
|
|
|
|
|
|
further.</p>
|
|
|
|
|
|
<p><strong>9. How does the model denote the time period during which a
|
|
|
|
|
|
Person’s information is valid?</strong></p>
|
|
|
|
|
|
<p>The OMOP Common Data Model uses something called observation periods
|
|
|
|
|
|
(stored in the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/observation_period">Observation_period</a>
|
|
|
|
|
|
table) as a way to define the time span during which a patient is
|
|
|
|
|
|
at-risk to have a clinical event recorded. In administrative claims
|
|
|
|
|
|
databases, for example, these observation periods are often analogous to
|
|
|
|
|
|
the notion of ‘enrollment’.</p>
|
|
|
|
|
|
<p><strong>10. How does the model capture start and stop dates for
|
|
|
|
|
|
insurance coverage? What if a person’s coverage changes?</strong></p>
|
|
|
|
|
|
<p>The <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/payer_plan_period">Payer_plan_period</a>
|
|
|
|
|
|
table captures details of the period of time that a Person is
|
|
|
|
|
|
continuously enrolled under a specific health Plan benefit structure
|
|
|
|
|
|
from a given Payer. Payer plan periods, as opposed to observation
|
|
|
|
|
|
periods, can overlap so as to denote the time when a Person is enrolled
|
|
|
|
|
|
in multiple plans at the same time such as Medicare Part A and Medicare
|
|
|
|
|
|
Part D.</p>
|
|
|
|
|
|
<p><strong>11. What if I have EHR data? How would I create observation
|
|
|
|
|
|
periods?</strong></p>
|
|
|
|
|
|
<p>An observation period is considered as the time at which a patient is
|
|
|
|
|
|
at-risk to have a clinical event recorded in the source system.
|
|
|
|
|
|
Determining the appropriate observation period for each source data can
|
|
|
|
|
|
vary, depending on what information the source contains. If a source
|
|
|
|
|
|
does not provide information about a patient’s entry or exit from a
|
|
|
|
|
|
system, then reasonable heuristics need to be developed and applied
|
|
|
|
|
|
within the ETL.</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
<div id="vocabulary-mapping" class="section level2">
|
|
|
|
|
|
<h2>Vocabulary Mapping</h2>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p><strong>12. Do I have to map my source codes to Standard Concepts
|
|
|
|
|
|
myself? Are there vocabulary mappings that already exist for me to
|
|
|
|
|
|
leverage?</strong></p>
|
|
|
|
|
|
<p>If your data use any of the 55 source vocabularies that are currently
|
|
|
|
|
|
supported, the mappings have been done for you. The full list is
|
|
|
|
|
|
available from the open-source <a
|
|
|
|
|
|
href="http://athena.ohdsi.org/search-terms/terms">ATHENA</a> tool under
|
|
|
|
|
|
the download tab (see below). You can choose to download the ten <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/Standardized-Vocabularies">vocabulary
|
|
|
|
|
|
tables</a> from there as well – you will need a copy in your environment
|
|
|
|
|
|
if you plan on building a CDM.</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
<p><img src="images/Athena_download_box.png" /></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>The <a href="http://athena.ohdsi.org/search-terms/terms">ATHENA</a>
|
|
|
|
|
|
tool also allows you to explore the vocabulary before downloading it if
|
|
|
|
|
|
you are curious about the mappings or if you have a specific code in
|
|
|
|
|
|
mind and would like to know which standard concept it is associated
|
|
|
|
|
|
with; just click on the search tab and type in a keyword to begin
|
|
|
|
|
|
searching.</p>
|
|
|
|
|
|
<p><strong>13. If I want to apply the mappings myself, can I do so? Are
|
|
|
|
|
|
they transparent to all users?</strong></p>
|
|
|
|
|
|
<p>Yes, all mappings are available in the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/CommonDataModel/wiki/CONCEPT_RELATIONSHIP">Concept_relationship</a>
|
|
|
|
|
|
table (which can be downloaded from <a
|
|
|
|
|
|
href="http://athena.ohdsi.org/search-terms/terms">ATHENA</a>). Each
|
|
|
|
|
|
value in a supported source terminology is assigned a Concept_id (which
|
|
|
|
|
|
is considered non-standard). Each Source_concept_id will have a mapping
|
|
|
|
|
|
to a Standard_concept_id. For example:</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
<p><img src="images/Sepsis_to_SNOMED.png" /></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>In this case the standard SNOMED concept 201826 for type 2 diabetes
|
|
|
|
|
|
mellitus would be stored in the Condition_occurrence table as the
|
|
|
|
|
|
Condition_concept_id and the ICD10CM concept 1567956 for type 2 diabetes
|
|
|
|
|
|
mellitus would be stored as the Condition_source_concept_id.</p>
|
|
|
|
|
|
<p><strong>14. Can RXNorm codes be stored in the model? Can I store
|
|
|
|
|
|
multiple levels if I so choose? What if one collaborator uses a
|
|
|
|
|
|
different level of RXNorm than I use when transforming their
|
|
|
|
|
|
database?</strong></p>
|
|
|
|
|
|
<p>In the OMOP Common Data Model RXNorm is considered the standard
|
|
|
|
|
|
vocabulary for representing drug exposures. One of the great things
|
|
|
|
|
|
about the Standardized Vocabulary is that the hierarchical nature of
|
|
|
|
|
|
RXNorm is preserved to enable efficient querying. It is agreed upon best
|
|
|
|
|
|
practice to store the lowest level RXNorm available and then use the
|
|
|
|
|
|
Vocabulary to explore any pertinent relationships. Drug ingredients are
|
|
|
|
|
|
the highest-level ancestors so a query for the descendants of an
|
|
|
|
|
|
ingredient should turn up all drug products (Clinical Drug or Branded
|
|
|
|
|
|
Drug) containing that ingredient. A query designed in this way will find
|
|
|
|
|
|
drugs of interest in any CDM regardless of the level of RXNorm used.</p>
|
|
|
|
|
|
<p><strong>15. What if the vocabulary has a mapping I don’t agree with?
|
|
|
|
|
|
Can it be changed?</strong></p>
|
|
|
|
|
|
<p>Yes, that is the beauty of the community! If you find a mapping in
|
|
|
|
|
|
the vocabulary that doesn’t seem to belong or that you think could be
|
|
|
|
|
|
better, feel free to write a note on the <a
|
|
|
|
|
|
href="https://forums.ohdsi.org/">forums</a> or on the <a
|
|
|
|
|
|
href="https://github.com/OHDSI/Vocabulary-v5.0/issues">vocabulary
|
|
|
|
|
|
github</a>. If the community agrees with your assessment it will be
|
|
|
|
|
|
addressed in the next vocabulary version.</p>
|
|
|
|
|
|
<p><strong>16. What if I have source codes that are specific to my site?
|
|
|
|
|
|
How would these be mapped?</strong></p>
|
|
|
|
|
|
<p>In the OMOP Vocabulary there is an empty table called the
|
|
|
|
|
|
Source_to_concept_map. It is a simple table structure that allows you to
|
|
|
|
|
|
establish mapping(s) for each source code with a standard concept in the
|
|
|
|
|
|
OMOP Vocabulary (TARGET_CONCEPT_ID). This work can be facilitated by the
|
|
|
|
|
|
OHDSI tool <a href="https://github.com/OHDSI/Usagi">Usagi</a> (pictured
|
|
|
|
|
|
below) which searches for text similarity between your source code
|
|
|
|
|
|
descriptions and the OMOP Vocabulary and exports mappings in a
|
|
|
|
|
|
SOURCE_TO_CONCEPT_MAP table structure. Example Source_to_concept_map
|
|
|
|
|
|
files can be found <a
|
|
|
|
|
|
href="https://github.com/OHDSI/ETL-CDMBuilder/tree/master/man/VOCABULARY_ADDITIONS">here</a>.
|
|
|
|
|
|
These generated Source_to_concept_map files are then loaded into the
|
|
|
|
|
|
OMOP Vocabulary’s empty Source_to_concept_map prior to processing the
|
|
|
|
|
|
native data into the CDM so that the CDM builder can use them in a
|
|
|
|
|
|
build.</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
<p><img src="images/Usagi.png" /></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>If an source code is not supported by the OMOP Vocabulary, one can
|
|
|
|
|
|
create a new records in the CONCEPT table, however the CONCEPT_IDs
|
|
|
|
|
|
should start >2000000000 so that it is easy to tell between the OMOP
|
|
|
|
|
|
Vocabulary concepts and the site specific concepts. Once those concepts
|
|
|
|
|
|
exist CONCEPT_RELATIONSHIPS can be generated to assign them to a
|
|
|
|
|
|
standard terminologies, USAGI can facilitate this process as well (<a
|
|
|
|
|
|
href="https://github.com/OHDSI/Themis/issues/22">THEMIS issue
|
|
|
|
|
|
#22</a>).</p>
|
2021-01-06 15:52:57 +00:00
|
|
|
|
<p><strong>17. How are one-to-many mappings applied?</strong></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>If one source code maps to two Standard Concepts then two rows are
|
|
|
|
|
|
stored in the corresponding clinical event table.</p>
|
|
|
|
|
|
<p><strong>18. What if I want to keep my original data as well as the
|
|
|
|
|
|
mapped values? Is there a way for me to do that?</strong></p>
|
|
|
|
|
|
<p>Yes! Source values and Source Concepts are fully maintained within
|
|
|
|
|
|
the OMOP Common Data Model. A Source Concept represents the code in the
|
|
|
|
|
|
source data. Each Source Concept is mapped to one or more Standard
|
|
|
|
|
|
Concepts during the ETL process and both are stored in the corresponding
|
|
|
|
|
|
clinical event table. If no mapping is available, the Standard Concept
|
|
|
|
|
|
with the concept_id = 0 is written into the *_concept_id field
|
|
|
|
|
|
(Condition_concept_id, Procedure_concept_id, etc.) so as to preserve the
|
|
|
|
|
|
record from the native data.</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
</div>
|
|
|
|
|
|
<div id="common-data-model-versioning" class="section level2">
|
|
|
|
|
|
<h2>Common Data Model Versioning</h2>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p><strong>19. Who decides when and how to change the data
|
|
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model?</strong></p>
|
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<p>The community! There is a <a
|
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|
|
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href="https://docs.google.com/document/d/144e_fc7dyuinfJfbYW5MsJeSijVSzsNE7GMY6KRX10g/edit?usp=sharing">working
|
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group</a> designed around updating the model and everything is done by
|
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consensus. Members submit proposed changes to the <a
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href="https://github.com/OHDSI/CommonDataModel">github</a> in the form
|
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of <a href="https://github.com/OHDSI/CommonDataModel/issues">issues</a>
|
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and the group meets once a month to discuss and vote on the changes. Any
|
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ratified proposals are then added to the queue for a future version of
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the Common Data Model.</p>
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<p><strong>20. Are changes to the model backwards
|
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compatible?</strong></p>
|
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<p>Generally point version changes (5.1 -> 5.2) are backwards
|
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compatible and major version changes (4.0 -> 5.0) may not be. All
|
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updates to the model are listed in the release notes for each version
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and anything that could potentially affect backwards compatibility is
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clearly labeled.</p>
|
2021-01-06 15:52:57 +00:00
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<p><strong>21. How frequently does the model change?</strong></p>
|
2023-02-08 20:04:22 +00:00
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<p>The current schedule is for major versions to be released every year
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and point versions to be release every quarter though that is subject to
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the needs of the community.</p>
|
2021-01-06 15:52:57 +00:00
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<p><strong>22. What is the dissemination plan for changes?</strong></p>
|
2023-02-08 20:04:22 +00:00
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<p>Changes are first listed in the release notes on the <a
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href="https://github.com/OHDSI/CommonDataModel/">github</a> and in the
|
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<a href="https://github.com/OHDSI/CommonDataModel/wiki">common data
|
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|
|
model wiki</a>. New versions are also announced on the weekly community
|
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calls and on the <a href="https://forums.ohdsi.org">community
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forums</a>.</p>
|
2019-08-28 15:02:47 +00:00
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</div>
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|
<div id="ohdsi-tools" class="section level2">
|
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<h2>OHDSI Tools</h2>
|
2023-02-08 20:04:22 +00:00
|
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<p><strong>23. What are the currently available analytic
|
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tools?</strong></p>
|
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<p>While there are a variety of tools freely available from the
|
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community, these are the most widely used:</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
<ul>
|
2023-02-08 20:04:22 +00:00
|
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|
<li><a href="http://www.github.com/ohdsi/achilles">ACHILLES</a> – a
|
|
|
|
|
|
stand-alone tool for database characterization</li>
|
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|
|
<li><a href="http://www.ohdsi.org/web/atlas/#/home">ATLAS</a> - an
|
|
|
|
|
|
integrated platform for vocabulary exploration, cohort definition, case
|
|
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|
|
|
review, clinical characterization, incidence estimation,
|
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|
|
population-level effect estimation design, and patient-level prediction
|
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|
|
|
design (<a href="http://www.github.com/ohdsi/atlas">link to
|
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|
|
github</a>)</li>
|
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|
|
<li><a href="https://github.com/OHDSI/ArachneUI">ARACHNE</a> – a tool to
|
|
|
|
|
|
facilitate distributed network analyses</li>
|
|
|
|
|
|
<li><a href="https://github.com/OHDSI/whiterabbit">WhiteRabbit</a> - an
|
|
|
|
|
|
application that can be used to analyse the structure and contents of a
|
|
|
|
|
|
database as preparation for designing an ETL</li>
|
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|
|
<li><a href="https://github.com/OHDSI/whiterabbit">RabbitInAHat</a> - an
|
|
|
|
|
|
application for interactive design of an ETL to the OMOP Common Data
|
|
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|
|
|
Model with the help of the the scan report generated by White
|
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|
Rabbit</li>
|
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|
|
<li><a href="https://github.com/OHDSI/usagi">Usagi</a> - an application
|
|
|
|
|
|
to help create mappings between coding systems and the Vocabulary
|
|
|
|
|
|
standard concepts.</li>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
</ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p><strong>24. Who is responsible for updating the tools to account for
|
|
|
|
|
|
data model changes, bugs, and errors?</strong></p>
|
|
|
|
|
|
<p>The community! All the tools are open source meaning that anyone can
|
|
|
|
|
|
submit an issue they have found, offer suggestions, and write code to
|
|
|
|
|
|
fix the problem.</p>
|
|
|
|
|
|
<p><strong>25. Do the current tools allow a user to define a treatment
|
|
|
|
|
|
gap (persistence window) of any value when creating treatment
|
|
|
|
|
|
episodes?</strong></p>
|
|
|
|
|
|
<p>Yes – the ATLAS tool allows you to specify a persistence window
|
|
|
|
|
|
between drug exposures when defining a cohort (see image below).</p>
|
2021-01-06 15:52:57 +00:00
|
|
|
|
<p><img src="images/ATLAS_Persistence_Window.png" /></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p><strong>26. Can the current tools identify medication use during
|
|
|
|
|
|
pregnancy?</strong></p>
|
|
|
|
|
|
<p>Yes, you can identify pregnancy markers from various clinical
|
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|
|
|
domains, including conditions and procedures, for example ‘live birth’,
|
|
|
|
|
|
and then define temporal logic to look for drug exposure records in some
|
|
|
|
|
|
interval prior to the pregnancy end. In addition, members of the
|
|
|
|
|
|
community have built an advanced logic to define pregnancy episodes with
|
|
|
|
|
|
all pregnancy outcomes represented, which can be useful for this type of
|
|
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|
|
|
research.</p>
|
|
|
|
|
|
<p><strong>27. Do the current tools execute against the mapped values or
|
|
|
|
|
|
source values?</strong></p>
|
|
|
|
|
|
<p>The tools can execute against both source and mapped values, though
|
|
|
|
|
|
mapped values are strongly encouraged. Since one of the aims of OHDSI is
|
|
|
|
|
|
to create a distributed data network across the world on which to run
|
|
|
|
|
|
research studies, the use of source values fails to take advantage of
|
|
|
|
|
|
the benefits of the Common Data Model.</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
</div>
|
|
|
|
|
|
<div id="network-research-studies" class="section level2">
|
|
|
|
|
|
<h2>Network Research Studies</h2>
|
2021-01-06 15:52:57 +00:00
|
|
|
|
<p><strong>28. Who can generate requests?</strong></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>Anyone in the community! Any question that gains enough interest and
|
|
|
|
|
|
participation can be a network research study.</p>
|
|
|
|
|
|
<p><strong>29. Who will develop the queries to distribute to the
|
|
|
|
|
|
network?</strong></p>
|
|
|
|
|
|
<p>Typically a principal investigator leads the development of a
|
|
|
|
|
|
protocol. The PI may also lead the development of the analysis procedure
|
|
|
|
|
|
corresponding to the protocol. If the PI does not have the technical
|
|
|
|
|
|
skills required to write the analysis procedure that implements the
|
|
|
|
|
|
protocol, someone in the community can help them put it together.</p>
|
2021-01-06 15:52:57 +00:00
|
|
|
|
<p><strong>30. What language are the queries written in?</strong></p>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>Queries are written in R and SQL. The <a
|
|
|
|
|
|
href="https://github.com/OHDSI/sqlrender">SqlRender</a> package can
|
|
|
|
|
|
translate any query written in a templated SQL Server-like dialect to
|
|
|
|
|
|
any of the supported RDBMS environments, including Postgresql, Oracle,
|
|
|
|
|
|
Redshift, Parallel Data Warehouse, Hadoop Impala, Google BigQuery, and
|
|
|
|
|
|
Netezza.</p>
|
|
|
|
|
|
<p><strong>31. How do the queries get to the data partners and how are
|
|
|
|
|
|
they run once there?</strong></p>
|
|
|
|
|
|
<p>OHDSI runs as a distributed data network. All analyses are publicly
|
|
|
|
|
|
available and can be downloaded to run at each site. The packages can be
|
|
|
|
|
|
run locally and, at the data partner’s discretion, aggregate results can
|
|
|
|
|
|
be shared with the study coordinator.</p>
|
|
|
|
|
|
<p>Data partners can also make use of one of OHDSI’s open-source tools
|
|
|
|
|
|
called <a href="https://github.com/OHDSI/arachne">ARACHNE</a>, a tool to
|
|
|
|
|
|
facilitate distributed network analytics against the OMOP CDM.</p>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
</div>
|
2022-04-22 19:12:19 +00:00
|
|
|
|
<div id="recommended-system-requirements" class="section level2">
|
|
|
|
|
|
<h2>Recommended System Requirements</h2>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>It is difficult to recommend what technical capabilities a site needs
|
|
|
|
|
|
to set up an ETL because it is heavily dependent on the amount of data
|
|
|
|
|
|
they have and how they plan to use it. Here are some examples of options
|
|
|
|
|
|
that have worked well for small to medium organizations and large
|
|
|
|
|
|
organizations:</p>
|
2022-04-22 19:12:19 +00:00
|
|
|
|
<p><strong>Small-to-Medium Organization</strong></p>
|
|
|
|
|
|
<ul>
|
|
|
|
|
|
<li>CDM size is 100MB to several GBs</li>
|
|
|
|
|
|
<li>Vocab ~20GB</li>
|
|
|
|
|
|
<li>Results < 500 MB</li>
|
|
|
|
|
|
<li>Recommend
|
|
|
|
|
|
<ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<li>Server class machine disk >= 250GB (SSD preferred), >= 4
|
|
|
|
|
|
cores, >= 32GB RAM</li>
|
2022-04-22 19:12:19 +00:00
|
|
|
|
</ul></li>
|
|
|
|
|
|
</ul>
|
|
|
|
|
|
<p><strong>Large Organization</strong></p>
|
|
|
|
|
|
<ul>
|
|
|
|
|
|
<li>CDM size is 12GB to several TBs</li>
|
|
|
|
|
|
<li>Vocab ~20GB</li>
|
|
|
|
|
|
<li>Results < 500 MB</li>
|
|
|
|
|
|
<li>Recommend
|
|
|
|
|
|
<ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<li>Cloud-based infrastructure like multiple AWS Redshift clusters, for
|
|
|
|
|
|
example:</li>
|
2022-04-22 19:12:19 +00:00
|
|
|
|
<li><img src="images/AWS_clusters.png" /></li>
|
|
|
|
|
|
</ul></li>
|
|
|
|
|
|
</ul>
|
|
|
|
|
|
</div>
|
2019-08-28 15:02:47 +00:00
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2022-04-22 19:12:19 +00:00
|
|
|
|
</div>
|
|
|
|
|
|
</div>
|
2019-08-28 15:02:47 +00:00
|
|
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</div>
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<script>
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// add bootstrap table styles to pandoc tables
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function bootstrapStylePandocTables() {
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$('tr.odd').parent('tbody').parent('table').addClass('table table-condensed');
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}
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$(document).ready(function () {
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bootstrapStylePandocTables();
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});
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</script>
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2020-04-27 20:35:41 +00:00
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<!-- tabsets -->
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<script>
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$(document).ready(function () {
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window.buildTabsets("TOC");
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});
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$(document).ready(function () {
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$('.tabset-dropdown > .nav-tabs > li').click(function () {
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$(this).parent().toggleClass('nav-tabs-open');
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2020-04-27 20:35:41 +00:00
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});
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});
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</script>
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<!-- code folding -->
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2022-04-22 19:12:19 +00:00
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<script>
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$(document).ready(function () {
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// temporarily add toc-ignore selector to headers for the consistency with Pandoc
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$('.unlisted.unnumbered').addClass('toc-ignore')
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// move toc-ignore selectors from section div to header
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$('div.section.toc-ignore')
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.removeClass('toc-ignore')
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.children('h1,h2,h3,h4,h5').addClass('toc-ignore');
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// establish options
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var options = {
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selectors: "h1,h2,h3,h4,h5",
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theme: "bootstrap3",
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context: '.toc-content',
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hashGenerator: function (text) {
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return text.replace(/[.\\/?&!#<>]/g, '').replace(/\s/g, '_');
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ignoreSelector: ".toc-ignore",
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scrollTo: 0
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};
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options.showAndHide = true;
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options.smoothScroll = true;
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// tocify
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var toc = $("#TOC").tocify(options).data("toc-tocify");
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});
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</script>
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2020-04-27 20:35:41 +00:00
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2019-08-28 15:02:47 +00:00
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<script>
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var script = document.createElement("script");
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script.src = "https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML";
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document.getElementsByTagName("head")[0].appendChild(script);
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</body>
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