2021-09-22 19:39:44 +00:00
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<title>Observation Period Considerations for EHR Data</title>
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2023-10-26 18:13:30 +00:00
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2022-01-13 18:59:03 +00:00
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2021-09-22 19:39:44 +00:00
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2022-01-13 18:59:03 +00:00
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2021-09-22 19:39:44 +00:00
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2023-10-26 18:13:30 +00:00
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2021-09-22 19:39:44 +00:00
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2022-07-27 01:48:28 +00:00
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2021-09-22 19:39:44 +00:00
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2022-07-27 01:48:28 +00:00
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2022-01-13 18:59:03 +00:00
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2021-09-22 19:39:44 +00:00
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</style>
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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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display: block;
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float: right;
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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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2022-01-13 18:59:03 +00:00
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border-left-color: #adb5bd;
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2021-09-22 19:39:44 +00:00
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}
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float: none;
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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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2021-09-22 19:39:44 +00:00
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// manage active state of menu based on current page
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// active menu anchor
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href = window.location.pathname
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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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} else { // Bootstrap 3
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2022-01-13 18:59:03 +00:00
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// Navbar adjustments
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// offset scroll position for anchor links (for fixed navbar)
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style.innerHTML = "body {" + pt + "padding-bottom: 40px; }\n" + css;
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2021-09-22 19:39:44 +00:00
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2023-10-26 18:13:30 +00:00
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2021-09-22 19:39:44 +00:00
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font-family: 'Glyphicons Halflings';
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padding: 10px;
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border-right: 1px solid #ddd;
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2023-10-26 18:13:30 +00:00
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content: "\e258";
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2021-09-22 19:39:44 +00:00
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font-family: 'Glyphicons Halflings';
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2023-10-26 18:13:30 +00:00
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border: none;
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2021-09-22 19:39:44 +00:00
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}
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border: none;
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display: inline-block;
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border-radius: 4px;
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background-color: transparent;
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display: block;
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float: none;
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display: none;
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<!-- code folding -->
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</head>
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<body>
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<div class="container-fluid main-container">
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2022-07-27 01:48:28 +00:00
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2021-09-22 19:39:44 +00:00
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<a class="navbar-brand" href="index.html"><div><img src="ohdsi16x16.png"></img> OMOP Common Data Model </div></a>
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2023-02-08 20:04:22 +00:00
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2021-09-22 19:39:44 +00:00
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2022-07-27 01:48:28 +00:00
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2022-01-13 18:59:03 +00:00
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2021-09-22 19:39:44 +00:00
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Background
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<a href="cdmRefreshProcess.html">CDM Refresh Process</a>
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<a href="vocabulary.html">How the Vocabulary is Built</a>
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2022-07-27 01:48:28 +00:00
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2022-01-13 18:59:03 +00:00
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2021-09-22 19:39:44 +00:00
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Conventions
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<span class="caret"></span>
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</a>
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<a href="dataModelConventions.html">General Conventions</a>
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<li>
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<a href="ehrObsPeriods.html">Observation Periods for EHR Data</a>
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</li>
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<li>
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<a href="cdmPrivacy.html">Patient Privacy and OMOP</a>
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2022-07-27 01:48:28 +00:00
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2022-01-13 18:59:03 +00:00
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2021-09-22 19:39:44 +00:00
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CDM Versions
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<span class="caret"></span>
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</a>
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<ul class="dropdown-menu" role="menu">
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<li>
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<a href="cdm30.html">CDM v3.0</a>
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</li>
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2021-09-22 19:39:44 +00:00
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2023-02-08 20:04:22 +00:00
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<h1 class="title toc-ignore"><strong>Observation Period Considerations
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for EHR Data</strong></h1>
|
2021-09-22 19:39:44 +00:00
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</div>
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<p><em>By Melanie Philofsky and the EHR Working Group</em></p>
|
2023-02-08 20:04:22 +00:00
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<p>The EHR WG convened on July 24, August 7, and August 21, 2020 to
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discuss the creation of an Observation Period from EHR data. The current
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and future conventions are not prescriptive enough and leave room for
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various ways of interpretation. The goals of our discussions were to
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increase the standardization for the implementation of the
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OBSERVATION_PERIOD table by providing some general guidelines for
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determining the start, end, and gaps in Observation Periods. The
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suggestions we came up with are only “suggestions” at this point. More
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research should be done to understand how these choices might impact
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evidence generated using these data. All of these decisions should be
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tempered by local understanding of patients in the EHR you are
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ETLing.</p>
|
2021-09-22 19:39:44 +00:00
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|
<ul>
|
2023-02-08 20:04:22 +00:00
|
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<li><em>Note - These suggestions are not intended for HMO EHR sites
|
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|
since HMO EHR Observation Periods more closely resemble claims data
|
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|
Observation Periods.</em></li>
|
2021-09-22 19:39:44 +00:00
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</ul>
|
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|
<div id="observation-period-start-date" class="section level2">
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<h2>Observation Period Start Date</h2>
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<ul>
|
2023-02-08 20:04:22 +00:00
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<li>Generally an Observation Period does NOT begin before birth,
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|
however, it might begin before birth IF the pregnant mother receives
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care recorded in your EHR. The child’s record is then split from the
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|
mother’s record at birth but may retain care given during pregnancy. For
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these children in your dataset, the field
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|
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<strong>observation_period_start_date should be the birth date minus 9
|
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|
|
months</strong></li>
|
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|
<li>An <strong>Observation Period does NOT begin before the
|
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|
|
implementation of the EHR at your site</strong>. Any records prior to
|
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implementation are probably “history of” record types and not a complete
|
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|
|
EHR record of clinical events.</li>
|
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|
|
<li>Special consideration should be given to migration from previous
|
|
|
|
|
EHR, implementation at different sites within your healthcare system,
|
|
|
|
|
implementation of different modules, etc.</li>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
</ul>
|
|
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|
|
</div>
|
|
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|
|
<div id="observation-period-end-date" class="section level2">
|
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|
<h2>Observation Period end date</h2>
|
2023-02-08 20:04:22 +00:00
|
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|
|
<p>Set the <strong>observation_period_end_date</strong> as the first
|
|
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|
|
date from the following:</p>
|
2021-09-22 19:39:44 +00:00
|
|
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|
<ul>
|
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|
<li><strong>Date of death + 60 days</strong>
|
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|
<ul>
|
2023-02-08 20:04:22 +00:00
|
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|
<li>This is a CDM convention to allow events after death (autopsy, final
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|
|
notes, etc).</li>
|
2021-09-22 19:39:44 +00:00
|
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</ul></li>
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|
<li><strong>Last clinical event + 60 days</strong>
|
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<ul>
|
2023-02-08 20:04:22 +00:00
|
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|
<li>The assumption is that person will return to the same health
|
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|
provider if an adverse reaction/complication/unresolved condition
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occurs.</li>
|
2021-09-22 19:39:44 +00:00
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</ul></li>
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<li><strong>Date of the data pull from the system</strong></li>
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</ul>
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</div>
|
2023-02-08 20:04:22 +00:00
|
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|
<div id="observation-period-gaps-and-persistence-windows"
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|
class="section level2">
|
2021-09-22 19:39:44 +00:00
|
|
|
|
<h2>Observation Period Gaps and Persistence Windows</h2>
|
|
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|
|
<div id="observation-period-gaps" class="section level3">
|
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|
|
<h3>Observation Period Gaps</h3>
|
2023-02-08 20:04:22 +00:00
|
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|
<p>Periods of time when a Person does not receive care from your
|
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|
|
institution and therefore is not observed and should not have an
|
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|
|
Observation Period. These gaps are usually hard to determine because
|
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|
most Persons don’t announce their departure from an EHR/healthcare
|
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|
|
institution. Therefore, a heuristic will need to be instituted to
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|
|
determine Observation Period Gaps where the information is not
|
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|
|
explicit.</p>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
</div>
|
|
|
|
|
<div id="observation-period-persistence-window" class="section level3">
|
|
|
|
|
<h3>Observation Period Persistence Window</h3>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>Defined as the maximum time allowed between two clinical events under
|
|
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|
|
the assumption a Person would have a clinical event recorded, if they
|
|
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|
|
are not healthy and seek care.</p>
|
|
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|
|
<p><strong>Example:</strong> Person 1 has a series of clinical events
|
|
|
|
|
recorded from <strong>Jan. 1, 2010 to June 15, 2012</strong>, where the
|
|
|
|
|
time between clinical events does not exceed 60 days. The next clinical
|
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|
|
event for Person 1 is on <strong>Oct. 1, 2018</strong>. Starting Oct. 1,
|
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|
|
|
2018 Person 1 has clinical events occurring at least every 90 days up to
|
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|
|
the present date.</p>
|
|
|
|
|
<p>There is a 6+ year gap between groups of clinical events recorded in
|
|
|
|
|
the CDM. After discussion in the EHR WG, we believe this 6+ year gap is
|
|
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|
|
indicative of a Person not being seen within our EHR/healthcare
|
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|
|
institution. Per convention #4 for Observation Period table, “As a
|
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|
|
|
general assumption, during an Observation Period any clinical event that
|
|
|
|
|
happens to the patient is expected to be recorded. Conversely, the
|
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|
|
|
absence of data indicates that no clinical events occurred to the
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|
|
|
|
patient.” Person 1 has two Observation Periods.</p>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
<p><strong>1st Observation Period</strong></p>
|
|
|
|
|
<ul>
|
|
|
|
|
<li>observation_period_start_date = <strong>01/01/2010</strong></li>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<li>observation_period_end_date = <strong>08/15/2012</strong> (Per the
|
|
|
|
|
end_date guideline above)</li>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
</ul>
|
|
|
|
|
<p><strong>2nd Observation Period</strong></p>
|
|
|
|
|
<ul>
|
|
|
|
|
<li>observation_period_start_date = <strong>10/01/2018</strong></li>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<li>observation_period_end_date = <strong>09/01/2020</strong> (Date of
|
|
|
|
|
the data pull, per the end_date guideline above)</li>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
</ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>Now, there are cases where a Person only receives care within you EHR
|
|
|
|
|
system when absolutely necessary. And if your EHR doesn’t offer primary
|
|
|
|
|
care services, the majority of Persons who lack healthcare insurance or
|
|
|
|
|
any other reason why Persons are only seen in urgent or emergent
|
|
|
|
|
situations, the above heuristic might be too restrictive. This is a
|
|
|
|
|
guideline. A question the EHR WG debated was how long between clinical
|
|
|
|
|
events should we assume any clinical event that happens to the Person is
|
|
|
|
|
expected to be recorded? When should we end one Observation Period and
|
|
|
|
|
begin another? What should be the time between events for an Observation
|
|
|
|
|
Period Persistence Window? Wellness checkups/Visits happen approximately
|
|
|
|
|
every 12-18 months depending on a multitude of factors.</p>
|
|
|
|
|
<p><strong>Our recommendation: If Observation Period Gaps are 548 days
|
|
|
|
|
or more, then the previous Observation Period should end and another
|
|
|
|
|
Observation Period should begin on the date of the next clinical event
|
|
|
|
|
as per the Person 1 example above.</strong></p>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
</div>
|
|
|
|
|
</div>
|
|
|
|
|
<div id="additional-etl-considerations" class="section level2">
|
|
|
|
|
<h2>Additional ETL considerations</h2>
|
|
|
|
|
<ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<li>Implementation of your EHR, migration from previous EHR,
|
|
|
|
|
implementation at different sites within your healthcare system,
|
|
|
|
|
implementation of different modules</li>
|
|
|
|
|
<li>Coverage of your healthcare system within your area, population
|
|
|
|
|
served by the healthcare system</li>
|
|
|
|
|
<li>All decisions should be tempered by local understanding of patients
|
|
|
|
|
in the EHR you are ETLing.</li>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
</ul>
|
2023-02-08 20:04:22 +00:00
|
|
|
|
<p>The Observation Period can be created by only one clinical event.
|
|
|
|
|
However, the clinical event must NOT be from the Death table. If a Death
|
|
|
|
|
date does not have any other clinical records 18 months before AND 18
|
|
|
|
|
months after the death date, then an Observation Period will not be
|
|
|
|
|
created. We believe this logic is needed because if a Person only has a
|
|
|
|
|
death death_date without other clinical event records, a Person is most
|
|
|
|
|
likely not being “observed” when the death occurred. If a Person was
|
|
|
|
|
being observed at their time of death, then other records (visit,
|
|
|
|
|
condition, measurement, etc.) would be created. This rule is most
|
|
|
|
|
relevant for those with death registry data since a Person who dies in
|
|
|
|
|
the hospital has many clinical event records.</p>
|
2021-09-22 19:39:44 +00:00
|
|
|
|
</div>
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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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|
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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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|
|
}
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|
$(document).ready(function () {
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|
bootstrapStylePandocTables();
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