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The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns TRUE for every new get_episode() index, and is thus equal to !duplicated(get_episode(...))."><title>Determine (New) Episodes for Patients — get_episode • AMR (for R)</title><!-- favicons --><link rel="icon" type="image/png" sizes="16x16" href="../favicon-16x16.png"><link rel="icon" type="image/png" sizes="32x32" href="../favicon-32x32.png"><link rel="apple-touch-icon" type="image/png" sizes="180x180" href="../apple-touch-icon.png"><link rel="apple-touch-icon" type="image/png" sizes="120x120" href="../apple-touch-icon-120x120.png"><link rel="apple-touch-icon" type="image/png" sizes="76x76" href="../apple-touch-icon-76x76.png"><link rel="apple-touch-icon" type="image/png" sizes="60x60" href="../apple-touch-icon-60x60.png"><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><link href="../deps/Fira_Code-0.4.5/font.css" rel="stylesheet"><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><link href="../extra.css" rel="stylesheet"><script src="../extra.js"></script><meta property="og:title" content="Determine (New) Episodes for Patients — get_episode"><meta property="og:description" content="These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument episode_days. This can be used to determine clinical episodes for any epidemiological analysis. The get_episode() function returns the index number of the episode per group, while the is_new_episode() function returns TRUE for every new get_episode() index, and is thus equal to !duplicated(get_episode(...))."><meta property="og:image" content="https://msberends.github.io/AMR/logo.svg"><meta name="twitter:card" content="summary_large_image"><meta name="twitter:creator" content="@msberends"><meta name="twitter:site" content="@msberends"><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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<img src="../logo.svg" class="logo" alt=""><h1>Determine (New) Episodes for Patients</h1>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/get_episode.R" class="external-link"><code>R/get_episode.R</code></a></small>
<div class="d-none name"><code>get_episode.Rd</code></div>
</div>
<div class="ref-description section level2">
<p>These functions determine which items in a vector can be considered (the start of) a new episode, based on the argument <code>episode_days</code>. This can be used to determine clinical episodes for any epidemiological analysis. The <code>get_episode()</code> function returns the index number of the episode per group, while the <code>is_new_episode()</code> function returns <code>TRUE</code> for every new <code>get_episode()</code> index, and is thus equal to <code>!duplicated(get_episode(...))</code>.</p>
</div>
<div class="section level2">
<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">x</span>, <span class="va">episode_days</span>, <span class="va">...</span><span class="op">)</span></span>
<span></span>
<span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">x</span>, <span class="va">episode_days</span>, <span class="va">...</span><span class="op">)</span></span></code></pre></div>
</div>
<div class="section level2">
<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
<dl><dt>x</dt>
<dd><p>vector of dates (class <code>Date</code> or <code>POSIXt</code>), will be sorted internally to determine episodes</p></dd>
<dt>episode_days</dt>
<dd><p>required episode length in days, can also be less than a day or <code>Inf</code>, see <em>Details</em></p></dd>
<dt>...</dt>
<dd><p>ignored, only in place to allow future extensions</p></dd>
</dl></div>
<div class="section level2">
<h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
<ul><li><p><code>get_episode()</code>: a <a href="https://rdrr.io/r/base/double.html" class="external-link">double</a> vector</p></li>
<li><p><code>is_new_episode()</code>: a <a href="https://rdrr.io/r/base/logical.html" class="external-link">logical</a> vector</p></li>
</ul></div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
<p>Dates are first sorted from old to new. The oldest date will mark the start of the first episode. After this date, the next date will be marked that is at least <code>episode_days</code> days later than the start of the first episode. From that second marked date on, the next date will be marked that is at least <code>episode_days</code> days later than the start of the second episode which will be the start of the third episode, and so on. Before the vector is being returned, the original order will be restored.</p>
<p>The <code><a href="first_isolate.html">first_isolate()</a></code> function is a wrapper around the <code>is_new_episode()</code> function, but is more efficient for data sets containing microorganism codes or names and allows for different isolate selection methods.</p>
<p>The <code>dplyr</code> package is not required for these functions to work, but these episode functions do support <a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">variable grouping</a> and work conveniently inside <code>dplyr</code> verbs such as <code><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise()</a></code>.</p>
</div>
<div class="section level2">
<h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2>
<div class="dont-index"><p><code><a href="first_isolate.html">first_isolate()</a></code></p></div>
</div>
<div class="section level2">
<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># `example_isolates` is a data set available in the AMR package.</span></span></span>
<span class="r-in"><span><span class="co"># See ?example_isolates</span></span></span>
<span class="r-in"><span><span class="va">df</span> <span class="op"><-</span> <span class="va">example_isolates</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/seq.html" class="external-link">seq_len</a></span><span class="op">(</span><span class="fl">2000</span><span class="op">)</span>, size <span class="op">=</span> <span class="fl">100</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># indices</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> [1] 18 31 37 38 34 17 23 19 11 33 12 38 17 4 37 6 47 45 1 31 32 41 23 21 30</span>
<span class="r-out co"><span class="r-pr">#></span> [26] 7 45 43 44 42 6 45 11 42 21 40 9 31 4 26 11 21 19 18 1 36 37 23 41 43</span>
<span class="r-out co"><span class="r-pr">#></span> [51] 39 31 28 18 9 14 20 9 26 2 5 35 45 24 38 15 15 5 33 13 35 25 27 29 16</span>
<span class="r-out co"><span class="r-pr">#></span> [76] 13 47 15 10 45 27 21 32 34 39 18 48 20 3 22 44 17 19 41 40 8 28 7 46 3</span>
<span class="r-in"><span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span> <span class="co"># TRUE/FALSE</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE FALSE</span>
<span class="r-out co"><span class="r-pr">#></span> [13] FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE TRUE TRUE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#></span> [25] TRUE TRUE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#></span> [37] TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#></span> [49] FALSE FALSE TRUE FALSE TRUE FALSE FALSE TRUE TRUE FALSE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#></span> [61] TRUE TRUE FALSE TRUE FALSE TRUE FALSE FALSE FALSE TRUE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#></span> [73] TRUE TRUE TRUE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE</span>
<span class="r-out co"><span class="r-pr">#></span> [85] FALSE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE</span>
<span class="r-out co"><span class="r-pr">#></span> [97] FALSE FALSE TRUE FALSE</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># filter on results from the third 60-day episode only, using base R</span></span></span>
<span class="r-in"><span><span class="va">df</span><span class="op">[</span><span class="fu"><a href="https://rdrr.io/r/base/which.html" class="external-link">which</a></span><span class="op">(</span><span class="fu">get_episode</span><span class="op">(</span><span class="va">df</span><span class="op">$</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span> <span class="op">==</span> <span class="fl">3</span><span class="op">)</span>, <span class="op">]</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 2 × 46</span></span>
<span class="r-out co"><span class="r-pr">#></span> date patient age gender ward mo PEN OXA FLC AMX </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span> <span style="color: #949494; font-style: italic;"><sir></span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> 2003-01-25 088256 73 F ICU B_STPHY_CONS R NA R R </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> 2003-03-18 889500 61 M Clinical B_STPHY_CONS R NA R R </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># … with 36 more variables: AMC <sir>, AMP <sir>, TZP <sir>, CZO <sir>,</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># FEP <sir>, CXM <sir>, FOX <sir>, CTX <sir>, CAZ <sir>, CRO <sir>,</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># GEN <sir>, TOB <sir>, AMK <sir>, KAN <sir>, TMP <sir>, SXT <sir>,</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># NIT <sir>, FOS <sir>, LNZ <sir>, CIP <sir>, MFX <sir>, VAN <sir>,</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># TEC <sir>, TCY <sir>, TGC <sir>, DOX <sir>, ERY <sir>, CLI <sir>,</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># AZM <sir>, IPM <sir>, MEM <sir>, MTR <sir>, CHL <sir>, COL <sir>,</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># MUP <sir>, RIF <sir></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># the functions also work for less than a day, e.g. to include one per hour:</span></span></span>
<span class="r-in"><span><span class="fu">get_episode</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.time</a></span><span class="op">(</span><span class="op">)</span>,</span></span>
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/Sys.time.html" class="external-link">Sys.time</a></span><span class="op">(</span><span class="op">)</span> <span class="op">+</span> <span class="fl">60</span> <span class="op">*</span> <span class="fl">60</span><span class="op">)</span>,</span></span>
<span class="r-in"><span> episode_days <span class="op">=</span> <span class="fl">1</span> <span class="op">/</span> <span class="fl">24</span><span class="op">)</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> [1] 1 2</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># \donttest{</span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="co"># is_new_episode() can also be used in dplyr verbs to determine patient</span></span></span>
<span class="r-in"><span> <span class="co"># episodes based on any (combination of) grouping variables:</span></span></span>
<span class="r-in"><span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>condition <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sample.html" class="external-link">sample</a></span><span class="op">(</span></span></span>
<span class="r-in"><span> x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"A"</span>, <span class="st">"B"</span>, <span class="st">"C"</span><span class="op">)</span>,</span></span>
<span class="r-in"><span> size <span class="op">=</span> <span class="fl">200</span>,</span></span>
<span class="r-in"><span> replace <span class="op">=</span> <span class="cn">TRUE</span></span></span>
<span class="r-in"><span> <span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">condition</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>new_episode <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">date</span>, <span class="va">condition</span>, <span class="va">new_episode</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in mutate(., condition = sample(x = c("A", "B", "C"), size = 200, replace = TRUE)):</span> <span style="color: #00BBBB;">ℹ</span> In argument: `condition = sample(x = c("A", "B", "C"), size = 200,</span>
<span class="r-err co"><span class="r-pr">#></span> replace = TRUE)`.</span>
<span class="r-err co"><span class="r-pr">#></span> <span style="font-weight: bold;">Caused by error:</span></span>
<span class="r-err co"><span class="r-pr">#></span> <span style="color: #BBBB00;">!</span> `condition` must be size 100 or 1, not 200.</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">ward</span>, <span class="va">patient</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/transmute.html" class="external-link">transmute</a></span><span class="op">(</span><span class="va">date</span>,</span></span>
<span class="r-in"><span> <span class="va">patient</span>,</span></span>
<span class="r-in"><span> new_index <span class="op">=</span> <span class="fu">get_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span>,</span></span>
<span class="r-in"><span> new_logical <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">60</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span> </span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/arrange.html" class="external-link">arrange</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">ward</span>, <span class="va">date</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 100 × 5</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: ward, patient [95]</span></span>
<span class="r-out co"><span class="r-pr">#></span> ward date patient new_index new_logical</span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><date></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><dbl></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> Clinical 2007-08-22 005088 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> Clinical 2009-07-24 006827 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> Clinical 2012-11-24 023456 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> Clinical 2013-10-30 066601 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> ICU 2014-06-28 078381 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> ICU 2002-06-04 082413 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> ICU 2014-02-08 082622 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> ICU 2003-01-25 088256 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> Clinical 2008-07-22 0E2483 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> ICU 2007-08-10 0E2483 1 TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># … with 90 more rows</span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">ward</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/summarise.html" class="external-link">summarise</a></span><span class="op">(</span></span></span>
<span class="r-in"><span> n_patients <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/n_distinct.html" class="external-link">n_distinct</a></span><span class="op">(</span><span class="va">patient</span><span class="op">)</span>,</span></span>
<span class="r-in"><span> n_episodes_365 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">365</span><span class="op">)</span><span class="op">)</span>,</span></span>
<span class="r-in"><span> n_episodes_60 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">60</span><span class="op">)</span><span class="op">)</span>,</span></span>
<span class="r-in"><span> n_episodes_30 <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/sum.html" class="external-link">sum</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, episode_days <span class="op">=</span> <span class="fl">30</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 3 × 5</span></span>
<span class="r-out co"><span class="r-pr">#></span> ward n_patients n_episodes_365 n_episodes_60 n_episodes_30</span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span> <span style="color: #949494; font-style: italic;"><int></span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">1</span> Clinical 54 13 34 44</span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">2</span> ICU 34 9 24 28</span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">3</span> Outpatient 7 5 7 7</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># grouping on patients and microorganisms leads to the same</span></span></span>
<span class="r-in"><span><span class="co"># results as first_isolate() when using 'episode-based':</span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> <span class="va">x</span> <span class="op"><-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="first_isolate.html">filter_first_isolate</a></span><span class="op">(</span></span></span>
<span class="r-in"><span> include_unknown <span class="op">=</span> <span class="cn">TRUE</span>,</span></span>
<span class="r-in"><span> method <span class="op">=</span> <span class="st">"episode-based"</span></span></span>
<span class="r-in"><span> <span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="va">y</span> <span class="op"><-</span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">mo</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">ungroup</a></span><span class="op">(</span><span class="op">)</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/identical.html" class="external-link">identical</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> [1] TRUE</span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># but is_new_episode() has a lot more flexibility than first_isolate(),</span></span></span>
<span class="r-in"><span><span class="co"># since you can now group on anything that seems relevant:</span></span></span>
<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
<span class="r-in"><span> </span></span>
<span class="r-in"><span> <span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_by.html" class="external-link">group_by</a></span><span class="op">(</span><span class="va">patient</span>, <span class="va">mo</span>, <span class="va">ward</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html" class="external-link">mutate</a></span><span class="op">(</span>flag_episode <span class="op">=</span> <span class="fu">is_new_episode</span><span class="op">(</span><span class="va">date</span>, <span class="fl">365</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select.html" class="external-link">select</a></span><span class="op">(</span><span class="fu"><a href="https://dplyr.tidyverse.org/reference/group_data.html" class="external-link">group_vars</a></span><span class="op">(</span><span class="va">.</span><span class="op">)</span>, <span class="va">flag_episode</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># A tibble: 100 × 4</span></span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># Groups: patient, mo, ward [97]</span></span>
<span class="r-out co"><span class="r-pr">#></span> patient mo ward flag_episode</span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><mo></span> <span style="color: #949494; font-style: italic;"><chr></span> <span style="color: #949494; font-style: italic;"><lgl></span> </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 1</span> A66134 B_STPHY_AURS Outpatient TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 2</span> 824233 B_STPHY_AURS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 3</span> 078381 B_STPHY_EPDR ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 4</span> 483195 B_STPHY_HMNS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 5</span> B33776 B_ACNTB Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 6</span> 851259 B_STRPT_PNMN Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 7</span> 6F0804 B_STRPT_PNMN Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 8</span> 122506 B_STPHY_AURS Clinical TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;"> 9</span> 904485 B_STRPT ICU TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #BCBCBC;">10</span> 695956 B_STRPT_PNMN Outpatient TRUE </span>
<span class="r-out co"><span class="r-pr">#></span> <span style="color: #949494;"># … with 90 more rows</span></span>
<span class="r-in"><span><span class="co"># }</span></span></span>
</code></pre></div>
</div>
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<p></p><p><code>AMR</code> (for R). Free and open-source, licenced under the <a target="_blank" href="https://github.com/msberends/AMR/blob/main/LICENSE" class="external-link">GNU General Public License version 2.0 (GPL-2)</a>.<br>Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a> in The Netherlands.</p>
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