HL7 Terminology (THO)
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HL7 Terminology (THO), published by HL7 International - Vocabulary Work Group. This guide is not an authorized publication; it is the continuous build for version 5.5.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7/UTG/ and changes regularly. See the Directory of published versions

: StatisticsCode - XML Representation

Draft as of 2020-04-09

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<CodeSystem xmlns="http://hl7.org/fhir">
  <id value="observation-statistics"/>
  <meta>
    <lastUpdated value="2020-04-09T21:10:28.568+00:00"/>
  </meta>
  <text>
    <status value="generated"/>
    <div xmlns="http://www.w3.org/1999/xhtml"><p>This case-sensitive code system <code>http://terminology.hl7.org/CodeSystem/observation-statistics</code> defines the following codes:</p><table class="codes"><tr><td style="white-space:nowrap"><b>Code</b></td><td><b>Display</b></td><td><b>Definition</b></td></tr><tr><td style="white-space:nowrap">average<a name="observation-statistics-average"> </a></td><td>Average</td><td><div><p>The <a href="https://en.wikipedia.org/wiki/Arithmetic_mean">mean</a> of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">maximum<a name="observation-statistics-maximum"> </a></td><td>Maximum</td><td><div><p>The <a href="https://en.wikipedia.org/wiki/Maximal_element">maximum</a> value of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">minimum<a name="observation-statistics-minimum"> </a></td><td>Minimum</td><td><div><p>The <a href="https://en.wikipedia.org/wiki/Minimal_element">minimum</a> value of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">count<a name="observation-statistics-count"> </a></td><td>Count</td><td><div><p>The [number] of valid measurements over the stated period that contributed to the other statistical outputs.</p>
</div></td></tr><tr><td style="white-space:nowrap">total-count<a name="observation-statistics-total-count"> </a></td><td>Total Count</td><td><div><p>The total [number] of valid measurements over the stated period, including observations that were ignored because they did not contain valid result values.</p>
</div></td></tr><tr><td style="white-space:nowrap">median<a name="observation-statistics-median"> </a></td><td>Median</td><td><div><p>The <a href="https://en.wikipedia.org/wiki/Median">median</a> of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">std-dev<a name="observation-statistics-std-dev"> </a></td><td>Standard Deviation</td><td><div><p>The <a href="https://en.wikipedia.org/wiki/Standard_deviation">standard deviation</a> of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">sum<a name="observation-statistics-sum"> </a></td><td>Sum</td><td><div><p>The <a href="https://en.wikipedia.org/wiki/Summation">sum</a> of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">variance<a name="observation-statistics-variance"> </a></td><td>Variance</td><td><div><p>The <a href="https://en.wikipedia.org/wiki/Variance">variance</a> of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">20-percent<a name="observation-statistics-20-percent"> </a></td><td>20th Percentile</td><td><div><p>The 20th <a href="https://en.wikipedia.org/wiki/Percentile">Percentile</a> of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">80-percent<a name="observation-statistics-80-percent"> </a></td><td>80th Percentile</td><td><div><p>The 80th <a href="https://en.wikipedia.org/wiki/Percentile">Percentile</a> of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">4-lower<a name="observation-statistics-4-lower"> </a></td><td>Lower Quartile</td><td><div><p>The lower <a href="https://en.wikipedia.org/wiki/Quartile">Quartile</a> Boundary of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">4-upper<a name="observation-statistics-4-upper"> </a></td><td>Upper Quartile</td><td><div><p>The upper <a href="https://en.wikipedia.org/wiki/Quartile">Quartile</a> Boundary of N measurements over the stated period.</p>
</div></td></tr><tr><td style="white-space:nowrap">4-dev<a name="observation-statistics-4-dev"> </a></td><td>Quartile Deviation</td><td><div><p>The difference between the upper and lower <a href="https://en.wikipedia.org/wiki/Quartile">Quartiles</a> is called the Interquartile range. (IQR = Q3-Q1) Quartile deviation or Semi-interquartile range is one-half the difference between the first and the third quartiles.</p>
</div></td></tr><tr><td style="white-space:nowrap">5-1<a name="observation-statistics-5-1"> </a></td><td>1st Quintile</td><td><div><p>The lowest of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population.</p>
</div></td></tr><tr><td style="white-space:nowrap">5-2<a name="observation-statistics-5-2"> </a></td><td>2nd Quintile</td><td><div><p>The second of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population.</p>
</div></td></tr><tr><td style="white-space:nowrap">5-3<a name="observation-statistics-5-3"> </a></td><td>3rd Quintile</td><td><div><p>The third of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population.</p>
</div></td></tr><tr><td style="white-space:nowrap">5-4<a name="observation-statistics-5-4"> </a></td><td>4th Quintile</td><td><div><p>The fourth of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population.</p>
</div></td></tr><tr><td style="white-space:nowrap">skew<a name="observation-statistics-skew"> </a></td><td>Skew</td><td><div><p>Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. The skewness value can be positive or negative, or even undefined.  Source: <a href="https://en.wikipedia.org/wiki/Skewness">Wikipedia</a>.</p>
</div></td></tr><tr><td style="white-space:nowrap">kurtosis<a name="observation-statistics-kurtosis"> </a></td><td>Kurtosis</td><td><div><p>Kurtosis  is a measure of the &quot;tailedness&quot; of the probability distribution of a real-valued random variable.   Source: <a href="https://en.wikipedia.org/wiki/Kurtosis">Wikipedia</a>.</p>
</div></td></tr><tr><td style="white-space:nowrap">regression<a name="observation-statistics-regression"> </a></td><td>Regression</td><td><div><p>Linear regression is an approach for modeling two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variables. Source: <a href="https://en.wikipedia.org/wiki/Simple_linear_regression">Wikipedia</a>  This Statistic code will return both a gradient and an intercept value.</p>
</div></td></tr></table></div>
  </text>
  <url value="http://terminology.hl7.org/CodeSystem/observation-statistics"/>
  <identifier>
    <system value="urn:ietf:rfc:3986"/>
    <value value="urn:oid:2.16.840.1.113883.4.642.1.1126"/>
  </identifier>
  <version value="1.0.0"/>
  <name value="StatisticsCode"/>
  <title value="StatisticsCode"/>
  <status value="draft"/>
  <experimental value="false"/>
  <date value="2020-04-09T21:10:28+00:00"/>
  <publisher value="Health Level Seven International"/>
  <contact>
    <telecom>
      <system value="url"/>
      <value value="http://hl7.org"/>
    </telecom>
    <telecom>
      <system value="email"/>
      <value value="hq@HL7.org"/>
    </telecom>
  </contact>
  <description
               value="The statistical operation parameter -&quot;statistic&quot; codes."/>
  <copyright
             value="This material derives from the HL7 Terminology (THO). THO is copyright ©1989+ Health Level Seven International and is made available under the CC0 designation. For more licensing information see: https://terminology.hl7.org/license"/>
  <caseSensitive value="true"/>
  <valueSet
            value="http://terminology.hl7.org/ValueSet/observation-statistics"/>
  <content value="complete"/>
  <concept>
    <code value="average"/>
    <display value="Average"/>
    <definition
                value="The [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="maximum"/>
    <display value="Maximum"/>
    <definition
                value="The [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="minimum"/>
    <display value="Minimum"/>
    <definition
                value="The [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="count"/>
    <display value="Count"/>
    <definition
                value="The [number] of valid measurements over the stated period that contributed to the other statistical outputs."/>
  </concept>
  <concept>
    <code value="total-count"/>
    <display value="Total Count"/>
    <definition
                value="The total [number] of valid measurements over the stated period, including observations that were ignored because they did not contain valid result values."/>
  </concept>
  <concept>
    <code value="median"/>
    <display value="Median"/>
    <definition
                value="The [median](https://en.wikipedia.org/wiki/Median) of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="std-dev"/>
    <display value="Standard Deviation"/>
    <definition
                value="The [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="sum"/>
    <display value="Sum"/>
    <definition
                value="The [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="variance"/>
    <display value="Variance"/>
    <definition
                value="The [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="20-percent"/>
    <display value="20th Percentile"/>
    <definition
                value="The 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="80-percent"/>
    <display value="80th Percentile"/>
    <definition
                value="The 80th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="4-lower"/>
    <display value="Lower Quartile"/>
    <definition
                value="The lower [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="4-upper"/>
    <display value="Upper Quartile"/>
    <definition
                value="The upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period."/>
  </concept>
  <concept>
    <code value="4-dev"/>
    <display value="Quartile Deviation"/>
    <definition
                value="The difference between the upper and lower [Quartiles](https://en.wikipedia.org/wiki/Quartile) is called the Interquartile range. (IQR = Q3-Q1) Quartile deviation or Semi-interquartile range is one-half the difference between the first and the third quartiles."/>
  </concept>
  <concept>
    <code value="5-1"/>
    <display value="1st Quintile"/>
    <definition
                value="The lowest of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population."/>
  </concept>
  <concept>
    <code value="5-2"/>
    <display value="2nd Quintile"/>
    <definition
                value="The second of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population."/>
  </concept>
  <concept>
    <code value="5-3"/>
    <display value="3rd Quintile"/>
    <definition
                value="The third of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population."/>
  </concept>
  <concept>
    <code value="5-4"/>
    <display value="4th Quintile"/>
    <definition
                value="The fourth of four values that divide the N measurements into a frequency distribution of five classes with each containing one fifth of the total population."/>
  </concept>
  <concept>
    <code value="skew"/>
    <display value="Skew"/>
    <definition
                value="Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. The skewness value can be positive or negative, or even undefined.  Source: [Wikipedia](https://en.wikipedia.org/wiki/Skewness)."/>
  </concept>
  <concept>
    <code value="kurtosis"/>
    <display value="Kurtosis"/>
    <definition
                value="Kurtosis  is a measure of the &quot;tailedness&quot; of the probability distribution of a real-valued random variable.   Source: [Wikipedia](https://en.wikipedia.org/wiki/Kurtosis)."/>
  </concept>
  <concept>
    <code value="regression"/>
    <display value="Regression"/>
    <definition
                value="Linear regression is an approach for modeling two-dimensional sample points with one independent variable and one dependent variable (conventionally, the x and y coordinates in a Cartesian coordinate system) and finds a linear function (a non-vertical straight line) that, as accurately as possible, predicts the dependent variable values as a function of the independent variables. Source: [Wikipedia](https://en.wikipedia.org/wiki/Simple_linear_regression)  This Statistic code will return both a gradient and an intercept value."/>
  </concept>
</CodeSystem>