Codesystem-observation-statistics.xml

Definition for Code System StatisticsCode

<?xml version="1.0" encoding="UTF-8"?>

<CodeSystem xmlns="http://hl7.org/fhir">
  <id value="observation-statistics"/> 
  <meta> 
    <lastUpdated value="2021-04-15T12:25:09.461+10:00"/> 
    <profile value="http://hl7.org/fhir/StructureDefinition/shareablecodesystem"/> 
  </meta> 
  <text> 
    <status value="generated"/> 
    <div xmlns="http://www.w3.org/1999/xhtml">
      <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> The [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements over the stated
             period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">maximum
            <a name="observation-statistics-maximum"> </a> 
          </td> 
          <td> Maximum</td> 
          <td> The [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N measurements over
             the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">minimum
            <a name="observation-statistics-minimum"> </a> 
          </td> 
          <td> Minimum</td> 
          <td> The [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N measurements over
             the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">count
            <a name="observation-statistics-count"> </a> 
          </td> 
          <td> Count</td> 
          <td> The [number] of valid measurements over the stated period that contributed to the other
             statistical outputs.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">total-count
            <a name="observation-statistics-total-count"> </a> 
          </td> 
          <td> Total Count</td> 
          <td> The total [number] of valid measurements over the stated period, including observations
             that were ignored because they did not contain valid result values.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">median
            <a name="observation-statistics-median"> </a> 
          </td> 
          <td> Median</td> 
          <td> The [median](https://en.wikipedia.org/wiki/Median) of N measurements over the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">std-dev
            <a name="observation-statistics-std-dev"> </a> 
          </td> 
          <td> Standard Deviation</td> 
          <td> The [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of N measurements
             over the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">sum
            <a name="observation-statistics-sum"> </a> 
          </td> 
          <td> Sum</td> 
          <td> The [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">variance
            <a name="observation-statistics-variance"> </a> 
          </td> 
          <td> Variance</td> 
          <td> The [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over the stated
             period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">20-percent
            <a name="observation-statistics-20-percent"> </a> 
          </td> 
          <td> 20th Percentile</td> 
          <td> The 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over
             the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">80-percent
            <a name="observation-statistics-80-percent"> </a> 
          </td> 
          <td> 80th Percentile</td> 
          <td> The 80th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over
             the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">4-lower
            <a name="observation-statistics-4-lower"> </a> 
          </td> 
          <td> Lower Quartile</td> 
          <td> The lower [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements
             over the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">4-upper
            <a name="observation-statistics-4-upper"> </a> 
          </td> 
          <td> Upper Quartile</td> 
          <td> The upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements
             over the stated period.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">4-dev
            <a name="observation-statistics-4-dev"> </a> 
          </td> 
          <td> Quartile Deviation</td> 
          <td> 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.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">5-1
            <a name="observation-statistics-5-1"> </a> 
          </td> 
          <td> 1st Quintile</td> 
          <td> 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.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">5-2
            <a name="observation-statistics-5-2"> </a> 
          </td> 
          <td> 2nd Quintile</td> 
          <td> 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.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">5-3
            <a name="observation-statistics-5-3"> </a> 
          </td> 
          <td> 3rd Quintile</td> 
          <td> 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.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">5-4
            <a name="observation-statistics-5-4"> </a> 
          </td> 
          <td> 4th Quintile</td> 
          <td> 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.</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">skew
            <a name="observation-statistics-skew"> </a> 
          </td> 
          <td> Skew</td> 
          <td> 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).</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">kurtosis
            <a name="observation-statistics-kurtosis"> </a> 
          </td> 
          <td> Kurtosis</td> 
          <td> 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).</td> 
        </tr> 
        <tr> 
          <td style="white-space:nowrap">regression
            <a name="observation-statistics-regression"> </a> 
          </td> 
          <td> Regression</td> 
          <td> 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.</td> 
        </tr> 
      </table> 
    </div> 
  </text> 
  <extension url="http://hl7.org/fhir/StructureDefinition/structuredefinition-wg">
    <valueCode value="oo"/> 
  </extension> 
  <url value="http://hl7.org/fhir/observation-statistics"/> 
  <identifier> 
    <system value="urn:ietf:rfc:3986"/> 
    <value value="urn:oid:2.16.840.1.113883.4.642.1.406"/> 
  </identifier> 
  <version value="4.6.0"/> 
  <name value="StatisticsCode"/> 
  <caseSensitive value="true"/> 
  <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>