R4 Ballot #1 (Mixed Normative/Trial use)

This page is part of the FHIR Specification (v3.3.0: R4 Ballot 2). The current version which supercedes this version is 5.0.0. For a full list of available versions, see the Directory of published versions . Page versions: R5 R4B R4 R3

4.2.13.406 Code System http://hl7.org/fhir/observation-statistics

Vocabulary Work Group Maturity Level: 0Informative Use Context: Any

This is a code system defined by the FHIR project.

Summary

Defining URL:http://hl7.org/fhir/observation-statistics
Name:StatisticsCode
Definition:

The statistical operation parameter -"statistic" codes

Committee:??
OID:2.16.840.1.113883.4.642.1.406 (for OID based terminology systems)
Source ResourceXML / JSON

This Code system is used in the following value sets:

  • StatisticsCode (The statistical operation parameter -"statistic" codes)

The statistical operation parameter -"statistic" codes

This code system http://hl7.org/fhir/observation-statistics defines the following codes:

CodeDisplayDefinition
average AverageThe [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements over the stated period
maximum MaximumThe [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N measurements over the stated period
minimum MinimumThe [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N measurements over the stated period
count CountThe [number] of valid measurements over the stated period that contributed to the other statistical outputs
totalcount Total CountThe total [number] of valid measurements over the stated period, including observations that were ignored because they did not contain valid result values
median MedianThe [median](https://en.wikipedia.org/wiki/Median) of N measurements over the stated period
std-dev Standard DeviationThe [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of N measurements over the stated period
sum SumThe [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the stated period
variance VarianceThe [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over the stated period
20-percent 20th PercentileThe 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period
80-percent 80th PercentileThe 80th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period
4-lower Lower QuartileThe lower [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period
4-upper Upper QuartileThe upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period
4-dev Quartile DeviationThe 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.
5-1 1st QuintileThe 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
5-2 2nd QuintileThe 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
5-3 3rd QuintileThe 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
5-4 4th QuintileThe 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
skew SkewSkewness 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)
kurtosis KurtosisKurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. Source: [Wikipedia](https://en.wikipedia.org/wiki/Kurtosis)
regression RegressionLinear 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.

 

See the full registry of value sets defined as part of FHIR.


Explanation of the columns that may appear on this page:

LvlA few code lists that FHIR defines are hierarchical - each code is assigned a level. See Code System for further information.
SourceThe source of the definition of the code (when the value set draws in codes defined elsewhere)
CodeThe code (used as the code in the resource instance). If the code is in italics, this indicates that the code is not selectable ('Abstract')
DisplayThe display (used in the display element of a Coding). If there is no display, implementers should not simply display the code, but map the concept into their application
DefinitionAn explanation of the meaning of the concept
CommentsAdditional notes about how to use the code