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4.4.1.642 Value Set http://hl7.org/fhir/ValueSet/observation-statistics

Orders and Observations Work Group Maturity Level: 0Informative Use Context: Any

This is a value set defined by the FHIR project.

Summary

Defining URL:http://hl7.org/fhir/ValueSet/observation-statistics
Version:4.1.0
Name:StatisticsCode
Title:StatisticsCode
Definition:

The statistical operation parameter -"statistic" codes.

Committee:Orders and Observations Work Group
OID:2.16.840.1.113883.4.642.3.405 (for OID based terminology systems)
Source ResourceXML / JSON

This value set is used in the following places:

  • CodeSystem: This value set is the designated 'entire code system' value set for StatisticsCode

This value set includes codes from the following code systems:

 

This expansion generated 17 Aug 2019


This value set contains 21 concepts

Expansion based on http://terminology.hl7.org/CodeSystem/observation-statistics version 4.1.0

All codes from system http://terminology.hl7.org/CodeSystem/observation-statistics

CodeDisplayDefinition
averageAverageThe [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements over the stated period.
maximumMaximumThe [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N measurements over the stated period.
minimumMinimumThe [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N measurements over the stated period.
countCountThe [number] of valid measurements over the stated period that contributed to the other statistical outputs.
total-countTotal CountThe total [number] of valid measurements over the stated period, including observations that were ignored because they did not contain valid result values.
medianMedianThe [median](https://en.wikipedia.org/wiki/Median) of N measurements over the stated period.
std-devStandard DeviationThe [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of N measurements over the stated period.
sumSumThe [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the stated period.
varianceVarianceThe [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over the stated period.
20-percent20th PercentileThe 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period.
80-percent80th PercentileThe 80th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period.
4-lowerLower QuartileThe lower [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period.
4-upperUpper QuartileThe upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period.
4-devQuartile 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.
5-11st 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.
5-22nd 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.
5-33rd 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.
5-44th 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.
skewSkewSkewness 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).
kurtosisKurtosisKurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. Source: [Wikipedia](https://en.wikipedia.org/wiki/Kurtosis).
regressionRegressionLinear 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. For value sets, levels are mostly used to organize codes for user convenience, but may follow code system hierarchy - 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