{"caseSensitive":true,"concept":[{"code":"average","definition":"The [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements over the stated period.","display":"Average"},{"code":"maximum","definition":"The [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N measurements over the stated period.","display":"Maximum"},{"code":"minimum","definition":"The [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N measurements over the stated period.","display":"Minimum"},{"code":"count","definition":"The [number] of valid measurements over the stated period that contributed to the other statistical outputs.","display":"Count"},{"code":"total-count","definition":"The total [number] of valid measurements over the stated period, including observations that were ignored because they did not contain valid result values.","display":"Total Count"},{"code":"median","definition":"The [median](https://en.wikipedia.org/wiki/Median) of N measurements over the stated period.","display":"Median"},{"code":"std-dev","definition":"The [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of N measurements over the stated period.","display":"Standard Deviation"},{"code":"sum","definition":"The [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the stated period.","display":"Sum"},{"code":"variance","definition":"The [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over the stated period.","display":"Variance"},{"code":"20-percent","definition":"The 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period.","display":"20th Percentile"},{"code":"80-percent","definition":"The 80th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period.","display":"80th Percentile"},{"code":"4-lower","definition":"The lower [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period.","display":"Lower Quartile"},{"code":"4-upper","definition":"The upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period.","display":"Upper Quartile"},{"code":"4-dev","definition":"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.","display":"Quartile Deviation"},{"code":"5-1","definition":"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.","display":"1st Quintile"},{"code":"5-2","definition":"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.","display":"2nd Quintile"},{"code":"5-3","definition":"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.","display":"3rd Quintile"},{"code":"5-4","definition":"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.","display":"4th Quintile"},{"code":"skew","definition":"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).","display":"Skew"},{"code":"kurtosis","definition":"Kurtosis is a measure of the \"tailedness\" of the probability distribution of a real-valued random variable. Source: [Wikipedia](https://en.wikipedia.org/wiki/Kurtosis).","display":"Kurtosis"},{"code":"regression","definition":"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.","display":"Regression"}],"contact":[{"telecom":[{"system":"url","value":"http://hl7.org/fhir"},{"system":"email","value":"fhir@lists.hl7.org"}]}],"content":"complete","date":"2022-12-01T09:29:23+11:00","description":"The statistical operation parameter -\"statistic\" codes.","experimental":false,"extension":[{"url":"http://hl7.org/fhir/StructureDefinition/structuredefinition-wg","valueCode":"oo"}],"id":"observation-statistics","identifier":[{"system":"urn:ietf:rfc:3986","value":"urn:oid:2.16.840.1.113883.4.642.1.1126"},{"system":"urn:ietf:rfc:3986","use":"old","value":"urn:oid:2.16.840.1.113883.4.642.1.395"}],"jurisdiction":[{"coding":[{"code":"001","display":"World","system":"http://unstats.un.org/unsd/methods/m49/m49.htm"}]}],"meta":{"lastUpdated":"2026-03-31T18:55:04.283+00:00"},"name":"StatisticsCode","publisher":"HL7 (FHIR Project)","resourceType":"CodeSystem","status":"active","text":{"div":"

Generated Narrative: CodeSystem observation-statistics

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

CodeDisplayDefinition
average Average

The mean of N measurements over the stated period.

\n
maximum Maximum

The maximum value of N measurements over the stated period.

\n
minimum Minimum

The minimum value of N measurements over the stated period.

\n
count Count

The [number] of valid measurements over the stated period that contributed to the other statistical outputs.

\n
total-count Total Count

The total [number] of valid measurements over the stated period, including observations that were ignored because they did not contain valid result values.

\n
median Median

The median of N measurements over the stated period.

\n
std-dev Standard Deviation

The standard deviation of N measurements over the stated period.

\n
sum Sum

The sum of N measurements over the stated period.

\n
variance Variance

The variance of N measurements over the stated period.

\n
20-percent 20th Percentile

The 20th Percentile of N measurements over the stated period.

\n
80-percent 80th Percentile

The 80th Percentile of N measurements over the stated period.

\n
4-lower Lower Quartile

The lower Quartile Boundary of N measurements over the stated period.

\n
4-upper Upper Quartile

The upper Quartile Boundary of N measurements over the stated period.

\n
4-dev Quartile Deviation

The difference between the upper and lower Quartiles 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.

\n
5-1 1st Quintile

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.

\n
5-2 2nd Quintile

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.

\n
5-3 3rd Quintile

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.

\n
5-4 4th Quintile

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.

\n
skew Skew

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.

\n
kurtosis Kurtosis

Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. Source: Wikipedia.

\n
regression Regression

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 This Statistic code will return both a gradient and an intercept value.

\n
","status":"generated"},"title":"Statistics Code","url":"http://hl7.org/fhir/observation-statistics","valueSet":"http://hl7.org/fhir/ValueSet/observation-statistics","version":"6.0.0-ballot4"}