FHIR Cross-Version Extensions package for FHIR R4 from FHIR R3 - Version 0.0.1-snapshot-2. See the Directory of published versions
| Official URL: http://hl7.org/fhir/3.0/ValueSet/R3-observation-statistics-for-R4 | Version: 0.0.1-snapshot-2 | |||
| Standards status: Informative | Maturity Level: 0 | Computable Name: R3_observation_statistics_for_R4 | ||
| This cross-version ValueSet represents concepts from http://hl7.org/fhir/ValueSet/observation-statistics | 3.0.2 for use in FHIR R4. Concepts not present here have direct equivalent mappings crossing all versions from R3 to R4. |
References
This value set is not used here; it may be used elsewhere (e.g. specifications and/or implementations that use this content)
http://hl7.org/fhir/observation-statistics version 3.0.2| Code | Display | Definition |
| average | Average | The [mean](https://en.wikipedia.org/wiki/Arithmetic_mean) of N measurements over the stated period |
| maximum | Maximum | The [maximum](https://en.wikipedia.org/wiki/Maximal_element) value of N measurements over the stated period |
| minimum | Minimum | The [minimum](https://en.wikipedia.org/wiki/Minimal_element) value of N measurements over the stated period |
| count | Count | The [number] of valid measurements over the stated period that contributed to the other statistical outputs |
| totalcount | 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 |
| median | Median | The [median](https://en.wikipedia.org/wiki/Median) of N measurements over the stated period |
| std-dev | Standard Deviation | The [standard deviation](https://en.wikipedia.org/wiki/Standard_deviation) of N measurements over the stated period |
| sum | Sum | The [sum](https://en.wikipedia.org/wiki/Summation) of N measurements over the stated period |
| variance | Variance | The [variance](https://en.wikipedia.org/wiki/Variance) of N measurements over the stated period |
| 20-percent | 20th Percentile | The 20th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period |
| 80-percent | 80th Percentile | The 80th [Percentile](https://en.wikipedia.org/wiki/Percentile) of N measurements over the stated period |
| 4-lower | Lower Quartile | The lower [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period |
| 4-upper | Upper Quartile | The upper [Quartile](https://en.wikipedia.org/wiki/Quartile) Boundary of N measurements over the stated period |
| 4-dev | Quartile Deviation | 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. |
| 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 |
| 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 |
| 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 |
| 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 |
| 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](https://en.wikipedia.org/wiki/Skewness) |
| kurtosis | Kurtosis | 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) |
| 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](https://en.wikipedia.org/wiki/Simple_linear_regression) This Statistic code will return both a gradient and an intercept value. |
This value set expansion contains 21 concepts.
| Code | System | Display | Definition |
| average | http://hl7.org/fhir/observation-statistics | Average | The mean of N measurements over the stated period |
| maximum | http://hl7.org/fhir/observation-statistics | Maximum | The maximum value of N measurements over the stated period |
| minimum | http://hl7.org/fhir/observation-statistics | Minimum | The minimum value of N measurements over the stated period |
| count | http://hl7.org/fhir/observation-statistics | Count | The [number] of valid measurements over the stated period that contributed to the other statistical outputs |
| totalcount | http://hl7.org/fhir/observation-statistics | 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 |
| median | http://hl7.org/fhir/observation-statistics | Median | The median of N measurements over the stated period |
| std-dev | http://hl7.org/fhir/observation-statistics | Standard Deviation | The standard deviation of N measurements over the stated period |
| sum | http://hl7.org/fhir/observation-statistics | Sum | The sum of N measurements over the stated period |
| variance | http://hl7.org/fhir/observation-statistics | Variance | The variance of N measurements over the stated period |
| 20-percent | http://hl7.org/fhir/observation-statistics | 20th Percentile | The 20th Percentile of N measurements over the stated period |
| 80-percent | http://hl7.org/fhir/observation-statistics | 80th Percentile | The 80th Percentile of N measurements over the stated period |
| 4-lower | http://hl7.org/fhir/observation-statistics | Lower Quartile | The lower Quartile Boundary of N measurements over the stated period |
| 4-upper | http://hl7.org/fhir/observation-statistics | Upper Quartile | The upper Quartile Boundary of N measurements over the stated period |
| 4-dev | http://hl7.org/fhir/observation-statistics | 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. |
| 5-1 | http://hl7.org/fhir/observation-statistics | 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 |
| 5-2 | http://hl7.org/fhir/observation-statistics | 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 |
| 5-3 | http://hl7.org/fhir/observation-statistics | 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 |
| 5-4 | http://hl7.org/fhir/observation-statistics | 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 |
| skew | http://hl7.org/fhir/observation-statistics | 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 |
| kurtosis | http://hl7.org/fhir/observation-statistics | Kurtosis | Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. Source: Wikipedia |
| regression | http://hl7.org/fhir/observation-statistics | 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. |
Explanation of the columns that may appear on this page:
| Level | A few code lists that FHIR defines are hierarchical - each code is assigned a level. In this scheme, some codes are under other codes, and imply that the code they are under also applies |
| System | The source of the definition of the code (when the value set draws in codes defined elsewhere) |
| Code | The code (used as the code in the resource instance) |
| Display | The 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 |
| Definition | An explanation of the meaning of the concept |
| Comments | Additional notes about how to use the code |