Extensions for Using Data Elements from FHIR R5 in FHIR R4
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Extensions for Using Data Elements from FHIR R5 in FHIR R4 - Downloaded Version null See the Directory of published versions

ValueSet: R5StatisticTypeForR4

Official URL: http://hl7.org/fhir/uv/xver/ValueSet/R5-statistic-type-for-R4 Version: 0.1.0
Standards status: Trial-use Maturity Level: 1 Responsible: Clinical Decision Support Computable Name: R5StatisticTypeForR4

This cross-version ValueSet represents content from http://hl7.org/fhir/ValueSet/statistic-type|5.0.0 for use in FHIR R4.

This value set is part of the cross-version definitions generated to enable use of the value set http://hl7.org/fhir/ValueSet/statistic-type|5.0.0 as defined in FHIR R5 in FHIR R4.

The source value set is bound to the following FHIR R5 elements:

  • Evidence.statistic.statisticType as Extensible

Across FHIR versions, the value set has been mapped as:

  • http://hl7.org/fhir/ValueSet/statistic-type|5.0.0
  • http://hl7.org/fhir/ValueSet/statistic-type|4.3.0

Note that all concepts are included in this cross-version definition because no concepts have compatible representations

Following are the generation technical comments: All concepts in the comparison are listed as identical. The source and target value sets have the same number of active concepts (22). FHIR ValueSet http://hl7.org/fhir/ValueSet/statistic-type|5.0.0, defined in FHIR R5 does not have any mapping to FHIR R4

References

Logical Definition (CLD)

  • Include these codes as defined in http://terminology.hl7.org/CodeSystem/statistic-type version 📍0.1.0
    CodeDisplayDefinition
    0000100Standardized Mean DifferenceComputed by forming the difference between two means, divided by an estimate of the within-group standard deviation. It is used to provide an estimatation of the effect size between two treatments when the predictor (independent variable) is categorical and the response(dependent) variable is continuous.
    0000301CovarianceThe strength of correlation between a set (2 or more) of random variables. The covariance is obtained by forming: cov(x,y)=e([x-e(x)][y-e(y)] where e(x), e(y) is the expected value (mean) of variable x and y respectively. Covariance is symmetric so cov(x,y)=cov(y,x). The covariance is usefull when looking at the variance of the sum of the 2 random variables since: var(x+y) = var(x) +var(y) +2cov(x,y) the covariance cov(x,y) is used to obtain the coefficient of correlation cor(x,y) by normalizing (dividing) cov(x,y) but the product of the standard deviations of x and y.
    0000424Risk DifferenceDifference between the observed risks (proportions of individuals with the outcome of interest) in the two groups. The risk difference is straightforward to interpret: it describes the actual difference in the observed risk of events between experimental and control interventions.
    0000457Mean DifferenceThe mean difference, or difference in means, measures the absolute difference between the mean value in two different groups.
    0000565Regression CoefficientGenerated by a type of data transformation called a regression, which aims to model a response variable by expression the predictor variables as part of a function where variable terms are modified by a number. A regression coefficient is one such number.
    C16726IncidenceThe relative frequency of occurrence of something.
    C16932Odds RatioThe ratio of the odds of an event occurring in one group to the odds of it occurring in another group, or to a sample-based estimate of that ratio.
    C17010PrevalenceThe ratio (for a given time period) of the number of occurrences of a disease or event to the number of units at risk in the population.
    C25463CountThe number or amount of something.
    C25564MaximumThe largest possible quantity or degree.
    C25570MinimumThe smallest possible quantity.
    C28007MedianThe value which has an equal number of values greater and less than it.
    C44256ProportionQuotient of quantities of the same kind for different components within the same system. [Use for univariate outcomes within an individual.].
    C53319MeanThe sum of a set of values divided by the number of values in the set.
    C65171Spearman Rank-Order CorrelationA distribution-free analog of correlation analysis. Like regression, it can be applied to compare two independent random variables, each at several levels (which may be discrete or continuous). Unlike regression, Spearman's rank correlation works on ranked (relative) data, rather than directly on the data itself.
    C65172Pearson Correlation CoefficientA measure of the correlation of two variables X and Y measured on the same object or organism, that is, a measure of the tendency of the variables to increase or decrease together. It is defined as the sum of the products of the standard scores of the two measures divided by the degrees of freedom.
    C93150Hazard RatioA measure of how often a particular event happens in one group compared to how often it happens in another group, over time. In cancer research, hazard ratios are often used in clinical trials to measure survival at any point in time in a group of patients who have been given a specific treatment compared to a control group given another treatment or a placebo. A hazard ratio of one means that there is no difference in survival between the two groups. A hazard ratio of greater than one or less than one means that survival was better in one of the groups.
    C93152Relative RiskA measure of the risk of a certain event happening in one group compared to the risk of the same event happening in another group. In cancer research, risk ratios are used in prospective (forward looking) studies, such as cohort studies and clinical trials. A risk ratio of one means there is no difference between two groups in terms of their risk of cancer, based on whether or not they were exposed to a certain substance or factor, or how they responded to two treatments being compared. A risk ratio of greater than one or of less than one usually means that being exposed to a certain substance or factor either increases (risk ratio greater than one) or decreases (risk ratio less than one) the risk of cancer, or that the treatments being compared do not have the same effects.
    absolute-MedianDiffAbsolute Median DifferenceComputed by forming the difference between two medians.
    descriptiveDescriptiveDescriptive measure reported as narrative.
    predictedRiskPredicted RiskA special use case where the proportion is derived from a formula rather than derived from summary evidence.
    rate-ratioIncidence Rate RatioA type of relative effect estimate that compares rates over time (eg events per person-years).

 

Expansion

This value set expansion contains 22 concepts.

SystemVersionCodeDisplayDefinitionJSONXML
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  0000100Standardized Mean DifferenceComputed by forming the difference between two means, divided by an estimate of the within-group standard deviation. It is used to provide an estimatation of the effect size between two treatments when the predictor (independent variable) is categorical and the response(dependent) variable is continuous.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  0000301CovarianceThe strength of correlation between a set (2 or more) of random variables. The covariance is obtained by forming: cov(x,y)=e([x-e(x)][y-e(y)] where e(x), e(y) is the expected value (mean) of variable x and y respectively. Covariance is symmetric so cov(x,y)=cov(y,x). The covariance is usefull when looking at the variance of the sum of the 2 random variables since: var(x+y) = var(x) +var(y) +2cov(x,y) the covariance cov(x,y) is used to obtain the coefficient of correlation cor(x,y) by normalizing (dividing) cov(x,y) but the product of the standard deviations of x and y.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  0000424Risk DifferenceDifference between the observed risks (proportions of individuals with the outcome of interest) in the two groups. The risk difference is straightforward to interpret: it describes the actual difference in the observed risk of events between experimental and control interventions.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  0000457Mean DifferenceThe mean difference, or difference in means, measures the absolute difference between the mean value in two different groups.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  0000565Regression CoefficientGenerated by a type of data transformation called a regression, which aims to model a response variable by expression the predictor variables as part of a function where variable terms are modified by a number. A regression coefficient is one such number.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C16726IncidenceThe relative frequency of occurrence of something.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C16932Odds RatioThe ratio of the odds of an event occurring in one group to the odds of it occurring in another group, or to a sample-based estimate of that ratio.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C17010PrevalenceThe ratio (for a given time period) of the number of occurrences of a disease or event to the number of units at risk in the population.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C25463CountThe number or amount of something.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C25564MaximumThe largest possible quantity or degree.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C25570MinimumThe smallest possible quantity.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C28007MedianThe value which has an equal number of values greater and less than it.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C44256ProportionQuotient of quantities of the same kind for different components within the same system. [Use for univariate outcomes within an individual.].
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C53319MeanThe sum of a set of values divided by the number of values in the set.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C65171Spearman Rank-Order CorrelationA distribution-free analog of correlation analysis. Like regression, it can be applied to compare two independent random variables, each at several levels (which may be discrete or continuous). Unlike regression, Spearman's rank correlation works on ranked (relative) data, rather than directly on the data itself.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C65172Pearson Correlation CoefficientA measure of the correlation of two variables X and Y measured on the same object or organism, that is, a measure of the tendency of the variables to increase or decrease together. It is defined as the sum of the products of the standard scores of the two measures divided by the degrees of freedom.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C93150Hazard RatioA measure of how often a particular event happens in one group compared to how often it happens in another group, over time. In cancer research, hazard ratios are often used in clinical trials to measure survival at any point in time in a group of patients who have been given a specific treatment compared to a control group given another treatment or a placebo. A hazard ratio of one means that there is no difference in survival between the two groups. A hazard ratio of greater than one or less than one means that survival was better in one of the groups.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  C93152Relative RiskA measure of the risk of a certain event happening in one group compared to the risk of the same event happening in another group. In cancer research, risk ratios are used in prospective (forward looking) studies, such as cohort studies and clinical trials. A risk ratio of one means there is no difference between two groups in terms of their risk of cancer, based on whether or not they were exposed to a certain substance or factor, or how they responded to two treatments being compared. A risk ratio of greater than one or of less than one usually means that being exposed to a certain substance or factor either increases (risk ratio greater than one) or decreases (risk ratio less than one) the risk of cancer, or that the treatments being compared do not have the same effects.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  absolute-MedianDiffAbsolute Median DifferenceComputed by forming the difference between two medians.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  descriptiveDescriptiveDescriptive measure reported as narrative.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  predictedRiskPredicted RiskA special use case where the proportion is derived from a formula rather than derived from summary evidence.
http://terminology.hl7.org/CodeSystem/statistic-type0.1.0  rate-ratioIncidence Rate RatioA type of relative effect estimate that compares rates over time (eg events per person-years).

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