FQL is a query language that allows you to retrieve, filter and project data from any data source containing FHIR Resources. It brings the power of three existing languages together: SQL, JSON and FhirPath. It allows you to create tables and is useful for gaining insight and perform quality control.
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Default
What is FQL?
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FQL Query resources
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- FQL Documentation
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FQL Language
Syntax specification
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YamlGen Generate resources
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YamlGen Language
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FHIRPath Inspect resource
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FHIRPath Documentation
FHIRPath Documentation
Find out what FHIRPath is or learn how to write FHIRPath scripts.
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Project FHIR API
This is the location where you can find your resource using a FHIR client.
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Simplifier FHIR API
The global endpoint is where users can search for all resources in Simplifier. Resources have a globally unique guid Id here.
Observation Statistics
The Statistics operation performs a set of statistical calculations on a set of clinical measurements such as a blood pressure as stored on the server. This operation is focused on Observation resources with valueQuantity elements that have UCUM unit codes.
The set of Observations is defined by 4 parameters:
- the subject of the observations for which the statistics are being generated (
subject
) - which observations to generate statistics for (
code
andsystem
, orcoding
) - the time period over which to generate statistics
'duration
orperiod
) - the set of statistical analyses to return (
statistic
)
Possible statistical analyses (see StatisticsCode):
- average ("Average"): The mean of N measurements over the stated period
- maximum ("Maximum"): The maximum value of N measurements over the stated period
- minimum ("Minimum"): The minimum 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 of N measurements over the stated period
- std-dev ("Standard Deviation"): The standard deviation of N measurements over the stated period
- sum ("Sum"): The sum of N measurements over the stated period
- variance ("Variance"): The variance of N measurements over the stated period
- 20-percent ("20th Percentile"): The 20th Percentile of N measurements over the stated period
- 80-percent ("80th Percentile"): The 80th Percentile of N measurements over the stated period
- 4-lower ("Lower Quartile"): The lower Quartile Boundary of N measurements over the stated period
- 4-upper ("Upper Quartile"): The upper Quartile Boundary of N measurements over the stated period
- 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.
- 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
- kurtosis ("Kurtosis"): Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable. Source: Wikipedia
- 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.
If successful, the operation returns an Observation resource for each code with the results of the statistical calculations as component value pairs where the component code = the statistical code. The Observation also contains the input parameters patient
,code
and duration
parameters. If unsuccessful, an OperationOutcome with an error message will be returned.
The client can request that all the observations on which the statistics are based be returned as well, using the include parameter. If an include parameter is specified, a limit may also be specified; the sources observations are subsetted at the server's discretion if count > limit. This functionality is included with the intent of supporting graphical presentation
- type OperationDefinition
- FHIR STU3
- status Maturity Level 0
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versionnone
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