Ancestor: HL7Connect.Cda.ANY

The quantity datatype is an abstract generalization for all datatypes whose domain values has an order relation (less-or-equal) and where difference is defined in all of the datatype's totally ordered value subsets.

The quantity type abstraction is needed in defining certain other types, such as the interval, and probability distributions

Properties

HL7Connect.Cda.ED expression;
   An expression that can be used to derive the actual value of the quantity given information taken from the context of use.

For example expression can be used for expressing dosage instructions that depend on patient body weight.

If no proper value is provided for the QTY, then the value SHALL have a nullFlavor, whether or not an expression is provided. If no proper value is provided, and an expression is provided, the appropriate nullFlavor is usually DER. No nullFlavor is required if both a proper value and an expression is provided; in such cases, it is up to the processing to determine when the expression should be evaluated.

The language of the expression is inferred from the mediatype. If multiple translations are provided in the expression, the evaluator is free to choose whichever language is preferred; all translations SHALL specify the same outcome.

The language defines the forms that the expression property can take, how the information available in the context of the expression is made available within the features of the language, and how the language declares the new form of the value. Languages may only be used if this information has been appropriately defined for the context in which the QTY is used.

Information Processing Entities are not required to implement any languages in order to claim direct or indirect conformance to this specification, but SHOULD declare what languages are supported in their conformance statements.

Language Mediatype

OCL text/plain+ocl

Factor application/hl7-factor+xml

MathML application/mathml+xml

Note: Factor is an HL7 specific language documented in the Abstract Data Types Specification.

HL7Connect.Cda.ED originalText;
   The text representation from which the QTY was encoded, if such a representation is the source of the QTY.

Original text can be used in a structured user interface to capture what the user saw as a representation of the quantity on the data input screen, or in a situation where the user dictates or directly enters text, it is the text entered or uttered by the user.

It is valid to use a QTY derived datatype to store only the text that the user entered or uttered. In this situation, original text will exist without a valid value. In a situation where the value is determined sometime after the text was entered, originalText is the text or phrase used as the basis for determining the value. The originalText is not a substitute for a valid value. If the actual value of the QTY is not valid, then the QTY SHALL be nullFlavored, irrespective of whether originalText has a value or not.

The original text SHALL be an excerpt of the relevant information in the original sources, rather than a pointer or exact reproduction. Thus the original text SHALL be represented in plain text form. In specific circumstances, when clearly descirbed the context of use, the originalText may be a reference to some other text artefact for which the resolution scope is clearly described.

Note: the details of the link in the originalText.reference between different artifacts of medical information (e.g., document and coded result) is outside the scope of this specification and may be further proscribed in specifications that use this specification.

HL7Connect.Cda.QTY uncertainty;
   The uncertainty of the quantity using a distribution function and its parameters. It is the primary measure of variance/uncertainty of the value (the square root of the sum of the squares of the differences between all data points and the mean). The actual type of uncertainty depends on the type of the QTY and is fixed for each type.

Uncertainty SHALL only be applied to value domains that have a continuous distribution (REAL, PQ, MO, and TS). Uncertainty MAY be applied to the numerator and denominator of a RTO separately.

Uncertainty SHALL not have an expression. Uncertainty SHALL not have uncertainty of its own. Uncertainty SHALL not have originalText - any uncertainty associated with the QTY should be conveyed as part of the originalText of the QTY itself.

Note: uncertainty does not have it's own originalText because it is expected that the uncertainty of the quantity should be expressed in the originalText of the quantity itself.

Tv3UncertaintyType uncertaintyType;
   A code specifying the type of probability distribution in uncertainty.

The null value (unknown) for the type code indicates that the probability distribution type is unknown. In that case, uncertainty has the meaning of an informal guess if it is populated.

If populated, the value of this attribute SHALL be taken from the HL7 DistributionType code system. -- List of possible uncertainty distribution algorithms

utNull

utU : Uniform : The uniform distribution assigns a constant probability over the entire interval of possible outcomes, while all outcomes outside this interval are assumed to have zero probability. The width of this interval is 2 s v3. Thus, the uniform distribution assigns the probability densities f(x) = (2 s v3)-1 to values - s v3 = x = + s v3 and f(x) = 0 otherwise

utN : Normal (Gaussian) : This is the well-known bell-shaped normal distribution. Because of the central limit theorem, the normal distribution is the distribution of choice for an unbounded random variable that is an outcome of a combination of many stochastic processes. Even for values bounded on a single side (i.e. greater than 0) the normal distribution may be accurate enough if the mean is "far away" from the bound of the scale measured in terms of standard deviations

utLN : Log-Normal : The logarithmic normal distribution is used to transform skewed random variable X into a normally distributed random variable U = log X. The log-normal distribution can be specified with the properties mean and standard deviation s. Note however that mean and standard deviation s are the parameters of the raw value distribution, not the transformed parameters of the lognormal distribution that are conventionally referred to by the same letters. Those log-normal parameters log and slog relate to the mean and standard deviation s of the data value through slog2 = log (s2/2 + 1) and log = log - slog2/2

utG : ? (gamma) : The gamma-distribution used for data that is skewed and bounded to the right, i.e. where the maximum of the distribution curve is located near the origin. The ?-distribution has two parameters a and . The relationship to mean and variance s2 is = a and s2 = a 2

utE : Exponential : Used for data that describes extinction. The exponential distribution is a special form of ?-distribution where a = 1, hence, the relationship to mean and variance s2 are = and s2 = 2

utX2 : ? : Used to describe the sum of squares of random variables that occurs when a variance is estimated (rather than presumed) from the sample. The only parameter of the ?2-distribution is ?, so called the number of degrees of freedom (which is the number of independent parts in the sum). The ?2-distribution is a special type of ?-distribution with parameter a = ? /2 and = 2. Hence, = ? and s2 = 2 ?

utT : t (student) : Used to describe the quotient of a normal random variable and the square root of a ?2 random variable. The t-distribution has one parameter ?, the number of degrees of freedom. The relationship to mean and variance s2 are: = 0 and s2 = ? / (? - 2)

utF : F : Used to describe the quotient of two ?2 random variables. The F-distribution has two parameters ?1 and ?2, which are the numbers of degrees of freedom of the numerator and denominator variable respectively. The relationship to mean and variance s2 are: = ?2 / (?2 - 2) and s 2 = (2 ?22 (? 2 + ?1 - 2)) / (?1 (?2 - 2)2 (?2 - 4))

utB : ?(beta) : The beta-distribution is used for data that is bounded on both sides and may or may not be skewed (e.g., occurs when probabilities are estimated.) Two parameters a and are available to adjust the curve. The mean and variance s2 relate as follows: = a / (a + ) and (s2 = a /((a + )2 (a + + 1))

HL7Connect.Cda.IVL uncertainRange;
   Indicates that the value comes from a range of possible values.

uncertainRange is used where the actual value is unknown, but it is known that the value comes from a known range of possible values. uncertainRange differs from uncertainty in that uncertainty is used to report a particular value along with an associated distribution of uncertainty for the value, or to report the summary distribution of a set of data, whereas uncertainRange indicates that there is a single value that, although unknown, comes from a particular range of values. No inference regarding distribution of values can be taken. uncertainRange is often associated with an instruction to perform a particular operation at some point within a given time interval.


Methods


© Kestral Computing P/L 2000 - 2003. HL7Connect v2.00-063 generated on 30-Nov 2015.
Keywords: originalText, expression, uncertainRange, uncertainty, uncertaintyType, QTY, HL7Connect.Cda.QTY