Class: Quantity
A structured object to represent an amount of something (e.g., weight, mass, length, duration of time) - including a value and unit.
URI: crdch:Quantity
Parents
- is_a: Entity - Any resource that has its own identifier
Referenced by class
- Diagnosis ➞age_at_diagnosis 0..1 Quantity
- DimensionalObservation ➞value_quantity 1..1 Quantity
- ExecutionTimeObservation ➞value_quantity 1..1 Quantity
- HistologicalCompositionObservation ➞value_quantity 1..1 Quantity
- Observation ➞value_quantity 0..1 Quantity
- ResearchSubject ➞age_at_enrollment 0..1 Quantity
- SpecimenCreationActivity ➞quantity_collected 0..1 Quantity
- SpecimenProcessingActivity ➞duration 0..* Quantity
- SpecimenQualityObservation ➞value_quantity 1..1 Quantity
- SpecimenQuantityObservation ➞value_quantity 1..1 Quantity
- SpecimenStorageActivity ➞duration 0..1 Quantity
- Specimen ➞distance_from_paired_specimen 0..1 Quantity
- Subject ➞age_at_death 0..1 Quantity
- Substance ➞substance_quantity 0..1 Quantity
- TimePoint ➞offset_from_index 0..1 Quantity
Attributes
Own
- value_decimal 0..1
- Description: An amount, in the given units (if specified)
- Range: CrdchDecimal
- value_codeable_concept 0..1
- Description: A coded value representing a quantity (e.g. "Adjacent (< or = 2cm)")
- Range: CodeableConcept
- unit 0..1
- Description: A coded or free text (in the .text field) representation of the unit.
- Range: CodeableConcept
Other properties
Comments: | QuantityMeasure' may be implemented as an Observation-like object that will let us capture any type of measure of the amount of some substance (e.g. weight, volume, maybe even concentration?), with distinct timestamps and methods associated. It could be implemented as a "simple" observation (one measurement per instance, where the 'code' fields is bound to a value set describing the different types of quantity measures allowed - e.g. 'weight', 'volume', 'concentration'), or as "composite" observation (multiple measurements possible in a single instance, each captured as a component defined to hold a specific type of quantity measure - e.g. 'weight', 'volume', 'concentration'). The number of different quantity measures we anticipate needed to support, and the potential for data sparseness, are factors that determine whether a simple or composite Observation would be most appropriate. |