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
• Treatment ➞treatment_dose _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.