2.2. Retrieve MedMij Core - Blood pressure (zib2017/STU3)

A unique identifier assigned to this observation.

Allows observations to be distinguished and referenced.

A plan, proposal or order that is fulfilled in whole or in part by this event.

Allows tracing of authorization for the event and tracking whether proposals/recommendations were acted upon.

References SHALL be a reference to an actual FHIR resource, and SHALL be resolveable (allowing for access control, temporary unavailability, etc). Resolution can be either by retrieval from the URL, or, where applicable by resource type, by treating an absolute reference as a canonical URL and looking it up in a local registry/repository.

The status of the result value.

Need to track the status of individual results. Some results are finalized before the whole report is finalized.

This element is labeled as a modifier because the status contains codes that mark the resource as not currently valid.

A code that classifies the general type of observation being made.

Used for filtering what observations are retrieved and displayed.

In addition to the required category valueset, this element allows various categorization schemes based on the owner’s definition of the category and effectively multiple categories can be used at once. The level of granularity is defined by the category concepts in the value set.

The patient, or group of patients, location, or device whose characteristics (direct or indirect) are described by the observation and into whose record the observation is placed. Comments: Indirect characteristics may be those of a specimen, fetus, donor, other observer (for example a relative or EMT), or any observation made about the subject.

Observations have no value if you don't know who or what they're about.

One would expect this element to be a cardinality of 1..1. The only circumstance in which the subject can be missing is when the observation is made by a device that does not know the patient. In this case, the observation SHALL be matched to a patient through some context/channel matching technique, and at this point, the observation should be updated.

If the target of the observation is different than the subject, the general extension observation-focal-subject. may be used. However, the distinction between the patient's own value for an observation versus that of the fetus, or the donor or blood product unit, etc., are often specified in the observation code.

The healthcare event (e.g. a patient and healthcare provider interaction) during which this observation is made.

For some observations it may be important to know the link between an observation and a particular encounter.

This will typically be the encounter the event occurred within, but some events may be initiated prior to or after the official completion of an encounter or episode but still be tied to the context of the encounter or episode (e.g. pre-admission lab tests).

The date and time this observation was made available to providers, typically after the results have been reviewed and verified.

Updated when the result is updated.

Optional Extension Element - found in all resources.

There can be no stigma associated with the use of extensions by any application, project, or standard - regardless of the institution or jurisdiction that uses or defines the extensions. The use of extensions is what allows the FHIR specification to retain a core level of simplicity for everyone.

A reference to a location at which the other resource is found. The reference may be a relative reference, in which case it is relative to the service base URL, or an absolute URL that resolves to the location where the resource is found. The reference may be version specific or not. If the reference is not to a FHIR RESTful server, then it should be assumed to be version specific. Internal fragment references (start with '#') refer to contained resources.

Using absolute URLs provides a stable scalable approach suitable for a cloud/web context, while using relative/logical references provides a flexible approach suitable for use when trading across closed eco-system boundaries. Absolute URLs do not need to point to a FHIR RESTful server, though this is the preferred approach. If the URL conforms to the structure "/[type]/[id]" then it should be assumed that the reference is to a FHIR RESTful server.

An identifier for the other resource. This is used when there is no way to reference the other resource directly, either because the entity is not available through a FHIR server, or because there is no way for the author of the resource to convert a known identifier to an actual location. There is no requirement that a Reference.identifier point to something that is actually exposed as a FHIR instance, but it SHALL point to a business concept that would be expected to be exposed as a FHIR instance, and that instance would need to be of a FHIR resource type allowed by the reference.

When an identifier is provided in place of a reference, any system processing the reference will only be able to resolve the identifier to a reference if it understands the business context in which the identifier is used. Sometimes this is global (e.g. a national identifier) but often it is not. For this reason, none of the useful mechanisms described for working with references (e.g. chaining, includes) are possible, nor should servers be expected to be able resolve the reference. Servers may accept an identifier based reference untouched, resolve it, and/or reject it - see CapabilityStatement.rest.resource.referencePolicy.

When both an identifier and a literal reference are provided, the literal reference is preferred. Applications processing the resource are allowed - but not required - to check that the identifier matches the literal reference

Applications converting a logical reference to a literal reference may choose to leave the logical reference present, or remove it.

Plain text narrative that identifies the resource in addition to the resource reference.

This is generally not the same as the Resource.text of the referenced resource. The purpose is to identify what's being referenced, not to fully describe it.

The value of the measured amount. The value includes an implicit precision in the presentation of the value.

Precision is handled implicitly in almost all cases of measurement.

The implicit precision in the value should always be honored. Monetary values have their own rules for handling precision (refer to standard accounting text books).

How the value should be understood and represented - whether the actual value is greater or less than the stated value due to measurement issues; e.g. if the comparator is "<" , then the real value is < stated value.

Need a framework for handling measures where the value is <5ug/L or >400mg/L due to the limitations of measuring methodology.

This is labeled as "Is Modifier" because the comparator modifies the interpretation of the value significantly. If there is no comparator, then there is no modification of the value.

If there is no comparator, then there is no modification of the value

A human-readable form of the unit.

There are many representations for units of measure and in many contexts, particular representations are fixed and required. I.e. mcg for micrograms.

Note that FHIR strings may not exceed 1MB in size

The identification of the system that provides the coded form of the unit.

Need to know the system that defines the coded form of the unit.

see http://en.wikipedia.org/wiki/Uniform_resource_identifier

Coded responses from the common UCUM units for vital signs value set.

Need a computable form of the unit that is fixed across all forms. UCUM provides this for quantities, but SNOMED CT provides many units of interest.

The preferred system is UCUM, but SNOMED CT can also be used (for customary units) or ISO 4217 for currency. The context of use may additionally require a code from a particular system.

Provides a reason why the expected value in the element Observation.value[x] is missing.

For many results it is necessary to handle exceptional values in measurements.

Null or exceptional values can be represented two ways in FHIR Observations. One way is to simply include them in the value set and represent the exceptions in the value. For example, measurement values for a serology test could be "detected", "not detected", "inconclusive", or "specimen unsatisfactory". The alternate way is to use the value element for actual observations and use the explicit dataAbsentReason element to record exceptional values. For example, the dataAbsentReason code "error" could be used when the measurement was not completed. Note that an observation may only be reported if there are values to report. For example differential cell counts values may be reported only when > 0. Because of these options, use-case agreements are required to interpret general observations for null or exceptional values.

The assessment made based on the result of the observation. Intended as a simple compact code often placed adjacent to the result value in reports and flow sheets to signal the meaning/normalcy status of the result. Otherwise known as abnormal flag.

For some results, particularly numeric results, an interpretation is necessary to fully understand the significance of a result.

Not all terminology uses fit this general pattern. In some cases, models should not use CodeableConcept and use Coding directly and provide their own structure for managing text, codings, translations and the relationship between elements and pre- and post-coordination.

The specimen that was used when this observation was made.

Should only be used if not implicit in code found in Observation.code. Observations are not made on specimens themselves; they are made on a subject, but in many cases by the means of a specimen. Note that although specimens are often involved, they are not always tracked and reported explicitly. Also note that observation resources may be used in contexts that track the specimen explicitly (e.g. Diagnostic Report).

The device used to generate the observation data.

An extension should be used if further typing of the device is needed. Devices used to support obtaining an observation can be represented using either an extension or through the Observation.related element.

The value of the low bound of the reference range. The low bound of the reference range endpoint is inclusive of the value (e.g. reference range is >=5 - <=9). If the low bound is omitted, it is assumed to be meaningless (e.g. reference range is <=2.3).

The context of use may frequently define what kind of quantity this is and therefore what kind of units can be used. The context of use may also restrict the values for the comparator.

The value of the high bound of the reference range. The high bound of the reference range endpoint is inclusive of the value (e.g. reference range is >=5 - <=9). If the high bound is omitted, it is assumed to be meaningless (e.g. reference range is >= 2.3).

The context of use may frequently define what kind of quantity this is and therefore what kind of units can be used. The context of use may also restrict the values for the comparator.

Codes to indicate the what part of the targeted reference population it applies to. For example, the normal or therapeutic range.

Need to be able to say what kind of reference range this is - normal, recommended, therapeutic, etc, - for proper interpretation.

This SHOULD be populated if there is more than one range. If this element is not present then the normal range is assumed.

Codes to indicate the target population this reference range applies to. For example, a reference range may be based on the normal population or a particular sex or race.

Need to be able to identify the target population for proper interpretation.

This SHOULD be populated if there is more than one range. If this element is not present then the normal population is assumed.

The age at which this reference range is applicable. This is a neonatal age (e.g. number of weeks at term) if the meaning says so.

Some analytes vary greatly over age.

The stated low and high value are assumed to have arbitrarily high precision when it comes to determining which values are in the range. I.e. 1.99 is not in the range 2 -> 3.

Text based reference range in an observation which may be used when a quantitative range is not appropriate for an observation. An example would be a reference value of "Negative" or a list or table of 'normals'.

Note that FHIR strings may not exceed 1MB in size

A code specifying the kind of relationship that exists with the target resource.

A relationship type SHOULD be provided.

The "derived-from" type is the only logical choice when referencing the QuestionnaireAnswer resource.

A reference to the observation or QuestionnaireResponse resource that is related to this observation.

References SHALL be a reference to an actual FHIR resource, and SHALL be resolveable (allowing for access control, temporary unavailability, etc). Resolution can be either by retrieval from the URL, or, where applicable by resource type, by treating an absolute reference as a canonical URL and looking it up in a local registry/repository.

Describes what was observed. Sometimes this is called the observation "code".

Knowing what kind of observation is being made is essential to understanding the observation.

Not all terminology uses fit this general pattern. In some cases, models should not use CodeableConcept and use Coding directly and provide their own structure for managing text, codings, translations and the relationship between elements and pre- and post-coordination.

Provides a reason why the expected value in the element Observation.value[x] is missing.

For many results it is necessary to handle exceptional values in measurements.

"Null" or exceptional values can be represented two ways in FHIR Observations. One way is to simply include them in the value set and represent the exceptions in the value. For example, measurement values for a serology test could be "detected", "not detected", "inconclusive", or "test not done". The alternate way is to use the value element for actual observations and use the explicit dataAbsentReason element to record exceptional values. For example, the dataAbsentReason code "error" could be used when the measurement was not completed. Because of these options, use-case agreements are required to interpret general observations for exceptional values.

The assessment made based on the result of the observation. Intended as a simple compact code often placed adjacent to the result value in reports and flow sheets to signal the meaning/normalcy status of the result. Otherwise known as abnormal flag.

For some results, particularly numeric results, an interpretation is necessary to fully understand the significance of a result.

The component interpretation applies only to the individual component value. For an overall interpretation all components together use thes Observation.interpretation element.

Guidance on how to interpret the value by comparison to a normal or recommended range.

Knowing what values are considered "normal" can help evaluate the significance of a particular result. Need to be able to provide multiple reference ranges for different contexts.

Most observations only have one generic reference range. Systems MAY choose to restrict to only supplying the relevant reference range based on knowledge about the patient (e.g., specific to the patient's age, gender, weight and other factors), but this may not be possible or appropriate. Whenever more than one reference range is supplied, the differences between them SHOULD be provided in the reference range and/or age properties.

Provides a reason why the expected value in the element Observation.value[x] is missing.

For many results it is necessary to handle exceptional values in measurements.

"Null" or exceptional values can be represented two ways in FHIR Observations. One way is to simply include them in the value set and represent the exceptions in the value. For example, measurement values for a serology test could be "detected", "not detected", "inconclusive", or "test not done". The alternate way is to use the value element for actual observations and use the explicit dataAbsentReason element to record exceptional values. For example, the dataAbsentReason code "error" could be used when the measurement was not completed. Because of these options, use-case agreements are required to interpret general observations for exceptional values.

The assessment made based on the result of the observation. Intended as a simple compact code often placed adjacent to the result value in reports and flow sheets to signal the meaning/normalcy status of the result. Otherwise known as abnormal flag.

For some results, particularly numeric results, an interpretation is necessary to fully understand the significance of a result.

The component interpretation applies only to the individual component value. For an overall interpretation all components together use thes Observation.interpretation element.

Guidance on how to interpret the value by comparison to a normal or recommended range.

Knowing what values are considered "normal" can help evaluate the significance of a particular result. Need to be able to provide multiple reference ranges for different contexts.

Most observations only have one generic reference range. Systems MAY choose to restrict to only supplying the relevant reference range based on knowledge about the patient (e.g., specific to the patient's age, gender, weight and other factors), but this may not be possible or appropriate. Whenever more than one reference range is supplied, the differences between them SHOULD be provided in the reference range and/or age properties.

Provides a reason why the expected value in the element Observation.value[x] is missing.

For many results it is necessary to handle exceptional values in measurements.

"Null" or exceptional values can be represented two ways in FHIR Observations. One way is to simply include them in the value set and represent the exceptions in the value. For example, measurement values for a serology test could be "detected", "not detected", "inconclusive", or "test not done". The alternate way is to use the value element for actual observations and use the explicit dataAbsentReason element to record exceptional values. For example, the dataAbsentReason code "error" could be used when the measurement was not completed. Because of these options, use-case agreements are required to interpret general observations for exceptional values.

The assessment made based on the result of the observation. Intended as a simple compact code often placed adjacent to the result value in reports and flow sheets to signal the meaning/normalcy status of the result. Otherwise known as abnormal flag.

For some results, particularly numeric results, an interpretation is necessary to fully understand the significance of a result.

The component interpretation applies only to the individual component value. For an overall interpretation all components together use thes Observation.interpretation element.

Guidance on how to interpret the value by comparison to a normal or recommended range.

Knowing what values are considered "normal" can help evaluate the significance of a particular result. Need to be able to provide multiple reference ranges for different contexts.

Most observations only have one generic reference range. Systems MAY choose to restrict to only supplying the relevant reference range based on knowledge about the patient (e.g., specific to the patient's age, gender, weight and other factors), but this may not be possible or appropriate. Whenever more than one reference range is supplied, the differences between them SHOULD be provided in the reference range and/or age properties.