Measurements and simple assertions made about a patient, device or other subject.

Observations are a key aspect of healthcare. This resource is used to capture those that do not require more sophisticated mechanisms.

Used for simple observations such as device measurements, laboratory atomic results, vital signs, height, weight, smoking status, comments, etc. Other resources are used to provide context for observations such as Lab reports, etc.

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.

The information determined as a result of making the observation, if the information has a simple value.

An observation exists to have a value, though it may not if it is in error, or it represents a group of observations.

Normally, an observation will have either a value or a set of related observations. A few observations (e.g. apgar store) may have both a value and related observations (for apgar, the observations from which the measure is derived). If a value is present, the datatype for this element should be determined by Observation.code. A CodeableConcept with just a text would be used instead of a string if the field was usually coded, or if the type associated with the Observation.code defines a coded value. For boolean values use valueCodeableConcept and select codes from <http://hl7.org/fhir/v2/vs/0136> (These "yes/no" concepts can be mapped to the display name "true/false" or other mutually exclusive terms that may be needed"). The element, Observation.value[x], has a variable name depending on the type as follows: valueQuantity, valueCodeableConcept, valueRatio, valueChoice, valuePeriod, valueSampleData, or valueString (The name format is "'value' + the type name" with a capital on the first letter of the type).

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.

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

May include statements about significant, unexpected or unreliable values, or information about the source of the value where this may be relevant to the interpretation of the result.

Need to be able to provide free text additional information.

The time or time-period the observed value is asserted as being true. For biological subjects - e.g. human patients - this is usually called the "physiologically relevant time". This is usually either the time of the procedure or of specimen collection, but very often the source of the date/time is not known, only the date/time itself.

Knowing when an observation was deemed true is important to its relevance as well as determining trends.

At least a date should be present unless this observation is a historical report.

The date and time this observation was made available.

Updated when the result is updated.

The status of the result value.

Need to track the status of individual results - some results are finalised before the whole report is finalised.

An estimate of the degree to which quality issues have impacted on the value reported.

Not all results are completely reliable, and some are still reported anyway.

Note that in most contexts, unreliable results are not recorded, deleted, or otherwise excluded, but it's not always possible to exclude them from the record. If the reliability indicator is present, interpreters of a result, whether human or machine, should always either be aware of the status or prevented from using the observation without being unaware that the reliability is not "ok".

Indicates the site on the subject's body where the observation was made ( i.e. the target site).

Knowing where the observation is made is important for tracking if multiple sites are possible.

Only used if not implicit in code found in Observation.code.

Indicates the mechanism used to perform the observation.

In some cases, method can impact results and is thus for determining whether results can be compared or determining significance of results.

Only used if not implicit in code for Observation.code.

A unique identifier for the simple observation.

Allows observations to be distinguished and referenced.

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, 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 (http://hl7.org/fhir/StructureDefinition/indirectTarget) can be used.

The specimen that was used when this observation was made.

Observations are not made on specimens themselves; they are made on a subject, but usually 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 are often used in contexts that track the specimen explicitly (e.g. Diagnostic Report).

Who was responsible for asserting the observed value as "true".

May give a degree of confidence in the observation and also indicates where follow-up questions should be directed.

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 extension or through the Observation.related element.

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.

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.

The value of the low bound of the reference range. If this element is omitted, the low bound of the reference range is assumed to be meaningless. (e.g. reference range is <2.3) If the low.comparator element is missing, it is assumed to be '>'.

The value of the high bound of the reference range. If this element is omitted, the high bound of the reference range is assumed to be meaningless. (e.g. reference range is > 5) If the low.comparator element is missing , it is assumed to be '<'.

Code for the meaning of the reference range.

Need to be able to say what kind of reference range this is - normal, recommended, therapeutic, or perhaps what state this reference range applies to (i.e. age, hormonal cycles, etc.).

This SHOULD be populated if there is more than one range.

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.

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'.

Related observations - either components, or previous observations, or statements of derivation.

Some observations have important relationships to other observations (e.g Blood Pressure = systolic + diastolic), or are derived from other observations (e.g. calculated apgar score).

Normally, an observation will have either a value or a set of related observations. A few observations (e.g. apgar store) may have both a value and related observations (for apgar, the observations from which the measure is derived).

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

May need to indicate whether this observation is composed of others, or merely derived from them.

A relationship type SHOULD be provided. If the relationship type is "COMP" (composed), then the observation should not be displayed/interpreted in the absence of the related observations.

A reference to the observation that is related to this observation.