This page is part of the Logica COVID-19 FHIR Profile Library IG (v1.0.0: Informative - Informative) based on FHIR R4. This is the current published version in its permanent home (it will always be available at this URL). For a full list of available versions, see the Directory of published versions
The following profile is for recording/transmitting data associated with COVID-19 signs and symptoms. This list of signs and symptoms is not comprehensive. It will be added to as we receive information from contributing partners.
The profile is based on the Observation resource where the code (Observation.code) is bound to the list of signs and symptoms and the value is bound to a list of presence/absence findings (present, absent, unknown).
The following are profiles to record/transmit any COVID-19 associated diagnoses; one for using SNOMED CT codes and one for using ICD 10 codes.
This profile was created as a means of capturing whether an underlying condition is present or absent. There are several slices of the component of Observation, each being a category of underlying conditions. Each component also has an extension for the category code as well as an extension to be a reference to the corresponding Condition, if it exists or needs to be instantiated.
Note The profile below is a specialization of the FHIR Observation resource and is used to capture the presence or absence of an underlying condition in a specific category. This is accomplished by using the Observation.component element as follows:
- component.code = the specific SNOMED CT code for the condition being stated as present or absent
- component.value = present, absent, or unknown
There are two extensions used in each slice of component, ConditionCategoryCode and ConditionReference.
- ConditionCategoryCode is used to identify the categorical group of the underlying condition.
- ConditionReference is a pointer to a data instance of the underlying condition (stored as a Condition), if it exists or needs to be instantiated.
COVID-19 Underlying Medical Condition observation
These profiles are used to capture underlying problems that would be on a problem list or tracked/monitored underlying conditions. These are specific to identified categories, i.e. underlying cardiovascular conditions. This list will grow over time as more categories are identified. The value sets for these profiles will also grow over time as we receive feedback and input from users and interested parties.
COVID-19 General underlying condition
COVID-19 cardiovascular underlying condition
COVID-19 neurologic underlying condition
COVID-19 immunocompromised underlying condition
COVID-19 respiratory underlying condition
COVID-19 metabolic underlying condition
COVID-19 hemoglobinopathy underlying condition
COVID-19 renal underlying condition
COVID-19 immune underlying condition