Hierarchy
Presentation
Care sites
This dataset is useful to link AP-HP's care sites of various levels together
To generate it, it uses the fact_relationship
OMOP table, with the care_site
domain and the A is part of B
relation. Thus, it generates a wide-type table, effectively flattening out the hierarchical structure of each care site.
This dataset is useful to find the parent of a care_site, e.g.:
- in which hospital is this UDS (Unité De Soin) ?
- in which UF (Unité Fonctionnelle) is this UMA (Unité Médico-Administrative) ?
Structure and usage
In this dataset each row corresponds to a given care_site
and the columns contain
the ids of the parent care_site
for several hierarchical level. Those columns are thus values contained in care_site_type_source_value
.
Internally, the dataset is returned by calling the function get_care_site_hierarchy()
:
from eds_scikit.resources import registry
df = registry.get("data", function_name="get_care_site_hierarchy")()
Use your own data.
It is as simple as registering a new loading function:
from eds_scikit.resources import registry # (1)
@registry.data("get_care_site_hierarchy") # (2)
def get_care_site_hierarchy():
"""
Your code here
"""
return df
- The
registry
instance stores user-defined functions - Using this decorator allows to register the function when importing the corresponding file
Then simply import your custom_resources
module before running eds-scikit's pipelines, and you're good to go.
Structure and usage
Internally, the dataset is returned by calling the function get_care_site_hierarchy()
.
It should return a Pandas Dataframe with the following columns:
care_site_id
(OMOP column): The identifier of the care sitecare_site_type_source_value
(OMOP column): The type of care site
Additionally, it can contains an arbitrary number of columns whose name are values from care_site_type_source_value
, and whose values are care_site_id
of the corresponding parent structure
Generation function
You can generate the dataset on your specific data using this function