Social Status[source]
The eds.social_status pipeline component extracts mentions of the social status.
Details of the used patterns
# fmt: off
from ..utils import make_assign_regex, make_status_assign, normalize_space_characters
healthy = dict(
source="healthy",
regex=[
"aidante? principale?",
"soutien familiale?",
"bien entouree?",
],
regex_attr="NORM",
)
healthy_orth = dict(
source="healthy_orth",
regex=[
r"\btravaille\b",
],
regex_attr="ORTH",
)
severe = dict(
source="severe",
regex=[
r"soins? de nursing",
r"tut(elles?|eur|rice)",
r"curat(?:elle|eur|rice)",
"mandataire professionnel",
"usld",
"sauvegarde de justice",
"maison de retraite",
"protection juridique",
r"intitution(nalisee?)?",
r"\bmadd\b",
],
regex_attr="NORM",
)
altered = dict(
source="altered",
regex=[
r"\bapa\b",
"peu entouree?",
],
regex_attr="NORM",
)
mild = dict(
source="mild",
regex=[
r"residence (autonomie|senior)",
"foyer logement",
],
)
severe_potential_fp = dict(
source="severe_potential_fp",
regex=[
"ehpad",
],
regex_attr="NORM",
exclude=dict(regex=["equipe"], window=(-2, 2)),
)
severe_orth = dict(
source="severe_orth",
regex=[
r"\bEPHAD\b",
],
regex_attr="ORTH",
)
house_stay = dict(
source="other_stay",
regex=["maintien au? domicile", r"\bmad\b"],
regex_attr="NORM",
assign=dict(
name="severe",
regex=make_assign_regex(["difficile", "difficulte"]),
window=(-2, 2),
),
)
isolation = dict(
source="altered_isolation",
regex=[
r"isole(e?|ment)",
],
exclude=[
dict(regex=["progression"], window=(-5, 5)),
dict(regex=[r"\besa\b", "nodule", "hepatomegalie"], window=(-5, 5)),
dict(regex=["contact", "bmr"], window=(-5, 5)),
],
regex_attr="NORM",
)
other = dict(
source="other",
regex=[
"habitation familiale",
r"aide[\s-]menagere",
r"aides? au? domicile",
r"aux(iliaires?)? de vie",
r"\badv\b",
"bilan social",
"evaluation sociale",
"(?:sur le )?plan social",
r"vit seule?",
r"vivait seule?",
"activite professionnelle",
],
regex_attr="NORM",
)
HEALTHY_FAMILY_COMPLEMENTS = ["vit avec", "presente?s?"]
ALTERED_FAMILY_COMPLEMENTS = [
"decedee?s?",
"morte?s?",
"deces",
r"ne(?: se)? voit (?:plus|pas)",
r"ne(?: se)? parle (?:plus|pas)",
"conflit",
]
family_members = dict(
source="other_family",
regex=[
r"\bmari\b",
"femme",
r"epou(?:x|se)",
r"\bcompagn(?:e|on)",
"concubine?",
],
regex_attr="NORM",
assign=[
dict(
name="healthy_family",
regex=make_assign_regex(HEALTHY_FAMILY_COMPLEMENTS),
window=(-3, 4),
),
dict(
name="altered_family",
regex=make_assign_regex(ALTERED_FAMILY_COMPLEMENTS),
window=(-3, 4),
),
],
include=dict(
regex=make_assign_regex(
HEALTHY_FAMILY_COMPLEMENTS + ALTERED_FAMILY_COMPLEMENTS
),
window=(-3, 4),
),
exclude=dict(
regex=["resorbables?", "ablation", r"chirurgi(?:e|cal|caux)", "admission"],
window=(-4, 4),
),
)
children = dict(
source="healthy_children",
regex=[
r"(\d+ ?)?(?:petits?[\s-]?)?fils",
r"(\d+ ?)?garcons?",
r"(\d+ ?)?(?:petites?[\s-]?)?filles?",
r"(\d+ ?)?(?:petits?[\s-]?)?enfants?",
],
assign=dict(
name="healthy_children",
regex=make_assign_regex(HEALTHY_FAMILY_COMPLEMENTS),
window=(-3, 4),
required=True,
),
exclude=dict(
regex=["resorbables?", "ablation", r"chirurgi(?:e|cal|caux)", "admission"],
window=(-4, 4),
),
)
ambiguous_family = dict(
source="other_ambiguous_family",
regex=[
"famille",
r"(\d+ ?)?\bfreres?",
r"(\d+ ?)?\bsoeurs?",
],
regex_attr="NORM",
assign=[
dict(
name="healthy_family",
regex=make_assign_regex(HEALTHY_FAMILY_COMPLEMENTS),
window=(-3, 4),
),
dict(
name="altered_family",
regex=make_assign_regex(ALTERED_FAMILY_COMPLEMENTS),
window=(-3, 4),
),
],
exclude=dict(
regex=["resorbables?", "ablation", r"chirurgi(?:e|cal|caux)", "admission"],
window=(-4, 4),
),
include=dict(
regex=make_assign_regex(
HEALTHY_FAMILY_COMPLEMENTS + ALTERED_FAMILY_COMPLEMENTS
),
window=(-3, 4),
),
)
status = dict(
source="other_status",
regex=["etat social", "statut social"],
regex_attr="NORM",
assign=make_status_assign(),
)
default_patterns = normalize_space_characters(
[
healthy,
healthy_orth,
altered,
severe_orth,
isolation,
severe,
mild,
other,
family_members,
children,
ambiguous_family,
house_stay,
severe_potential_fp,
status,
]
)
# fmt: on
Extensions
On each span span that match, the following attribute is available:
span._.social_status: set to None.
It will specify the severity of the mention regarding the social status of the patient.
Possible values are:
healthy: this span suggests the patient is well regarding that domain.altered_nondescript: this span suggests the patient is not well, but it is not yet possible to ascertain the degree of alteration.altered_mild: this span suggests a light alteration regarding this domain.altered_severe: this span suggests a severe alteration regarding this domain.other: this span is not indicative of the level of alteration regarding this domain. Still, it hints that this domain has been evaluated.
Examples
import edsnlp, edsnlp.pipes as eds
nlp = edsnlp.blank("eds")
nlp.add_pipe(eds.sentences())
nlp.add_pipe(eds.normalizer())
nlp.add_pipe(f"eds.social_status")
Below are a few examples:
Parameters
| PARAMETER | DESCRIPTION |
|---|---|
nlp | The pipeline TYPE: |
name | The name of the component TYPE: |
patterns | The patterns to use for matching TYPE: |
label | The label to use for the TYPE: |
span_setter | How to set matches on the doc TYPE: |