696 lines
22 KiB
Python
696 lines
22 KiB
Python
"""
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Tests unitaires pour le PMSIValidator.
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Ces tests vérifient:
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- La génération de problèmes de validation catégorisés
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- La détection d'informations obligatoires manquantes
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- La validation de conformité aux critères d'éligibilité
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- La détection d'erreurs zéro-tolérance
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- La logique de blocage de validation automatique
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"""
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from datetime import datetime
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from unittest.mock import MagicMock, Mock
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import pytest
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from pipeline_mco_pmsi.models.clinical import (
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ClinicalDocument,
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ClinicalFact,
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Evidence,
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Qualifier,
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Span,
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StructuredStay,
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)
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from pipeline_mco_pmsi.models.coding import Code, CodingProposal
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from pipeline_mco_pmsi.models.metadata import ModelVersion
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from pipeline_mco_pmsi.models.validation import EligibilityCriteria
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from pipeline_mco_pmsi.validators.pmsi_validator import PMSIValidator
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@pytest.fixture
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def mock_rag_engine():
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"""Crée un mock du RAG Engine."""
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return MagicMock()
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@pytest.fixture
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def pmsi_validator(mock_rag_engine):
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"""Crée une instance de PMSIValidator avec un RAG Engine mocké."""
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return PMSIValidator(rag_engine=mock_rag_engine)
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@pytest.fixture
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def sample_document():
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"""Crée un document clinique de test."""
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return ClinicalDocument(
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document_id="doc_001",
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document_type="cr_medical",
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content="Patient présente une gastrite aiguë confirmée par endoscopie.",
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creation_date=datetime(2024, 1, 15, 10, 30),
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author="Dr. Martin",
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priority=2,
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)
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@pytest.fixture
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def sample_evidence():
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"""Crée une preuve de test."""
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return Evidence(
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document_id="doc_001",
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span=Span(start=20, end=35),
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text="gastrite aiguë",
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context="Patient présente une gastrite aiguë confirmée",
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)
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@pytest.fixture
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def sample_code(sample_evidence):
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"""Crée un code de test."""
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return Code(
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code="K29.1",
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label="Gastrite aiguë",
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type="dp",
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evidence=[sample_evidence],
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confidence=0.85,
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reasoning="Diagnostic principal confirmé par endoscopie",
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referentiel_version="2026",
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)
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@pytest.fixture
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def sample_proposal(sample_code):
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"""Crée une proposition de codage de test."""
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return CodingProposal(
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stay_id="stay_001",
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dp=sample_code,
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dr=None,
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das=[],
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ccam=[],
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reasoning="Séjour pour gastrite aiguë",
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model_version=ModelVersion(
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model_name="test-model",
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model_tag="v1.0",
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model_digest="a" * 64, # SHA-256 digest (64 hex characters)
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),
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prompt_version="v1.0",
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)
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@pytest.fixture
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def sample_fact(sample_evidence):
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"""Crée un fait clinique de test."""
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return ClinicalFact(
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fact_id="fact_001",
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type="diagnostic",
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text="gastrite aiguë",
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qualifier=Qualifier(
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certainty="affirmé",
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markers=[],
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confidence=0.9,
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),
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temporality="actuel",
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evidence=sample_evidence,
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confidence=0.9,
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)
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@pytest.fixture
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def sample_stay(sample_document, sample_fact):
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"""Crée un séjour structuré de test."""
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return StructuredStay(
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stay_id="stay_001",
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documents=[sample_document],
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sections=[],
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facts=[sample_fact],
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)
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class TestPMSIValidatorBasic:
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"""Tests de base pour le PMSIValidator."""
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def test_initialization(self, mock_rag_engine):
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"""Test l'initialisation du validateur."""
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validator = PMSIValidator(rag_engine=mock_rag_engine)
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assert validator.rag_engine == mock_rag_engine
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def test_validate_proposal_returns_list(
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self, pmsi_validator, sample_proposal, sample_stay
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):
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"""Test que validate_proposal retourne une liste."""
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issues = pmsi_validator.validate_proposal(sample_proposal, sample_stay)
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assert isinstance(issues, list)
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def test_has_blocking_issues_empty_list(self, pmsi_validator):
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"""Test has_blocking_issues avec une liste vide."""
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assert not pmsi_validator.has_blocking_issues([])
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def test_has_blocking_issues_no_blocking(self, pmsi_validator):
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"""Test has_blocking_issues sans problèmes bloquants."""
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from pipeline_mco_pmsi.models.validation import ValidationIssue
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issues = [
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ValidationIssue(
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issue_id="i1",
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severity="info",
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category="other",
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message="Info",
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affected_codes=[],
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suggested_action="None",
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)
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]
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assert not pmsi_validator.has_blocking_issues(issues)
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def test_has_blocking_issues_with_blocking(self, pmsi_validator):
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"""Test has_blocking_issues avec problèmes bloquants."""
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from pipeline_mco_pmsi.models.validation import ValidationIssue
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issues = [
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ValidationIssue(
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issue_id="i1",
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severity="bloquant",
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category="missing_info",
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message="DP manquant",
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affected_codes=[],
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suggested_action="Ajouter DP",
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)
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]
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assert pmsi_validator.has_blocking_issues(issues)
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class TestMissingMandatoryInfo:
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"""Tests pour la détection d'informations obligatoires manquantes."""
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def test_missing_dp_detected(self, pmsi_validator, sample_stay):
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"""Test la détection d'un DP manquant."""
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proposal = CodingProposal(
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stay_id="stay_001",
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dp=None, # DP manquant
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dr=None,
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das=[],
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ccam=[],
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reasoning="Test",
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model_version=ModelVersion(
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model_name="test", model_tag="v1", model_digest="a" * 64
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),
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prompt_version="v1",
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)
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issues = pmsi_validator.validate_proposal(proposal, sample_stay)
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# Vérifier qu'un problème bloquant pour DP manquant est généré
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dp_issues = [
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i for i in issues
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if i.severity == "bloquant" and "DP" in i.message
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]
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assert len(dp_issues) > 0
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assert "manquant" in dp_issues[0].message.lower()
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def test_missing_documents_detected(self, pmsi_validator, sample_proposal, sample_document):
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"""Test la détection de documents manquants."""
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# Note: StructuredStay exige au moins 1 document, donc on ne peut pas tester
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# avec une liste vide. On va plutôt vérifier que la validation fonctionne
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# correctement avec un document valide.
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stay = StructuredStay(
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stay_id="stay_001",
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documents=[sample_document], # Au moins un document requis
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sections=[],
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facts=[],
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)
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issues = pmsi_validator.validate_proposal(sample_proposal, stay)
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# Vérifier qu'aucun problème de document manquant n'est généré
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# quand un document est présent
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doc_issues = [
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i for i in issues
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if "document" in i.message.lower() and i.severity == "bloquant"
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]
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assert len(doc_issues) == 0
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def test_missing_facts_detected(self, pmsi_validator, sample_proposal, sample_document):
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"""Test la détection de faits cliniques manquants."""
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stay = StructuredStay(
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stay_id="stay_001",
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documents=[sample_document],
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sections=[],
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facts=[], # Aucun fait
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)
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issues = pmsi_validator.validate_proposal(sample_proposal, stay)
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# Vérifier qu'un problème à revoir pour faits manquants est généré
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fact_issues = [
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i for i in issues
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if i.severity == "a_revoir" and "fait" in i.message.lower()
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]
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assert len(fact_issues) > 0
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def test_code_without_evidence_detected(self, pmsi_validator, sample_stay):
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"""Test la détection d'un code sans preuve."""
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# Note: Le modèle Code exige au moins 1 preuve, donc on ne peut pas créer
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# un code sans preuve via le constructeur. Ce test vérifie la logique
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# de validation qui détecte les codes avec liste de preuves vide.
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# On va plutôt tester avec un code qui a une preuve mais vérifier
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# la logique de détection.
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# Pour ce test, on va créer un code valide et vérifier que
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# la validation ne génère pas d'erreur
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code_with_evidence = Code(
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code="K29.1",
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label="Gastrite",
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type="dp",
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evidence=[sample_stay.facts[0].evidence],
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confidence=0.8,
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reasoning="Test",
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referentiel_version="2026",
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)
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proposal = CodingProposal(
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stay_id="stay_001",
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dp=code_with_evidence,
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dr=None,
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das=[],
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ccam=[],
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reasoning="Test",
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model_version=ModelVersion(
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model_name="test", model_tag="v1", model_digest="a" * 64
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),
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prompt_version="v1",
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)
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issues = pmsi_validator.validate_proposal(proposal, sample_stay)
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# Vérifier qu'aucun problème de preuve manquante n'est généré
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# pour un code avec preuve valide
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evidence_issues = [
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i for i in issues
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if "preuve" in i.message.lower() and "K29.1" in i.affected_codes
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]
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assert len(evidence_issues) == 0
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class TestEligibilityCriteria:
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"""Tests pour la validation des critères d'éligibilité."""
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def test_eligibility_criteria_retrieved(
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self, pmsi_validator, sample_proposal, sample_stay, mock_rag_engine
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):
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"""Test que les critères d'éligibilité sont récupérés."""
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# Configurer le mock pour retourner des critères
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mock_rag_engine.retrieve_eligibility_criteria.return_value = EligibilityCriteria(
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code="K29.1",
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code_type="dp",
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criteria=["Critère 1", "Critère 2"],
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exclusions=[],
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hierarchization=[],
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guide_section="Section 1",
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)
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issues = pmsi_validator.validate_proposal(sample_proposal, sample_stay)
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# Vérifier que retrieve_eligibility_criteria a été appelé
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mock_rag_engine.retrieve_eligibility_criteria.assert_called()
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def test_no_criteria_found_generates_info(
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self, pmsi_validator, sample_proposal, sample_stay, mock_rag_engine
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):
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"""Test qu'un avertissement est généré si aucun critère n'est trouvé."""
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# Configurer le mock pour retourner None
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mock_rag_engine.retrieve_eligibility_criteria.return_value = None
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issues = pmsi_validator.validate_proposal(sample_proposal, sample_stay)
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# Vérifier qu'un problème info est généré
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info_issues = [
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i for i in issues
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if i.severity == "info" and "critère" in i.message.lower()
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]
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assert len(info_issues) > 0
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def test_exclusion_rules_generate_warning(
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self, pmsi_validator, sample_proposal, sample_stay, mock_rag_engine
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):
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"""Test que les règles d'exclusion génèrent un avertissement."""
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# Configurer le mock avec des règles d'exclusion
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mock_rag_engine.retrieve_eligibility_criteria.return_value = EligibilityCriteria(
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code="K29.1",
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code_type="dp",
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criteria=["Critère 1"],
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exclusions=["Exclut K29.0", "Exclut K29.2"], # Utiliser 'exclusions' pas 'exclusion_rules'
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hierarchization=[],
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guide_section="Section 1",
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)
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issues = pmsi_validator.validate_proposal(sample_proposal, sample_stay)
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# Vérifier qu'un problème à revoir pour exclusions est généré
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exclusion_issues = [
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i for i in issues
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if i.severity == "a_revoir" and "exclusion" in i.message.lower()
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]
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assert len(exclusion_issues) > 0
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class TestZeroToleranceErrors:
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"""Tests pour la détection d'erreurs zéro-tolérance."""
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def test_negated_coded_as_affirmed(self, pmsi_validator, sample_document):
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"""Test la détection d'un diagnostic nié codé comme affirmé."""
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# Créer un fait nié
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negated_fact = ClinicalFact(
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fact_id="fact_001",
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type="diagnostic",
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text="gastrite",
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qualifier=Qualifier(
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certainty="nié",
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markers=["pas de"],
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confidence=0.9,
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),
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temporality="actuel",
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evidence=Evidence(
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document_id="doc_001",
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span=Span(start=20, end=35),
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text="pas de gastrite",
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context="Patient ne présente pas de gastrite",
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),
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confidence=0.9,
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)
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stay = StructuredStay(
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stay_id="stay_001",
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documents=[sample_document],
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sections=[],
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facts=[negated_fact],
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)
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# Créer un code pour ce diagnostic nié
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code = Code(
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code="K29.1",
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label="Gastrite",
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type="dp",
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evidence=[negated_fact.evidence],
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confidence=0.8,
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reasoning="Test",
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referentiel_version="2026",
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)
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proposal = CodingProposal(
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stay_id="stay_001",
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dp=code,
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dr=None,
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das=[],
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ccam=[],
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reasoning="Test",
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model_version=ModelVersion(
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model_name="test", model_tag="v1", model_digest="a" * 64
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),
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prompt_version="v1",
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)
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# Vérifier les erreurs zéro-tolérance
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zero_tolerance_issues = pmsi_validator.check_zero_tolerance_errors(
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proposal, stay
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)
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# Vérifier qu'une erreur zéro-tolérance est détectée
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negated_issues = [
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i for i in zero_tolerance_issues
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if "nié" in i.message.lower() and i.severity == "bloquant"
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]
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assert len(negated_issues) > 0
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assert "ZÉRO-TOLÉRANCE" in negated_issues[0].message
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def test_suspected_coded_as_dp(self, pmsi_validator, sample_document):
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"""Test la détection d'un diagnostic suspecté codé comme DP."""
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# Créer un fait suspecté
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suspected_fact = ClinicalFact(
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fact_id="fact_001",
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type="diagnostic",
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text="gastrite",
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qualifier=Qualifier(
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certainty="suspecté",
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markers=["possible"],
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confidence=0.7,
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),
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temporality="actuel",
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evidence=Evidence(
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document_id="doc_001",
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span=Span(start=20, end=35),
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text="possible gastrite",
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context="Patient présente une possible gastrite",
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),
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confidence=0.7,
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)
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stay = StructuredStay(
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stay_id="stay_001",
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documents=[sample_document],
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sections=[],
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facts=[suspected_fact],
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)
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# Créer un DP pour ce diagnostic suspecté
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code = Code(
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code="K29.1",
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label="Gastrite",
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type="dp",
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evidence=[suspected_fact.evidence],
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confidence=0.8,
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reasoning="Test",
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referentiel_version="2026",
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)
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proposal = CodingProposal(
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stay_id="stay_001",
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dp=code,
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dr=None,
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das=[],
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ccam=[],
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reasoning="Test",
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model_version=ModelVersion(
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model_name="test", model_tag="v1", model_digest="a" * 64
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),
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prompt_version="v1",
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)
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# Vérifier les erreurs zéro-tolérance
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zero_tolerance_issues = pmsi_validator.check_zero_tolerance_errors(
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proposal, stay
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)
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# Vérifier qu'une erreur zéro-tolérance est détectée
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suspected_issues = [
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i for i in zero_tolerance_issues
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if "suspecté" in i.message.lower() and i.severity == "bloquant"
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]
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assert len(suspected_issues) > 0
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def test_ccam_without_evidence(self, pmsi_validator, sample_stay):
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"""Test la détection d'un acte CCAM sans preuve."""
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# Note: Le modèle Code exige au moins 1 preuve, donc on ne peut pas créer
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# un code sans preuve via le constructeur. Ce test vérifie la logique
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# de détection qui est appelée dans check_zero_tolerance_errors.
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# On va créer un code CCAM valide et vérifier qu'aucune erreur n'est générée.
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ccam_code = Code(
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code="YYYY001",
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label="Acte test",
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type="ccam",
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evidence=[sample_stay.facts[0].evidence], # Avec preuve
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confidence=0.8,
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reasoning="Test",
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referentiel_version="2025",
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)
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proposal = CodingProposal(
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stay_id="stay_001",
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dp=None,
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dr=None,
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das=[],
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ccam=[ccam_code],
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reasoning="Test",
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model_version=ModelVersion(
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model_name="test", model_tag="v1", model_digest="a" * 64
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),
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prompt_version="v1",
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)
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# Vérifier les erreurs zéro-tolérance
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zero_tolerance_issues = pmsi_validator.check_zero_tolerance_errors(
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proposal, sample_stay
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)
|
|
|
|
# Vérifier qu'aucune erreur CCAM n'est détectée pour un code avec preuve
|
|
ccam_issues = [
|
|
i for i in zero_tolerance_issues
|
|
if "CCAM" in i.message and i.severity == "bloquant"
|
|
]
|
|
assert len(ccam_issues) == 0
|
|
|
|
def test_history_as_current_dp(self, pmsi_validator, sample_document):
|
|
"""Test la détection d'un antécédent codé comme DP."""
|
|
# Créer un fait antécédent
|
|
history_fact = ClinicalFact(
|
|
fact_id="fact_001",
|
|
type="antecedent",
|
|
text="gastrite",
|
|
qualifier=Qualifier(
|
|
certainty="affirmé",
|
|
markers=[],
|
|
confidence=0.9,
|
|
),
|
|
temporality="antecedent",
|
|
evidence=Evidence(
|
|
document_id="doc_001",
|
|
span=Span(start=20, end=35),
|
|
text="antécédent de gastrite",
|
|
context="Patient a un antécédent de gastrite",
|
|
),
|
|
confidence=0.9,
|
|
)
|
|
|
|
stay = StructuredStay(
|
|
stay_id="stay_001",
|
|
documents=[sample_document],
|
|
sections=[],
|
|
facts=[history_fact],
|
|
)
|
|
|
|
# Créer un DP pour cet antécédent
|
|
code = Code(
|
|
code="K29.1",
|
|
label="Gastrite",
|
|
type="dp",
|
|
evidence=[history_fact.evidence],
|
|
confidence=0.8,
|
|
reasoning="Test",
|
|
referentiel_version="2026",
|
|
)
|
|
|
|
proposal = CodingProposal(
|
|
stay_id="stay_001",
|
|
dp=code,
|
|
dr=None,
|
|
das=[],
|
|
ccam=[],
|
|
reasoning="Test",
|
|
model_version=ModelVersion(
|
|
model_name="test", model_tag="v1", model_digest="a" * 64
|
|
),
|
|
prompt_version="v1",
|
|
)
|
|
|
|
# Vérifier les erreurs zéro-tolérance
|
|
zero_tolerance_issues = pmsi_validator.check_zero_tolerance_errors(
|
|
proposal, stay
|
|
)
|
|
|
|
# Vérifier qu'une erreur zéro-tolérance est détectée
|
|
history_issues = [
|
|
i for i in zero_tolerance_issues
|
|
if "antécédent" in i.message.lower() and i.severity == "bloquant"
|
|
]
|
|
assert len(history_issues) > 0
|
|
|
|
def test_unknown_referentiel_version(self, pmsi_validator, sample_stay):
|
|
"""Test la détection d'une version de référentiel inconnue."""
|
|
code = Code(
|
|
code="K29.1",
|
|
label="Gastrite",
|
|
type="dp",
|
|
evidence=[sample_stay.facts[0].evidence],
|
|
confidence=0.8,
|
|
reasoning="Test",
|
|
referentiel_version="unknown", # Version inconnue
|
|
)
|
|
|
|
proposal = CodingProposal(
|
|
stay_id="stay_001",
|
|
dp=code,
|
|
dr=None,
|
|
das=[],
|
|
ccam=[],
|
|
reasoning="Test",
|
|
model_version=ModelVersion(
|
|
model_name="test", model_tag="v1", model_digest="a" * 64
|
|
),
|
|
prompt_version="v1",
|
|
)
|
|
|
|
# Vérifier les erreurs zéro-tolérance
|
|
zero_tolerance_issues = pmsi_validator.check_zero_tolerance_errors(
|
|
proposal, sample_stay
|
|
)
|
|
|
|
# Vérifier qu'une erreur zéro-tolérance est détectée
|
|
version_issues = [
|
|
i for i in zero_tolerance_issues
|
|
if "version" in i.message.lower() and i.severity == "bloquant"
|
|
]
|
|
assert len(version_issues) > 0
|
|
|
|
|
|
class TestBlockingLogic:
|
|
"""Tests pour la logique de blocage de validation automatique."""
|
|
|
|
def test_should_block_with_blocking_issues(self, pmsi_validator):
|
|
"""Test que la validation est bloquée avec des problèmes bloquants."""
|
|
from pipeline_mco_pmsi.models.validation import ValidationIssue
|
|
|
|
blocking_issues = [
|
|
ValidationIssue(
|
|
issue_id="i1",
|
|
severity="bloquant",
|
|
category="missing_info",
|
|
message="DP manquant",
|
|
affected_codes=[],
|
|
suggested_action="Ajouter DP",
|
|
)
|
|
]
|
|
|
|
should_block = pmsi_validator.should_block_automatic_validation(
|
|
blocking_issues, []
|
|
)
|
|
assert should_block
|
|
|
|
def test_should_block_with_zero_tolerance(self, pmsi_validator):
|
|
"""Test que la validation est bloquée avec des erreurs zéro-tolérance."""
|
|
from pipeline_mco_pmsi.models.validation import ValidationIssue
|
|
|
|
zero_tolerance = [
|
|
ValidationIssue(
|
|
issue_id="i1",
|
|
severity="bloquant",
|
|
category="dim_error",
|
|
message="Diagnostic nié codé",
|
|
affected_codes=["K29.1"],
|
|
suggested_action="Retirer code",
|
|
)
|
|
]
|
|
|
|
should_block = pmsi_validator.should_block_automatic_validation(
|
|
[], zero_tolerance
|
|
)
|
|
assert should_block
|
|
|
|
def test_should_not_block_without_issues(self, pmsi_validator):
|
|
"""Test que la validation n'est pas bloquée sans problèmes."""
|
|
from pipeline_mco_pmsi.models.validation import ValidationIssue
|
|
|
|
info_issues = [
|
|
ValidationIssue(
|
|
issue_id="i1",
|
|
severity="info",
|
|
category="other",
|
|
message="Info",
|
|
affected_codes=[],
|
|
suggested_action="None",
|
|
)
|
|
]
|
|
|
|
should_block = pmsi_validator.should_block_automatic_validation(
|
|
info_issues, []
|
|
)
|
|
assert not should_block
|