fix(clinical): red flags, one crisis rule, callback after a crisis, one table of numbers

Clinical review of the questionnaires (ADR-013):
- Red-flag block first in stage 1 (config/instruments/red_flags.yaml); any «Да» stops the
  questionnaire with an acute alert and the help screen of its category.
- One crisis rule: the crisis screen opens at a HIGH C-SSRS risk only; moderate stops and goes
  to a psychiatrist (24 h as a guide), low is a flag with the safety plan. PHQ-9 item 9 with a
  negative screener is a discrepancy flag; without a completed screener it asks the C-SSRS at once.
  config/questionnaire.yaml: cssrs_positive_policy graded (C01).
- Every crisis leaves a callback task for the doctor on duty (post_crisis_call, one per patient)
  and the app asks how the person is the next day, the safety plan one tap away.
- Routing: risk and flags first, scales second; PCL-5 >= 50 no longer means a priority
  appointment (pcl5_severe is moderate on the dashboard too).
- Crisis numbers live only in config/texts/crisis.yaml; texts and the agent prompt refer to them
  via {phone:<key>}. Fixes the children's helpline offered to adults by the chat agent.

Refs #92

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
2026-10-04 16:21:16 +03:00
co-authored by Claude Opus 5.5
parent bde6ec6855
commit 44814b7293
29 changed files with 365 additions and 56 deletions
+2 -1
View File
@@ -12,6 +12,7 @@ import yaml
from app.config import get_settings
from app.core.intake_questions import content
from app.core.questionnaire import IntakeDecision, IntakePolicy
from app.core.safety import fill_phones
# Stage 1 finding → diary module of stage 2 (PTSD is the «veteran» module of the profile).
FINDING_MODULE = {"depression_suspected": "depression", "ptsd_suspected": "veteran"}
@@ -23,7 +24,7 @@ PCL5_IMPROVED_BELOW = 28
def texts() -> dict[str, Any]:
return yaml.safe_load((get_settings().config_dir / "texts/results.yaml").read_text(encoding="utf-8"))
return yaml.safe_load(fill_phones((get_settings().config_dir / "texts/results.yaml").read_text(encoding="utf-8")))
def render(interpretation: dict[str, Any]) -> str: