feat(questionnaire): integrate revised intake and follow-up monitoring

Add gated TSQ, Russian C-SSRS Recent, durable responses and notifications, diaries, schedules and audited clinical review. Preserve manual assessment when the Russian follow-up source is unavailable.

Refs #52

app/core/intake_runtime.py

@@ -0,0 +1,153 @@
+"""Versioned release gate and deterministic follow-up planning."""
+
+from calendar import monthrange
+from datetime import date, timedelta
+from pathlib import Path
+from typing import Literal
+from zoneinfo import ZoneInfo
+
+import yaml
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+from app.config import get_settings
+from app.core.questionnaire import Approval, load_policy
+
+
+class RuntimePolicy(BaseModel):
+    model_config = ConfigDict(extra="forbid", frozen=True)
+    version: str
+    enabled: bool = False
+    approval: Approval | None = None
+    content_review: Approval | None = None
+    contact_review: Approval | None = None
+    timezone: str
+    daily_hour: int = Field(ge=0, le=23)
+    mood_baseline_days: int = Field(ge=2)
+    mood_bad_days: int = Field(ge=1)
+    mood_drop: int = Field(ge=1, le=10)
+    sleep_bad_days: int = Field(ge=1)
+    sleep_hours_below: float = Field(gt=0, le=24)
+    nightmares_at: int = Field(ge=0, le=4)
+    missed_medication_days: int = Field(ge=1)
+    high_risk_silence_days: int = Field(ge=1)
+    medication_days: tuple[int, ...]
+    medication_repeat_days: int = Field(ge=1)
+    route_intervals: dict[str, dict[str, int]]
+    alcohol_repeat_days: int = Field(ge=1)
+    phq9_retriage_delta: int = Field(ge=1)
+    pcl5_retriage_delta: int = Field(ge=1)
+
+    @model_validator(mode="after")
+    def valid(self):
+        ZoneInfo(self.timezone)
+        if set(self.route_intervals) != {"after_crisis", "specialist", "self_help"} or any(
+            set(row) != {"phq9", "pcl5"} for row in self.route_intervals.values()
+        ):
+            raise ValueError("all route and scale intervals must be defined")
+        if not self.medication_days or tuple(sorted(set(self.medication_days))) != self.medication_days:
+            raise ValueError("medication days must be nonempty and strictly increasing")
+        if self.medication_days[0] < 1 or any(v < 1 for row in self.route_intervals.values() for v in row.values()):
+            raise ValueError("intervals must be positive")
+        if any(
+            a and a.policy_version != self.version for a in (self.approval, self.content_review, self.contact_review)
+        ):
+            raise ValueError("review must match the runtime version")
+        return self
+
+    @property
+    def released(self) -> bool:
+        return self.enabled and all((self.approval, self.content_review, self.contact_review))
+
+
+def load_runtime(path: Path | None = None) -> RuntimePolicy:
+    path = path or get_settings().config_dir / "intake_runtime.yaml"
+    return RuntimePolicy.model_validate(yaml.safe_load(path.read_text()))
+
+
+def intake_enabled() -> bool:
+    return load_runtime().released and load_policy().approval is not None
+
+
+def month_before(day: date, months: int = 1) -> date:
+    year, month = divmod(day.year * 12 + day.month - 1 - months, 12)
+    return day.replace(year=year, month=month + 1, day=min(day.day, monthrange(year, month + 1)[1]))
+
+
+def due_scales(
+    *,
+    today: date,
+    enrolled: date,
+    last: dict[str, date],
+    route: Literal["specialist", "self_help"],
+    medication_changed: date | None = None,
+    after_crisis: date | None = None,
+    policy: RuntimePolicy | None = None,
+) -> tuple[str, ...]:
+    """Return each overdue form once. Therapy day zero is the recorded start/change date.
+
+    Due dates stay due until completion. Overlapping schedules choose the earlier
+    date; missed ticks do not create a burst of historical questionnaires.
+    """
+    p = policy or load_runtime()
+    due = set()
+    for scale in ("phq9", "pcl5"):
+        completed = last.get(scale)
+        dates = [(completed or enrolled) + timedelta(days=p.route_intervals[route][scale])]
+        if after_crisis and after_crisis <= today:
+            dates.append(
+                max(completed or after_crisis, after_crisis) + timedelta(days=p.route_intervals["after_crisis"][scale])
+            )
+        if medication_changed and medication_changed <= today:
+            for offset in p.medication_days:
+                milestone = medication_changed + timedelta(days=offset)
+                if completed is None or completed < milestone:
+                    dates.append(milestone)
+                    break
+            else:
+                dates.append(
+                    max(completed or medication_changed, medication_changed + timedelta(days=p.medication_days[-1]))
+                    + timedelta(days=p.medication_repeat_days)
+                )
+        if min(dates) <= today:
+            due.add(scale)
+    if (last.get("rus_audit_s") or enrolled) + timedelta(days=p.alcohol_repeat_days) <= today:
+        due.add("rus_audit_s")
+    return tuple(sorted(due))
+
+
+def diary_flags(history: dict[date, dict], today: date, policy: RuntimePolicy | None = None) -> tuple[str, ...]:
+    """Consecutive calendar dates; missing data never become zero or missed doses.
+
+    Baseline is the seven dates BEFORE the three-day deterioration window;
+    every baseline value is required. Nightmares OR short sleep must hold on
+    each of three nights. These candidate definitions require signed review.
+    """
+    p = policy or load_runtime()
+    flags = []
+    current = history.get(today, {})
+    if current.get("death_thoughts") == 1:
+        flags.append("suicide_assessment_now")
+    recent = [history.get(today - timedelta(days=i), {}) for i in range(p.mood_bad_days)]
+    baseline = [
+        history.get(today - timedelta(days=i), {}).get("mood")
+        for i in range(p.mood_bad_days, p.mood_bad_days + p.mood_baseline_days)
+    ]
+    if all(x is not None for x in baseline) and all(x.get("mood") is not None for x in recent):
+        mean = sum(baseline) / len(baseline)
+        if all(mean - x["mood"] >= p.mood_drop for x in recent):
+            flags.append("phq9_due_mood")
+    nights = [history.get(today - timedelta(days=i), {}) for i in range(p.sleep_bad_days)]
+    if all(
+        (r.get("nightmares") is not None and r["nightmares"] >= p.nightmares_at)
+        or (r.get("sleep_hours") is not None and r["sleep_hours"] < p.sleep_hours_below)
+        for r in nights
+    ):
+        flags.append("sleep_review")
+    doses = [history.get(today - timedelta(days=i), {}) for i in range(p.missed_medication_days)]
+    if all(r.get("medication") == "none" for r in doses):
+        flags.append("medication_contact")
+    if current.get("side_effects") == 1:
+        flags.append("side_effects_review")
+    if current.get("medication") == "partial":
+        flags.append("partial_medication_review")
+    return tuple(flags)