openenv.yaml

spec_version: 1
name: medcoderl
type: space
runtime: fastapi
app: server.app:app
port: 7680

description: >
  MedCodeRL — Medical Coding & Billing Compliance environment.
  Agents analyze clinical documentation and assign ICD-10/CPT codes,
  make billing compliance decisions, and identify fraud patterns.
  90 synthetic cases across 3 difficulty tiers with deterministic grading.

author: privexa
version: 1.0.0
tags:
  - openenv
  - medical-coding
  - healthcare
  - compliance

tasks:
  easy:
    description: "Straightforward cases with single diagnoses and direct ICD-10/CPT mapping."
    count: 30
  medium:
    description: "Multi-diagnosis cases with comorbidities, insurance considerations, and partial ambiguity."
    count: 30
  hard:
    description: "Complex compliance dilemmas: upcoding, unbundling, fraud detection, ethical edge cases."
    count: 30

action_space:
  type: object
  model: models.MedAction
  fields:
    diagnosis_codes: "list[str] — ICD-10-CM codes (1-5)"
    procedure_codes: "list[str] — CPT/HCPCS codes (0-5)"
    decision: "str — approve | reject | review"
    confidence: "float — 0.0 to 1.0"
    reasoning: "str — clinical justification (15-500 chars)"
    modifier_codes: "list[str] — optional CPT modifiers (0-3)"
    risk_flags: "list[str] — compliance risk flags (0-5)"

observation_space:
  type: object
  model: models.MedObservation
  fields:
    case_id: "str — unique case identifier"
    difficulty: "str — easy | medium | hard"
    clinical_note: "str — full clinical documentation"
    symptoms: "list[str] — reported symptoms"
    treatments: "list[str] — treatments administered"
    insurance_type: "str — Medicare | Medicaid | Private | Uninsured"
    prior_auth_required: "bool — prior authorization needed"
    treatment_cost: "str — low | medium | high"
    patient_age: "int — patient age in years"
    patient_sex: "str — M | F"
    provider_specialty: "str — treating provider specialty"
    visit_type: "str — inpatient | outpatient | emergency | telehealth"
    comorbidities: "list[str] — pre-existing conditions"
    lab_results: "str | null — relevant lab findings"
    medications: "list[str] — current medications"

reward_space:
  type: float
  range: [0.01, 0.99]
  description: >
    Deterministic composite score: diagnosis accuracy (35%),
    procedure accuracy (20%), decision accuracy (25%),
    reasoning quality (10%), risk flag identification (5%),
    confidence calibration (5%). Shaped with bonuses and penalties.