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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.
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