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How to Build a Safe, Autonomous Prior Authorization Agent for Healthcare Revenue Cycle Management with Human-in-the-Loop Controls

def _now_iso() -> str: return datetime.utcnow().replace(microsecond=0).isoformat() + "Z" def _stable_id(prefix: str, seed: str) -> str: h =…
How to Build a Safe, Autonomous Prior Authorization Agent for Healthcare Revenue Cycle Management with Human-in-the-Loop Controls
def _now_iso() -> str: return datetime.utcnow().replace(microsecond=0).isoformat() + "Z" def _stable_id(prefix: str, seed: str) -> str: h = hashlib.sha256(seed.encode("utf-8")).hexdigest()[:10] return f"{prefix}_{h}" class MockEHR: def __init__(self): self.orders_queue: List = [] self.patient_docs: Dict] = {} def seed_data(self, n_orders: int = 5): random.seed(7) def make_patient(i: int) -> Patient: pid = f"PT{i:04d}" plan = random.choice(list(InsurancePlan)) return Patient( patient_id=pid, name=f"Patient {i}", dob="1980-01-01", member_id=f"M{i:08d}", plan=plan, ) def docs_for_order(patient: Patient, surgery: SurgeryType) -> List: base = [ ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "H&P"), doc_type=DocType.H_AND_P, created_at=_now_iso(), content="H&P: Relevant history, exam findings, and surgical indication.", source="EHR", ), ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "NOTE"), doc_type=DocType.CLINICAL_NOTE, created_at=_now_iso(), content="Clinical note: Symptoms, conservative management attempted, clinician assessment.", source="EHR", ), ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "MEDS"), doc_type=DocType.MED_LIST, created_at=_now_iso(), content="Medication list: Current meds, allergies, contraindications.", source="EHR", ), ] maybe = [] if surgery in : maybe.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "LABS"), doc_type=DocType.LABS, created_at=_now_iso(), content="Labs: CBC/CMP within last 30 days.", source="LabSystem", ) ) if surgery in : maybe.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "IMG"), doc_type=DocType.IMAGING, created_at=_now_iso(), content="Imaging: MRI/X-ray report supporting diagnosis and severity.", source="Radiology", ) ) final = base + if random.random() > 0.6: final.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "PRIOR_TX"), doc_type=DocType.PRIOR_TX, created_at=_now_iso(), content="Prior treatments: PT, meds, injections tried over 6+ weeks.", source="EHR", ) ) if random.random() > 0.5: final.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "CONSENT"), doc_type=DocType.CONSENT, created_at=_now_iso(), content="Consent: Signed procedure consent and risk disclosure.", source="EHR", ) ) return final for i in range(1, n_orders + 1): patient = make_patient(i) surgery = random.choice(list(SurgeryType)) order = SurgeryOrder( order_id=_stable_id("ORD", patient.patient_id + surgery.value), patient=patient, surgery_type=surgery, scheduled_date=(datetime.utcnow().date() + timedelta(days=random.randint(3, 21))).isoformat(), ordering_provider_npi=str(random.randint(1000000000, 1999999999)), diagnosis_codes=["M17.11", "M54.5"] if surgery != SurgeryType.CATARACT else ["H25.9"], created_at=_now_iso(), ) self.orders_queue.append(order) self.patient_docs = docs_for_order(patient, surgery) def poll_new_surgery_orders(self, max_n: int = 1) -> List: pulled = self.orders_queue[:max_n] self.orders_queue = self.orders_queue return pulled def get_patient_documents(self, patient_id: str) -> List: return list(self.patient_docs.get(patient_id, [])) def fetch_additional_docs(self, patient_id: str, needed: List) -> List: generated = [] for dt in needed: generated.append( ClinicalDocument( doc_id=_stable_id("DOC", patient_id + dt.value + str(time.time())), doc_type=dt, created_at=_now_iso(), content=f"Auto-collected document for {dt.value}: extracted and formatted per payer policy.", source="AutoCollector", ) ) self.patient_docs.setdefault(patient_id, []).extend(generated) return generated class MockPayerPortal: def __init__(self): self.db: Dict] = {} random.seed(11) def required_docs_policy(self, plan: InsurancePlan, surgery: SurgeryType) -> List: base = if surgery in : base += if surgery == SurgeryType.BARIATRIC: base += if plan in : base += return sorted(list(set(base)), key=lambda x: x.value) def submit(self, pa: PriorAuthRequest) -> PayerResponse: payer_ref = _stable_id("PAYREF", pa.request_id + _now_iso()) docs_present = {d.doc_type for d in pa.docs_attached} required = self.required_docs_policy(pa.order.patient.plan, pa.order.surgery_type) missing = self.db = { "status": AuthStatus.SUBMITTED, "order_id": pa.order.order_id, "plan": pa.order.patient.plan, "surgery": pa.order.surgery_type, "missing": missing, "polls": 0, "submitted_at": _now_iso(), "denial_reason": None, } msg = "Submission received.
nexttech-news.com
January 16, 2026 at 7:09 AM
How to Build a Safe, Autonomous Prior Authorization Agent for Healthcare Revenue Cycle Management with Human-in-the-Loop Controls

def _now_iso() -> str: return datetime.utcnow().replace(microsecond=0).isoformat() + "Z" def _stable_id(prefix: str, seed: str) -> str: h =…
How to Build a Safe, Autonomous Prior Authorization Agent for Healthcare Revenue Cycle Management with Human-in-the-Loop Controls
def _now_iso() -> str: return datetime.utcnow().replace(microsecond=0).isoformat() + "Z" def _stable_id(prefix: str, seed: str) -> str: h = hashlib.sha256(seed.encode("utf-8")).hexdigest()[:10] return f"{prefix}_{h}" class MockEHR: def __init__(self): self.orders_queue: List = [] self.patient_docs: Dict] = {} def seed_data(self, n_orders: int = 5): random.seed(7) def make_patient(i: int) -> Patient: pid = f"PT{i:04d}" plan = random.choice(list(InsurancePlan)) return Patient( patient_id=pid, name=f"Patient {i}", dob="1980-01-01", member_id=f"M{i:08d}", plan=plan, ) def docs_for_order(patient: Patient, surgery: SurgeryType) -> List: base = [ ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "H&P"), doc_type=DocType.H_AND_P, created_at=_now_iso(), content="H&P: Relevant history, exam findings, and surgical indication.", source="EHR", ), ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "NOTE"), doc_type=DocType.CLINICAL_NOTE, created_at=_now_iso(), content="Clinical note: Symptoms, conservative management attempted, clinician assessment.", source="EHR", ), ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "MEDS"), doc_type=DocType.MED_LIST, created_at=_now_iso(), content="Medication list: Current meds, allergies, contraindications.", source="EHR", ), ] maybe = [] if surgery in : maybe.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "LABS"), doc_type=DocType.LABS, created_at=_now_iso(), content="Labs: CBC/CMP within last 30 days.", source="LabSystem", ) ) if surgery in : maybe.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "IMG"), doc_type=DocType.IMAGING, created_at=_now_iso(), content="Imaging: MRI/X-ray report supporting diagnosis and severity.", source="Radiology", ) ) final = base + if random.random() > 0.6: final.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "PRIOR_TX"), doc_type=DocType.PRIOR_TX, created_at=_now_iso(), content="Prior treatments: PT, meds, injections tried over 6+ weeks.", source="EHR", ) ) if random.random() > 0.5: final.append( ClinicalDocument( doc_id=_stable_id("DOC", patient.patient_id + "CONSENT"), doc_type=DocType.CONSENT, created_at=_now_iso(), content="Consent: Signed procedure consent and risk disclosure.", source="EHR", ) ) return final for i in range(1, n_orders + 1): patient = make_patient(i) surgery = random.choice(list(SurgeryType)) order = SurgeryOrder( order_id=_stable_id("ORD", patient.patient_id + surgery.value), patient=patient, surgery_type=surgery, scheduled_date=(datetime.utcnow().date() + timedelta(days=random.randint(3, 21))).isoformat(), ordering_provider_npi=str(random.randint(1000000000, 1999999999)), diagnosis_codes=["M17.11", "M54.5"] if surgery != SurgeryType.CATARACT else ["H25.9"], created_at=_now_iso(), ) self.orders_queue.append(order) self.patient_docs = docs_for_order(patient, surgery) def poll_new_surgery_orders(self, max_n: int = 1) -> List: pulled = self.orders_queue[:max_n] self.orders_queue = self.orders_queue return pulled def get_patient_documents(self, patient_id: str) -> List: return list(self.patient_docs.get(patient_id, [])) def fetch_additional_docs(self, patient_id: str, needed: List) -> List: generated = [] for dt in needed: generated.append( ClinicalDocument( doc_id=_stable_id("DOC", patient_id + dt.value + str(time.time())), doc_type=dt, created_at=_now_iso(), content=f"Auto-collected document for {dt.value}: extracted and formatted per payer policy.", source="AutoCollector", ) ) self.patient_docs.setdefault(patient_id, []).extend(generated) return generated class MockPayerPortal: def __init__(self): self.db: Dict] = {} random.seed(11) def required_docs_policy(self, plan: InsurancePlan, surgery: SurgeryType) -> List: base = if surgery in : base += if surgery == SurgeryType.BARIATRIC: base += if plan in : base += return sorted(list(set(base)), key=lambda x: x.value) def submit(self, pa: PriorAuthRequest) -> PayerResponse: payer_ref = _stable_id("PAYREF", pa.request_id + _now_iso()) docs_present = {d.doc_type for d in pa.docs_attached} required = self.required_docs_policy(pa.order.patient.plan, pa.order.surgery_type) missing = self.db = { "status": AuthStatus.SUBMITTED, "order_id": pa.order.order_id, "plan": pa.order.patient.plan, "surgery": pa.order.surgery_type, "missing": missing, "polls": 0, "submitted_at": _now_iso(), "denial_reason": None, } msg = "Submission received.
nexttech-news.com
January 16, 2026 at 7:09 AM
Term Insurance எடுக்க இது மட்டும் போதுமா

Panathottam Website: panathottam.com
Contact: 95144 30035

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January 10, 2025 at 4:43 AM
Benefit of LIC Jeevan Anand Policy: ಎಲ್‌ಐಸಿ ಜೀವನ್ ಆನಂದ್ ಪಾಲಿಸಿ: ನಿಮ್ಮ ಭವಿಷ್ಯಕ್ಕೆ ಭದ್ರ ಬುನಾದಿ, ಯೋಜನೆಯ ಪ್ರಮುಖ ಲಾಭಗಳೇನು? ಈ ಸುದ್ದಿ ಓದಿ….!

#LICJeevanAnand #LICIndia #LICPolicy #InsurancePlan #SaveAndEarn #FinancialSecurity #LongTermInvestment
#MaturityBenefits #LICReturns #SecureFuture #BestLICPlan #MoneySavingTips
Benefit Of LIC Jeevan Anand Policy: ಎಲ್‌ಐಸಿ ಜೀವನ್ ಆನಂದ್ ಪಾಲಿಸಿ: ನಿಮ್ಮ ಭವಿಷ್ಯಕ್ಕೆ ಭದ್ರ ಬುನಾದಿ, ಯೋಜನೆಯ ಪ್ರಮುಖ ಲಾಭಗಳೇನು? ಈ ಸುದ್ದಿ ಓದಿ….! - ISM Kannada News
Benefit of LIC Jeevan Anand Policy - ಇಂದಿನ ಸ್ಪರ್ಧಾತ್ಮಕ ಜಗತ್ತಿನಲ್ಲಿ ಹಣ ಉಳಿತಾಯ ಮಾಡುವುದು ಮತ್ತು ಹೂಡಿಕೆ ಮಾಡುವುದು ಎಲ್ಲರ ಜೀವನದ ಅವಿಭಾಜ್ಯ ಅಂಗವಾಗಿದೆ. ಕೆಲವರು ಷೇರು
ismkannadanews.com
June 4, 2025 at 6:34 AM
The premium for an ACA health insuranceplan is $635 per month. The average bronze plan costs $543 per month; silver plans cost $660 per month; gold plans cost $708 per month and platinum plans cost $1,209 per month.
January 27, 2025 at 7:08 PM