Implementation Guide: Manage prescription refill requests end-to-end within approved protocols

# Initial FortiGate setup (console access via USB or mgmt port at 192.168.1.99)
config system interface
  edit port1
    set alias 'WAN'
    set mode dhcp
    set allowaccess ping https
  next
  edit port2
    set alias 'LAN-Clinical'
    set ip 10.10.10.1/24
    set allowaccess ping https ssh
  next
  edit port3
    set alias 'LAN-Guest'
    set ip 10.10.20.1/24
    set allowaccess ping
  next
end

# Enable HIPAA-relevant security profiles
config antivirus profile
  edit 'hipaa-av'
    set scan-mode full
    config http
      set av-scan enable
    end
  next
end

config ips sensor
  edit 'hipaa-ips'
    config entries
      edit 1
        set status enable
        set log enable
        set log-packet enable
        set severity medium high critical
      next
    end
  next
end

# Create firewall policy: Clinical LAN → Internet (for EHR/AI traffic)
config firewall policy
  edit 1
    set name 'Clinical-to-Cloud'
    set srcintf port2
    set dstintf port1
    set srcaddr all
    set dstaddr all
    set action accept
    set schedule always
    set service ALL
    set av-profile 'hipaa-av'
    set ips-sensor 'hipaa-ips'
    set ssl-ssh-profile certificate-inspection
    set logtraffic all
    set nat enable
  next
end

# Enable FortiCloud management for MSP remote access
config system fortiguard
  set forticloud-account-id '<MSP_FORTICLOUD_ID>'
end
exec forticloud activate

# Configure NTP for accurate audit logging
config system ntp
  set ntpsync enable
  set type custom
  config ntpserver
    edit 1
      set server time.nist.gov
    next
  end
end

# Enable logging to FortiCloud / FortiAnalyzer
config log fortianalyzer setting
  set status enable
  set server '<FORTIANALYZER_IP_OR_CLOUD>'
end

<Response>
  <Say voice='Polly.Joanna'>We're sorry, our automated refill system is temporarily unavailable. Please hold while we transfer you to our staff.</Say>
  <Dial>+1PRACTICEPHONE</Dial>
</Response>

// Webhook configuration (Step 8)
{
  "event": "call_ended",
  "url": "https://api.keragon.com/v1/webhooks/<WORKFLOW_ID>/trigger",
  "method": "POST",
  "headers": {
    "Authorization": "Bearer <KERAGON_API_KEY>",
    "Content-Type": "application/json"
  }
}

// Payload includes: call transcript, extracted variables
// (patient name, DOB, medication, pharmacy, etc.)

// Function parameters (Step 9 — verify_patient)
{
  "first_name": "string",
  "last_name": "string",
  "date_of_birth": "string"
}

# === REFILL PROTOCOL DOCUMENTATION TEMPLATE ===

# PRACTICE: [Practice Name]
# CLINICAL SPONSOR: [Physician Name, License #]
# DATE: [Date]
# VERSION: 1.0

# SECTION 1: APPROVED MEDICATION CLASSES FOR AI PROCESSING
# (AI can collect refill request and route to provider queue)
# - Antihypertensives (ACE inhibitors, ARBs, beta-blockers, CCBs, diuretics)
# - Statins and lipid-lowering agents
# - Oral diabetes medications (metformin, sulfonylureas, DPP-4 inhibitors)
# - Thyroid medications (levothyroxine)
# - Proton pump inhibitors
# - Antihistamines (prescription-strength)
# - Topical medications (dermatologic)
# - Oral contraceptives (if applicable)
# - Inhaled corticosteroids / bronchodilators (stable asthma/COPD)
# [ADD/REMOVE per clinical sponsor direction]

# SECTION 2: EXCLUDED MEDICATION CLASSES (Immediate human escalation)
# - ALL Schedule II controlled substances (opioids, stimulants, etc.)
# - ALL Schedule III-V controlled substances (benzodiazepines, etc.)
# - Anticoagulants (warfarin, DOACs) — require INR/lab review
# - Immunosuppressants
# - Antipsychotics / mood stabilizers
# - Chemotherapy agents
# - Any medication requiring lab monitoring before refill
# [ADD/REMOVE per clinical sponsor direction]

# SECTION 3: REFILL ELIGIBILITY RULES
# - Patient must be active in the practice (seen within last 12 months)
# - Medication must have remaining refills on the existing prescription
# - If no remaining refills: escalate to provider for new Rx decision
# - Patient must not have an overdue annual physical (if > 14 months since last visit)
# - Maximum of [3] refill requests per medication before requiring office visit

# SECTION 4: ESCALATION CRITERIA
# - Any adverse reaction reported by patient → immediate nurse escalation
# - Dose change request → provider review required
# - New medication request → provider review required
# - Patient confusion or distress detected by AI → transfer to live staff
# - Controlled substance request → transfer to clinical staff

# SECTION 5: SIGN-OFF
# Clinical Sponsor Signature: __________________
# Date: __________________

GET /fhir/r4/Patient?family={last_name}&given={first_name}&birthdate={dob}

GET /fhir/r4/MedicationRequest?patient={patient_id}&status=active

POST /fhir/r4/Task
{
  "resourceType": "Task",
  "status": "requested",
  "intent": "order",
  "description": "AI-processed refill request: [MedName] [Dose] for [PatientName]",
  "for": { "reference": "Patient/{patient_id}" },
  "requester": { "display": "AI Refill Agent" },
  "input": [
    { "type": { "text": "medication" }, "valueString": "{med_name}" },
    { "type": { "text": "pharmacy" }, "valueString": "{pharmacy_name}" },
    { "type": { "text": "call_recording_id" }, "valueString": "{recording_id}" }
  ]
}

# === For athenahealth (most common SMB EHR) ===

# 1. Register API application at https://developer.athenahealth.com
# Create developer account → New Application → Select API version (v1)
# Application Type: Backend Service
# Requested Scopes: patient.read, medicationrequest.read, task.write
# Note Practice ID: provided by practice administrator

# 2. Obtain OAuth2 credentials
# Client ID: <provided after app approval>
# Client Secret: <provided after app approval>
# Token Endpoint: https://api.athenahealth.com/oauth2/v1/token

# 3. Test authentication
curl -X POST 'https://api.athenahealth.com/oauth2/v1/token' \
  -H 'Content-Type: application/x-www-form-urlencoded' \
  -d 'grant_type=client_credentials&client_id=<CLIENT_ID>&client_secret=<CLIENT_SECRET>&scope=athena/service/Athenahealth.MDP.*'

# Expected response: { 'access_token': '<TOKEN>', 'token_type': 'bearer', 'expires_in': 3600 }

# 4. Test patient search
curl -X GET 'https://api.athenahealth.com/v1/<PRACTICE_ID>/patients?firstname=John&lastname=Smith&dob=01/15/1980' \
  -H 'Authorization: Bearer <ACCESS_TOKEN>'

# 5. Test medication list retrieval
curl -X GET 'https://api.athenahealth.com/v1/<PRACTICE_ID>/patients/<PATIENT_ID>/medications' \
  -H 'Authorization: Bearer <ACCESS_TOKEN>'

# 6. Test task/message creation (for refill routing)
curl -X POST 'https://api.athenahealth.com/v1/<PRACTICE_ID>/patients/<PATIENT_ID>/messages' \
  -H 'Authorization: Bearer <ACCESS_TOKEN>' \
  -H 'Content-Type: application/x-www-form-urlencoded' \
  -d 'messagetype=REFILL_REQUEST&subject=AI+Refill+Request&messagetext=Refill+requested+for+Lisinopril+10mg'

# === For Epic (FHIR R4) ===

# 1. Register at https://appmarket.epic.com (App Orchard)
# Create Backend System application
# Request FHIR R4 scopes: patient/*.read, MedicationRequest.read, Task.write

# 2. Generate JWT for Epic backend authentication
# Epic uses SMART Backend Services (JWT-based OAuth2)
# Generate RSA key pair and register public key with Epic

openssl genrsa -out epic_private_key.pem 2048
openssl rsa -in epic_private_key.pem -pubout -out epic_public_key.pem

# 3. Test FHIR Patient search
curl -X GET 'https://<EPIC_FHIR_BASE>/api/FHIR/R4/Patient?family=Smith&given=John&birthdate=1980-01-15' \
  -H 'Authorization: Bearer <ACCESS_TOKEN>'

# 4. Enter credentials into Keragon
# Navigate to: Keragon → Integrations → [EHR] → Configure → Enter credentials
# Test connection within Keragon interface

# Configure FortiClient with ZTNA tags (if using FortiGate)

config user forticlient-ems
  edit 1
    set name 'Practice-EMS'
    set server '<FORTICLIENT_EMS_IP>'
  next
end

config firewall policy
  edit 100
    set name 'ZTNA-MSP-Admin'
    set srcintf 'ssl.root'
    set dstintf port2
    set srcaddr 'ZTNA-Tag-MSP'
    set dstaddr 'AI-Management-Servers'
    set action accept
    set schedule always
    set utm-status enable
    set logtraffic all
  next
end

# KERAGON WORKFLOW: Patient Identity Verification
# Trigger: Retell AI custom function webhook call
# Response: Synchronous JSON response within 5 seconds

# Workflow Name: verify_patient_identity
# Trigger Type: Webhook (synchronous)
# Endpoint: https://api.keragon.com/v1/webhooks/{workflow_id}/trigger

# --- INPUT SCHEMA ---
# {
#   "first_name": "string",
#   "last_name": "string",  
#   "date_of_birth": "string (MM/DD/YYYY)",
#   "phone_last_four": "string (optional)"
# }

# --- WORKFLOW STEPS ---

# Step 1: Normalize Input
# Action: Transform data
# - Trim whitespace from all fields
# - Convert first_name and last_name to proper case
# - Parse date_of_birth into ISO format (YYYY-MM-DD)
# - Remove any non-numeric characters from phone_last_four

# Step 2: Query EHR Patient Search API
# Action: HTTP Request (via EHR connector)
# --- athenahealth example ---
# Method: GET
# URL: https://api.athenahealth.com/v1/{practice_id}/patients
# Query Parameters:
#   firstname: {normalized_first_name}
#   lastname: {normalized_last_name}
#   dob: {dob_in_MM/DD/YYYY}
#   show: patientid,firstname,lastname,dob,mobilephone,lastappointmentdate
# Headers:
#   Authorization: Bearer {ehr_access_token}

# --- Epic FHIR R4 example ---
# Method: GET  
# URL: https://{epic_fhir_base}/api/FHIR/R4/Patient
# Query Parameters:
#   family: {normalized_last_name}
#   given: {normalized_first_name}
#   birthdate: {dob_in_YYYY-MM-DD}
# Headers:
#   Authorization: Bearer {ehr_access_token}

# Step 3: Evaluate Results
# Action: Conditional Logic
# Condition A: No results returned
#   → Return: { "verified": false, "reason": "no_match" }
# Condition B: Multiple results returned  
#   → If phone_last_four provided, filter by phone number match
#   → If still multiple: Return { "verified": false, "reason": "multiple_matches" }
# Condition C: Single result returned
#   → Extract patient_id, last_appointment_date
#   → Calculate months_since_last_visit
#   → Return: {
#       "verified": true,
#       "patient_id": "{ehr_patient_id}",
#       "patient_first_name": "{first_name}",
#       "last_visit_date": "{last_appointment_date}",
#       "months_since_last_visit": {calculated_months},
#       "active_patient": {months_since_last_visit <= 18}
#     }

# Step 4: Audit Logging
# Action: Log to audit trail
# Log entry: {
#   "event": "patient_verification",
#   "timestamp": "{current_utc_timestamp}",
#   "input_name": "{first_name} {last_name}",
#   "input_dob": "{date_of_birth}",
#   "result": "{verified: true/false}",
#   "patient_id": "{ehr_patient_id or null}",
#   "source": "retell_ai_agent"
# }

# --- OUTPUT SCHEMA ---
# Success: { "verified": true, "patient_id": "12345", "patient_first_name": "John", "last_visit_date": "2024-11-15", "months_since_last_visit": 3, "active_patient": true }
# Failure: { "verified": false, "reason": "no_match" | "multiple_matches" }

# --- TIMEOUT HANDLING ---
# If EHR API does not respond within 4 seconds:
# Return: { "verified": false, "reason": "timeout" }
# Agent will transfer to human staff

# --- ERROR HANDLING ---
# If EHR API returns error (401, 403, 500, etc.):
# Return: { "verified": false, "reason": "system_error" }
# Send alert to MSP monitoring: "EHR API error in patient verification - {error_code}"

# KERAGON WORKFLOW: Refill Eligibility Check and EHR Task Creation
# Trigger: Retell AI post-call webhook (call_ended event)
# Processing: Asynchronous (patient is no longer on the line)

# Workflow Name: process_refill_request
# Trigger Type: Webhook (asynchronous)
# Endpoint: https://api.keragon.com/v1/webhooks/{workflow_id}/trigger

# --- INPUT SCHEMA (from Retell AI call_ended webhook) ---
# {
#   "call_id": "string",
#   "call_recording_url": "string",
#   "call_duration_seconds": integer,
#   "call_status": "completed" | "transferred" | "failed",
#   "extracted_data": {
#     "patient_id": "string (from verification step)",
#     "patient_name": "string",
#     "patient_phone": "string",
#     "medication_name": "string",
#     "medication_dose": "string or null",
#     "pharmacy_name": "string",
#     "pharmacy_location": "string or null",
#     "patient_notes": "string or null",
#     "adverse_effects_reported": boolean,
#     "controlled_substance_detected": boolean,
#     "was_transferred": boolean,
#     "transfer_reason": "string or null"
#   }
# }

# --- WORKFLOW STEPS ---

# Step 1: Pre-filter
# Action: Conditional check
# If call_status != "completed" OR was_transferred == true:
#   → Log: "Call {call_id} was transferred/incomplete. No automated processing."
#   → End workflow
# If patient_id is null or empty:
#   → Log: "Call {call_id} has no verified patient. Manual review needed."
#   → Trigger escalation with reason: "unverified_patient"
#   → End workflow

# Step 2: Medication Classification
# Action: Lookup against approved medication list
# Data source: Practice-specific approved medication JSON (stored in Keragon variables)

# APPROVED_MEDICATIONS_LIST (configure per practice based on Step 5 protocol doc):
# {
#   "approved_classes": [
#     { "class": "ACE Inhibitors", "medications": ["lisinopril", "enalapril", "ramipril", "benazepril", "captopril", "fosinopril", "quinapril"] },
#     { "class": "ARBs", "medications": ["losartan", "valsartan", "irbesartan", "olmesartan", "telmisartan", "candesartan"] },
#     { "class": "Beta Blockers", "medications": ["metoprolol", "atenolol", "propranolol", "carvedilol", "bisoprolol", "nebivolol"] },
#     { "class": "CCBs", "medications": ["amlodipine", "nifedipine", "diltiazem", "verapamil", "felodipine"] },
#     { "class": "Diuretics", "medications": ["hydrochlorothiazide", "chlorthalidone", "furosemide", "spironolactone", "triamterene"] },
#     { "class": "Statins", "medications": ["atorvastatin", "rosuvastatin", "simvastatin", "pravastatin", "lovastatin", "pitavastatin", "fluvastatin"] },
#     { "class": "Oral Diabetes", "medications": ["metformin", "glipizide", "glyburide", "glimepiride", "sitagliptin", "saxagliptin", "linagliptin", "empagliflozin", "dapagliflozin", "canagliflozin", "pioglitazone"] },
#     { "class": "Thyroid", "medications": ["levothyroxine", "liothyronine", "synthroid", "armour thyroid"] },
#     { "class": "PPIs", "medications": ["omeprazole", "pantoprazole", "esomeprazole", "lansoprazole", "rabeprazole", "dexlansoprazole"] },
#     { "class": "Inhaled Respiratory", "medications": ["albuterol", "fluticasone", "budesonide", "montelukast", "tiotropium", "ipratropium", "salmeterol", "formoterol"] },
#     { "class": "Oral Contraceptives", "medications": ["norgestimate-ethinyl estradiol", "levonorgestrel-ethinyl estradiol", "drospirenone-ethinyl estradiol", "norethindrone"] },
#     { "class": "Antihistamines Rx", "medications": ["hydroxyzine", "cetirizine", "levocetirizine", "desloratadine"] }
#   ]
# }

# Normalize medication_name: lowercase, trim, remove brand name suffixes
# Fuzzy match against approved list (Levenshtein distance <= 2 for typo tolerance)
# Result: { "is_approved": boolean, "matched_class": "string or null", "confidence": float }

# If NOT approved and NOT controlled (may be unknown/unlisted):
#   → Trigger escalation with reason: "medication_not_on_approved_list"
#   → End workflow

# Step 3: Query EHR for Active Prescriptions
# Action: HTTP Request via EHR connector
# --- athenahealth ---
# GET /v1/{practice_id}/patients/{patient_id}/medications
# Filter: active medications only
# --- Epic FHIR ---
# GET /api/FHIR/R4/MedicationRequest?patient={patient_id}&status=active

# Parse response to find matching medication
# Match criteria: medication name (fuzzy match) AND dose (if provided by patient)
# Extract: prescription_id, remaining_refills, last_fill_date, prescribing_provider

# Step 4: Eligibility Rules Engine
# Action: Sequential rule evaluation

# Rule 1: Active prescription exists?
# If NO matching active Rx found:
#   → Escalate: "no_active_prescription"
#   → SMS to patient: "We could not find an active prescription matching your request. Our clinical staff will follow up with you."
#   → End

# Rule 2: Refills remaining?
# If remaining_refills == 0:
#   → Create EHR task with flag: "NEW_PRESCRIPTION_NEEDED"
#   → SMS to patient: "Your prescription for {medication} has no remaining refills. Your provider will review and determine if a new prescription can be issued. This may require an office visit."
#   → End

# Rule 3: Last visit within required window?
# Query last appointment date (from verification step or separate API call)
# If months_since_last_visit > 12 (configurable per practice):
#   → Create EHR task with flag: "OVERDUE_VISIT_REFILL_REQUEST"
#   → SMS to patient: "Your refill request has been submitted, but your records show it has been over 12 months since your last visit. Your provider may require an appointment before approving this refill."
#   → Continue (don't block, but flag)

# Rule 4: Refill frequency check
# If last_fill_date < 21 days ago (for 30-day supply) or < 75 days ago (for 90-day supply):
#   → Escalate: "too_early_refill" (possible diversion or error)
#   → SMS to patient: "It appears this medication was recently filled. Our clinical team will review your request."
#   → End

# Step 5: Create EHR Refill Task (All rules passed)
# Action: HTTP Request via EHR connector

# --- athenahealth ---
# POST /v1/{practice_id}/patients/{patient_id}/documents/prescription
# Body: {
#   "documentsubclass": "PRESCRIPTION_REFILL_REQUEST",
#   "internalnote": "AI REFILL AGENT REQUEST\nMedication: {medication_name} {medication_dose}\nPharmacy: {pharmacy_name} {pharmacy_location}\nPatient Notes: {patient_notes}\nCall Recording: {call_recording_url}\nProcessed: {timestamp}\nAll eligibility checks PASSED.",
#   "providerid": "{prescribing_provider_id}"
# }

# --- Generic FHIR R4 ---
# POST /api/FHIR/R4/Task
# Body: {
#   "resourceType": "Task",
#   "status": "requested",
#   "intent": "order",
#   "priority": "routine",
#   "code": { "coding": [{ "system": "http://terminology.hl7.org/CodeSystem/task-code", "code": "refill" }] },
#   "description": "AI-Processed Refill: {medication_name} {medication_dose}",
#   "for": { "reference": "Patient/{patient_id}" },
#   "requester": { "display": "AI Refill Agent v1.0" },
#   "owner": { "reference": "Practitioner/{prescribing_provider_id}" },
#   "input": [
#     { "type": { "text": "medication" }, "valueString": "{medication_name} {medication_dose}" },
#     { "type": { "text": "pharmacy" }, "valueString": "{pharmacy_name} - {pharmacy_location}" },
#     { "type": { "text": "patient_notes" }, "valueString": "{patient_notes}" },
#     { "type": { "text": "call_recording" }, "valueString": "{call_recording_url}" },
#     { "type": { "text": "eligibility_flags" }, "valueString": "{comma_separated_flags}" }
#   ]
# }

# Step 6: Patient Confirmation SMS
# Action: Send SMS via Twilio (through Keragon Twilio connector)
# To: {patient_phone}
# Body: "{PRACTICE_NAME}: Your refill request for {medication_name} has been submitted to your provider for approval. Once approved, it will be sent to {pharmacy_name}. Expected processing time: {TURNAROUND_TIME}. Do not reply to this message."
# Note: Keep SMS HIPAA-safe — minimal PHI, medication name is acceptable as patient initiated the request

# Step 7: Audit Log Entry
# Action: Write to audit log
# {
#   "event": "refill_request_processed",
#   "timestamp": "{utc_timestamp}",
#   "call_id": "{call_id}",
#   "patient_id": "{patient_id}",
#   "medication": "{medication_name}",
#   "eligibility_result": "approved" | "escalated",
#   "escalation_reason": "{reason or null}",
#   "ehr_task_id": "{created_task_id}",
#   "sms_sent": true/false,
#   "processing_duration_ms": {elapsed_time}
# }

# CONTROLLED SUBSTANCE REFERENCE DATA
# Version: 1.0
# Last Updated: 2025-01-15
# Source: DEA Controlled Substances Schedules
# Usage: Import into Retell AI Knowledge Base AND Keragon workflow variable

{
  "version": "1.0",
  "last_updated": "2025-01-15",
  "schedules": {
    "II": {
      "description": "High potential for abuse; severe dependence",
      "action": "IMMEDIATE_ESCALATION",
      "medications": [
        {"generic": "oxycodone", "brands": ["oxycontin", "roxicodone", "xtampza"]},
        {"generic": "hydrocodone", "brands": ["vicodin", "norco", "lortab", "zohydro"]},
        {"generic": "oxycodone/acetaminophen", "brands": ["percocet", "endocet"]},
        {"generic": "morphine", "brands": ["ms contin", "kadian", "avinza"]},
        {"generic": "fentanyl", "brands": ["duragesic", "subsys", "actiq", "abstral"]},
        {"generic": "hydromorphone", "brands": ["dilaudid", "exalgo"]},
        {"generic": "methadone", "brands": ["dolophine", "methadose"]},
        {"generic": "meperidine", "brands": ["demerol"]},
        {"generic": "amphetamine/dextroamphetamine", "brands": ["adderall", "adderall xr"]},
        {"generic": "methylphenidate", "brands": ["ritalin", "concerta", "daytrana", "quillivant"]},
        {"generic": "lisdexamfetamine", "brands": ["vyvanse"]},
        {"generic": "dextroamphetamine", "brands": ["dexedrine", "zenzedi"]},
        {"generic": "methamphetamine", "brands": ["desoxyn"]},
        {"generic": "tapentadol", "brands": ["nucynta"]},
        {"generic": "cocaine", "brands": []},
        {"generic": "pentobarbital", "brands": ["nembutal"]},
        {"generic": "secobarbital", "brands": ["seconal"]}
      ]
    },
    "III": {
      "description": "Moderate potential for abuse; moderate dependence",
      "action": "IMMEDIATE_ESCALATION",
      "medications": [
        {"generic": "acetaminophen/codeine", "brands": ["tylenol 3", "tylenol with codeine"]},
        {"generic": "buprenorphine", "brands": ["subutex"]},
        {"generic": "buprenorphine/naloxone", "brands": ["suboxone", "zubsolv"]},
        {"generic": "ketamine", "brands": ["ketalar"]},
        {"generic": "testosterone", "brands": ["androgel", "testim", "depo-testosterone", "axiron"]},
        {"generic": "nandrolone", "brands": ["deca-durabolin"]},
        {"generic": "oxandrolone", "brands": ["oxandrin"]},
        {"generic": "benzphetamine", "brands": ["didrex"]},
        {"generic": "phendimetrazine", "brands": ["bontril"]}
      ]
    },
    "IV": {
      "description": "Low potential for abuse; limited dependence",
      "action": "IMMEDIATE_ESCALATION",
      "medications": [
        {"generic": "alprazolam", "brands": ["xanax", "xanax xr"]},
        {"generic": "diazepam", "brands": ["valium"]},
        {"generic": "clonazepam", "brands": ["klonopin"]},
        {"generic": "lorazepam", "brands": ["ativan"]},
        {"generic": "temazepam", "brands": ["restoril"]},
        {"generic": "triazolam", "brands": ["halcion"]},
        {"generic": "midazolam", "brands": ["versed"]},
        {"generic": "zolpidem", "brands": ["ambien", "ambien cr", "edluar", "intermezzo"]},
        {"generic": "eszopiclone", "brands": ["lunesta"]},
        {"generic": "zaleplon", "brands": ["sonata"]},
        {"generic": "tramadol", "brands": ["ultram", "ultracet", "conzip"]},
        {"generic": "carisoprodol", "brands": ["soma"]},
        {"generic": "phenobarbital", "brands": ["luminal"]},
        {"generic": "modafinil", "brands": ["provigil"]},
        {"generic": "armodafinil", "brands": ["nuvigil"]},
        {"generic": "phentermine", "brands": ["adipex-p", "lomaira"]},
        {"generic": "suvorexant", "brands": ["belsomra"]},
        {"generic": "lemborexant", "brands": ["dayvigo"]}
      ]
    },
    "V": {
      "description": "Lowest potential for abuse",
      "action": "IMMEDIATE_ESCALATION",
      "medications": [
        {"generic": "pregabalin", "brands": ["lyrica", "lyrica cr"]},
        {"generic": "lacosamide", "brands": ["vimpat"]},
        {"generic": "brivaracetam", "brands": ["briviact"]},
        {"generic": "cenobamate", "brands": ["xcopri"]},
        {"generic": "codeine cough syrup", "brands": ["promethazine with codeine", "robitussin ac"]},
        {"generic": "diphenoxylate/atropine", "brands": ["lomotil"]}
      ]
    }
  },
  "matching_rules": {
    "case_sensitive": false,
    "match_type": "fuzzy",
    "max_levenshtein_distance": 2,
    "match_against": ["generic", "brands"],
    "partial_match": true,
    "notes": "Match any substring — e.g., patient saying 'my xanax' should match 'xanax'. Also match common misspellings and phonetic variations."
  }
}

# Routes escalated requests to clinical staff with full context

# KERAGON WORKFLOW: Escalation Handler
# Trigger: Called by Refill Eligibility Engine or directly by Retell AI transfer event
# Purpose: Route escalated requests to clinical staff with full context

# Workflow Name: handle_escalation
# Trigger Type: Internal workflow call OR Webhook

# --- INPUT SCHEMA ---
# {
#   "escalation_type": "controlled_substance" | "adverse_effects" | "unverified_patient" | "unapproved_medication" | "no_active_prescription" | "too_early_refill" | "overdue_visit" | "patient_requested_human" | "system_error" | "ai_comprehension_failure",
#   "call_id": "string",
#   "call_recording_url": "string",
#   "patient_id": "string or null",
#   "patient_name": "string",
#   "patient_phone": "string",
#   "medication_name": "string or null",
#   "additional_context": "string or null",
#   "timestamp": "ISO 8601 string"
# }

# --- ESCALATION ROUTING MATRIX ---
# Configure per practice:

# ROUTING_CONFIG = {
#   "controlled_substance": {
#     "priority": "high",
#     "route_to": "clinical_nurse",
#     "notification_method": ["sms", "ehr_task"],
#     "sla_minutes": 60,
#     "ehr_task_priority": "urgent"
#   },
#   "adverse_effects": {
#     "priority": "urgent",
#     "route_to": "provider",
#     "notification_method": ["sms", "ehr_task", "email"],
#     "sla_minutes": 30,
#     "ehr_task_priority": "urgent"
#   },
#   "unverified_patient": {
#     "priority": "normal",
#     "route_to": "front_desk",
#     "notification_method": ["ehr_task"],
#     "sla_minutes": 240,
#     "ehr_task_priority": "routine"
#   },
#   "unapproved_medication": {
#     "priority": "normal",
#     "route_to": "clinical_nurse",
#     "notification_method": ["ehr_task"],
#     "sla_minutes": 120,
#     "ehr_task_priority": "routine"
#   },
#   "no_active_prescription": {
#     "priority": "normal",
#     "route_to": "provider",
#     "notification_method": ["ehr_task"],
#     "sla_minutes": 240,
#     "ehr_task_priority": "routine"
#   },
#   "too_early_refill": {
#     "priority": "high",
#     "route_to": "clinical_nurse",
#     "notification_method": ["sms", "ehr_task"],
#     "sla_minutes": 60,
#     "ehr_task_priority": "urgent"
#   },
#   "overdue_visit": {
#     "priority": "normal",
#     "route_to": "clinical_nurse",
#     "notification_method": ["ehr_task"],
#     "sla_minutes": 240,
#     "ehr_task_priority": "routine"
#   },
#   "patient_requested_human": {
#     "priority": "normal",
#     "route_to": "front_desk",
#     "notification_method": ["none_realtime_transfer"],
#     "sla_minutes": 0,
#     "ehr_task_priority": null
#   },
#   "system_error": {
#     "priority": "critical",
#     "route_to": "msp_support",
#     "notification_method": ["email", "sms"],
#     "sla_minutes": 15,
#     "ehr_task_priority": null
#   },
#   "ai_comprehension_failure": {
#     "priority": "normal",
#     "route_to": "front_desk",
#     "notification_method": ["ehr_task"],
#     "sla_minutes": 120,
#     "ehr_task_priority": "routine"
#   }
# }

# --- WORKFLOW STEPS ---

# Step 1: Look up routing config for escalation_type
# Step 2: Create EHR task (if configured)
#   POST to EHR task API with appropriate priority and assignee
#   Include in task description:
#   - Escalation reason
#   - Patient name and ID
#   - Medication requested
#   - Link to call recording
#   - Additional context from AI agent
#   - Timestamp

# Step 3: Send SMS notification (if configured)
#   To: Designated clinical staff phone number per route_to config
#   Body: "[REFILL ESCALATION - {priority}] Patient: {patient_name}. Reason: {escalation_type}. Medication: {medication_name}. Call recording available in EHR task. Please respond within {sla_minutes} minutes."

# Step 4: Send email notification (if configured)
#   To: Designated email per route_to config
#   Subject: "[AI Refill Escalation] {patient_name} - {escalation_type}"
#   Body: Full escalation details including call transcript excerpt

# Step 5: Send MSP alert for system errors
#   If escalation_type == "system_error":
#   Send to MSP monitoring system (email, PagerDuty, or ConnectWise ticket)
#   Include: error details, affected patient count, suggested remediation

# Step 6: Patient notification
#   If patient was NOT transferred in real-time:
#   SMS to patient: "Your refill request requires additional review by our clinical staff. Someone will contact you within {sla_hours} hours. If this is urgent, please call {PRACTICE_MAIN_NUMBER}."

# Step 7: Audit log
#   Log all escalation details, routing decisions, and notification timestamps

# --- SLA MONITORING (Keragon scheduled check) ---
# Create a separate scheduled workflow that runs every 30 minutes:
# Query open escalation tasks in EHR
# For any task exceeding its SLA:
#   Send reminder notification to route_to staff
#   After 2x SLA: escalate to practice manager
#   After 3x SLA: alert MSP support

# Workflow Name: generate_operations_report

# --- DAILY REPORT STEPS ---

GET https://api.retellai.com/v1/analytics
Parameters: date_from={yesterday}, date_to={yesterday}, agent_id={agent_id}

completion_rate = completed_calls / total_calls * 100
escalation_rate = escalations_total / total_calls * 100
automation_rate = refills_processed / total_calls * 100
cost_per_refill = total_cost / refills_processed
estimated_savings = refills_processed * $11 - total_cost
daily_staff_hours_saved = refills_processed * 4.5 / 60

# ========================================
# AI PRESCRIPTION REFILL DAILY REPORT
# {PRACTICE_NAME} | {DATE}
# ========================================
#
# CALL VOLUME
# Total Calls: {total_calls}
# Completed: {completed_calls} ({completion_rate}%)
# Transferred to Staff: {transferred_calls}
# Abandoned: {abandoned_calls}
#
# REFILL PROCESSING
# Successfully Routed to Provider: {refills_processed}
# Automation Rate: {automation_rate}%
# Average Processing Time: {avg_time}s
#
# ESCALATIONS
# Total Escalations: {escalations_total} ({escalation_rate}%)
# - Controlled Substances: {N}
# - Adverse Effects: {N}
# - No Active Rx: {N}
# - Unapproved Medication: {N}
# - Patient Requested Human: {N}
# - Other: {N}
#
# COST & SAVINGS
# AI Platform Cost: ${total_cost}
# Cost per Refill: ${cost_per_refill}
# Estimated Manual Cost (at $11/refill): ${manual_cost}
# Estimated Daily Savings: ${estimated_savings}
# Staff Hours Saved: {hours_saved} hours
#
# ERRORS / ISSUES
# System Errors: {errors}
# [List any error details]
#
# ========================================
# Generated by AI Operations Agent | MSP: {MSP_NAME}
# ========================================