Tencent Cloud ADPJan 13, 2026

Hospital Intelligent Triage: Multi-Intent AI

One Agent for location queries and medical consultation. Auto-route by intent, collect patient info, recommend departments and doctors.

01-hero-hospital-triage-journey.png

Executive Summary

Hospital outpatient lobbies face two high-frequency question types daily: "Where is XX examination/service?" and "What department should I visit for my symptoms?" Traditional solutions involve multiple triage nurses working in shifts, but peak hours still see long queues, low efficiency, and inevitable nurse fatigue.

This article demonstrates how to build an Intelligent Triage Agent using Tencent Cloud ADP, leveraging multi-intent recognition to automatically identify patient needs and route to different workflows:

  • Location Query: Directly output location guidance for examination rooms/service windows
  • Medical Consultation: Collect age, gender, and symptoms โ†’ Recommend department โ†’ Check if appointment needed โ†’ Recommend on-duty doctors

Key Highlights:

  • Multi-intent recognition covering multiple scenario types with one Agent
  • Slot-filling mechanism ensuring complete information collection
  • Knowledge base maintains weekly schedules for doctor recommendations

1. Scenario Analysis: Two Core Needs at Triage Desks

1.1 Demand Distribution

Analysis of one week's triage records at a hospital outpatient lobby shows patient inquiries mainly fall into two categories:

Need TypePercentageTypical Questions
Location Queries~40%"Where is the CT room?" "Which floor for blood tests?" "How to get to insurance window?"
Medical Consultation~30%"What department for headaches?" "Which doctor for my child's fever?" "Any slots in orthopedics today?"
02-problem-distribution-healthcare.png

1.2 Traditional Pain Points

Pain PointManifestation
Repetitive WorkTriage nurses answer countless "Where is XX" questions daily
Inaccurate GuidanceHigh pressure during peak hours leads to occasional errors
Difficult LookupNurses struggle to check which doctors are on duty and slot availability
Peak CongestionSevere queuing from 8-10 AM, increasing patient anxiety

2. Agent Design: Multi-Intent Recognition + Routing

2.1 Overall Architecture

                        Patient Question
                              โ†“
                    โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
                    โ”‚ Multi-Intent        โ”‚
                    โ”‚ Recognition         โ”‚
                    โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                               โ†“
            โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ดโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
            โ†“                                     โ†“
    โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”                     โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
    โ”‚ Location      โ”‚                     โ”‚ Medical       โ”‚
    โ”‚ Query Flow    โ”‚                     โ”‚ Consultation  โ”‚
    โ”‚ Direct Output โ”‚                     โ”‚ Collect Info  โ”‚
    โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜                     โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                                                  โ†“
                                          โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
                                          โ”‚ Recommend     โ”‚
                                          โ”‚ Department    โ”‚
                                          โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                                                  โ†“
                                          โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
                                          โ”‚ Need          โ”‚
                                          โ”‚ Appointment?  โ”‚
                                          โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”ฌโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                                                  โ†“
                                          โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
                                          โ”‚ Recommend     โ”‚
                                          โ”‚ On-Duty Doctorโ”‚
                                          โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
03-hospital-ai-architecture.png

2.2 Multi-Intent Recognition

The Agent first determines which category the patient's question belongs to:

Intent TypeRecognition Keywords/PatternsProcessing Flow
Location Query"where is" "how to get to" "which floor" "which window"Directly query and output location info
Medical ConsultationSymptom descriptions, "what department" "which doctor" "any slots"Enter consultation workflow

Example Dialogues:

Patient: Which floor is the CT room on?
Agent: Based on your query, please go to B1 Floor, Imaging Diagnostic Center, CT Room.

Patient: I've been having headaches lately
Agent: To recommend the right department, please tell me:
1. What is your age?
2. What is your gender?

2.3 Medical Consultation Flow Details

When identified as "Medical Consultation" intent, the Agent enters the information collection flow:

Step 1: Collect Basic Information (Slot Filling)

Required InfoPurposeExample Question
AgeDifferent age groups have different common conditions"What is your age?"
GenderSome departments are gender-related"What is your gender?"
SymptomsCore basis for recommendation"Please describe your main symptoms"

Step 2: Recommend Department

Based on collected information and preset triage rules, recommend the best-matching department:

Patient: I'm 18, male, my eyes are itchy and I can't see clearly.
Agent: Based on your symptoms, please go to 5th Floor, ENT & Oral Center, Ophthalmology Department for treatment.

Step 3: Check Appointment Need

After recommending a department, the Agent proactively asks about appointment needs:

  • If patient says yes โ†’ Enter doctor recommendation flow
  • If patient says no โ†’ End conversation or ask about other questions

Step 4: Recommend On-Duty Doctors

Query the department's schedule for the day and recommend available doctors:

Agent: Based on your symptoms, today you can register with Dr. Zhang, Chief Physician, at 5th Floor Area A, Ophthalmology Clinic.
04-symptom-assessment-workflow.png

3. Building with Tencent Cloud ADP

3.1 Create Agent and Configure Role

Role Configuration (Example):

You are an intelligent triage assistant for a hospital, helping patients with two types of questions:
1. Location queries: Provide specific locations for examination rooms and service windows
2. Medical consultation: Collect patient information and recommend appropriate departments and doctors

Important rules:
- You only provide triage services, no medical diagnosis
- Must collect age, gender, and symptoms before recommending departments

3.2 Configure Knowledge Bases

Location Information Knowledge Base (Example):

Department/ServiceLocation
CT Room2F East, Outpatient Building
Blood Test Room1F West, Outpatient Building
Insurance Window1F Lobby, Outpatient Building
Pharmacy1F North, Outpatient Building
......

Schedule Information Knowledge Base (Example):

DoctorMonTueWedThuFriSatSun
Zhang (Chief)AMAMOffAMAMAMOff
Wang (Attending)PMOffAMAMPMOffPM
Li (Attending)AMAMAMAMAMAMOff
Liu (Resident)PMAMAMPMAMOffOff
.........

3.4 Configure Workflow

Intent Recognition Node:

  • Input: Patient question
  • Output: Intent type (Location Query / Medical Consultation)

Location Query Node:

  • Input: Query content
  • Process: Search location knowledge base
  • Output: Location guidance

Medical Consultation Node:

  • Input: Patient question
  • Process: Slot filling (age, gender, symptoms) โ†’ Triage rule matching โ†’ Department recommendation
  • Output: Recommended department + appointment need check

Doctor Recommendation Node:

  • Input: Department name
  • Process: Search schedule knowledge base
  • Output: Today's on-duty doctor recommendation
05-multimodal-interaction-hospital.png

4. Dialogue Examples

4.1 Location Query Scenario

Patient: Where is the parking lot?

Agent: Based on your query, please go to B2 Floor, Patient Parking Lot.

4.2 Medical Consultation Scenario (Complete Flow)

Patient: I've been having stomach pain lately

Agent: Please provide a valid age.
       Please specify your gender (male/female).

Patient: 28

Agent: Please specify your gender (male/female).

Patient: Female

Agent: Based on your symptoms, today you should go to 2nd Floor, Internal Medicine Clinic Cluster, Gastroenterology Department for further treatment.

Patient: Which doctor can I register with?

Agent: Based on your symptoms, today you can register with Dr. Zhang, Chief Physician, at 2nd Floor Internal Medicine Clinic Cluster, Gastroenterology Department.

5. Compliance & Boundaries

5.1 Strict Red Lines

Prohibited ActionExplanation
Disease DiagnosisCannot say "You have XX disease"
Treatment AdviceCannot say "You should take XX medication"
Condition AssessmentCannot say "Your condition is serious/not serious"

5.2 Emergency Handling

When urgent symptoms are detected, direct to emergency immediately:

Patient: I suddenly have high fever and joint pain

Agent: Please provide a valid age.
       Please specify your gender (male/female).

Patient: 19, male

Agent: Based on your symptoms, today you can register with Dr. Zhang, Chief Physician, at 1st Floor Emergency Department.
06-medical-compliance-boundaries.png

6. Results

6.1 Core Metrics

MetricTargetActual
Intent Recognition Accuracyโ‰ฅ90%93.5%
Department Recommendation Accuracyโ‰ฅ85%88.2%
Average Response Timeโ‰ค3s1.8s
Patient Satisfactionโ‰ฅ4.0/5.04.4/5.0

6.2 Business Value

Value PointImprovement
Triage desk queue timeReduced 50%
Nurse repetitive Q&A workloadReduced 65%
Patient department-finding timeFrom 8 min to 2 min
24/7 service coverage80% night consultation resolution
07-patient-satisfaction-metrics.png

7. Extension Directions

7.1 Feature Extensions

ExtensionDescription
Examination BookingIntegrate with booking system for examination appointments
Report QueryIntegrate with lab system for report interpretation (values only, no diagnosis)
Insurance ConsultationAdd insurance policy knowledge base
Multi-languageSupport English, Cantonese, and other languages

7.2 Multi-Modal Interaction

Interaction MethodUse Case
TouchscreenSelf-service kiosks in outpatient lobby
Voice InteractionElderly patients, visually impaired
Mini-programYounger patients, advance consultation
08-extended-applications-roadmap.png

Summary

This article demonstrated how to build a hospital intelligent triage assistant using Tencent Cloud ADP. The core design principles are:

  1. Multi-Intent Recognition: One Agent covering "Location Query", "Appointment Query", and "Medical Consultation" scenarios
  2. Slot Filling: Ensure collection of age, gender, and symptoms for medical consultations
  3. Routing: Location queries output directly; medical consultations follow complete flow
  4. System Integration: Connect with scheduling system for real-time doctor recommendations
  5. Compliance First: Strictly distinguish triage service from medical diagnosis

Start now and build your intelligent triage assistant with Tencent Cloud ADP!

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