Core Components

Patient

Every healthcare journey begins with a person - the patient. This component captures who they are, where they live, and important personal information that helps healthcare providers give them the best care possible.

Think of the patient record as the foundation of everything else. It's like the cover page of a medical file that tells you who this person is, how to contact them, and important details about their identity and background.

Data Model

Field	Type	Description
code	string	Unique identifier for this patient in the system
surname	string	Patient's family name
name	string	Patient's given name
sex	string	Patient's biological sex (M/F)
birthdate	date	Patient's date of birth
phone	string	Patient's contact number
nationality	string	Patient's nationality
disabilities	array of strings	Any disabilities the patient has
occupation	string	Patient's job or profession
marital_status	string	Patient's marital status
photos	array of strings	URLs to patient photos (for identification)
address	object	Where the patient lives (detailed address)
identifications	array of objects	ID cards, passports, etc.
death_date	datetime	Date of death (if applicable)
spid	string	Social Protection ID (for benefit programs)
created_at	datetime	When this record was created
updated_at	datetime	When this record was last updated

Address Model

Cambodia uses a specific address structure based on NCDD standards:

Field	Type	Description
province	object	Province information (code and name)
district	object	District information (code and name)
commune	object	Commune information (code and name)
village	object	Village information (code and name)
house_number	string	House number
street_number	string	Street number
location	string	Additional location details

Example

{  
  "patient": {  
    "code": "P25003877",  
    "surname": "សៅ",  
    "name": "សុវ៉ាន់",  
    "sex": "M",  
    "birthdate": "1980-05-15",  
    "phone": "+855 12 345 678",
    "nationality": "Cambodian",  
    "disabilities": ["Hearing impairment"],  
    "occupation": "Teacher",  
    "marital_status": "Married",  
    "photos": ["https://hospital.example/photos/PT20250317001_1.jpg"],  
    "address": {  
      "province": {  
        "code": "12",  
        "name": "Phnom Penh"  
      },  
      "district": {  
        "code": "1201",  
        "name": "Chamkar Mon"  
      },  
      "commune": {  
        "code": "120101",  
        "name": "Tonle Bassac"  
      },  
      "village": {  
        "code": "12010101",  
        "name": "Phsar Deum Thkov"  
      },  
      "house_number": "45",  
      "street_number": "302",  
      "location": "Near Central Market"  
    },  
    "identifications": [  
      {  
        "patient_code": "P25003877",  
        "card_code": "ID123456789",  
        "card_type": "National ID"  
      }  
    ],  
    "death_date": null,
    "spid": "250317001",  
    "created_at": "2025-03-17T08:30:00.000+07:00",  
    "updated_at": "2025-03-17T08:30:00.000+07:00"  
  }  
}

Visit

A visit is like opening a new chapter in the patient's medical story. It represents their entire stay at the hospital - from the moment they walk in (or are brought in) until they leave.

Every visit has a beginning and an end, and everything that happens in between gets connected to this visit. Think of it as the "container" that holds all the medical care, tests, treatments, and interactions that occur during this particular trip to the hospital.

Data Model

Field	Type	Description
health_facility_code	string	Which hospital or clinic this visit is at
patient_code	string	Which patient this visit belongs to
code	string	Unique identifier for this specific visit
admission_type	string	How the patient arrived (Walk-in, Appointment, Referral)
discharge_type	string	How the patient left (Authorized, Refer Out, etc.)
visit_outcome	string	Patient's condition when leaving (Improved, Recovered, etc.)
visit_type	string	Type of care (IPD for inpatient, OPD for outpatient)
admitted_at	datetime	When the patient arrived
discharged_at	datetime	When the patient left
followup_at	datetime	When they should return for follow-up
created_at	datetime	When this record was created
updated_at	datetime	When this record was last updated

Example

{  
  "visits": [  
    {  
      "health_facility_code": "121020",  
      "patient_code": "P25003877",  
      "code": "V420650",  
      "admission_type": "Walk-in",  
      "discharge_type": "Authorized",  
      "visit_outcome": "Improved",  
      "visit_type": "OPD",  
      "admitted_at": "2025-03-17T09:30:00.000+07:00",  
      "discharged_at": "2025-03-17T10:45:00.000+07:00",  
      "followup_at": "2025-03-24T09:00:00.000+07:00",  
      "created_at": "2025-03-17T09:30:00.000+07:00",  
      "updated_at": "2025-03-17T10:45:00.000+07:00"  
    }
  ]  
}

Triage

Triage is like the "first impression" of the patient's visit. When someone arrives at the hospital, a nurse or healthcare worker quickly assesses them to understand: How urgent is their condition? What are their main complaints? What are their basic vital measurements?

This is where the patient's story begins to unfold. The triage nurse asks "What brings you here today?" and records the patient's chief complaint - the main reason they came to the hospital.

Data Model

Field	Type	Description
patient_code	string	Which patient this triage belongs to
visit_code	string	Which visit this triage is part of
encounter_code	string	Reference to encounter (usually itself)
code	string	Unique identifier for this triage
chief_complaint	text	Patient's main complaint in their own words
height	number	Patient's height in centimeters
weight	number	Patient's weight in kilograms
recorded_at	datetime	When this triage was done
recorded_by	string	Name of the healthcare provider
title	string	Provider's role (Doctor, Nurse, etc.)

Example

{  
  "triages": [{  
    "visit_code": "V420650",
    "encounter_code": "P25003877",  
    "code": "TR250317",  
    "chief_complaint": "Periodic fever with chills for 3 days",  
    "height": 170,  
    "weight": 65,  
    "recorded_at": "2025-03-17T09:32:00.000+07:00",  
    "recorded_by": "Khun Srey Mom",
    "title": "Nurse"
  }]  
}

Vital Signs

Vital signs are like taking a snapshot of how the patient's body is functioning right now. These are the basic measurements that tell healthcare providers if the patient is stable, in distress, or needs immediate attention.

Think of vital signs as the body's "dashboard" - just like a car's dashboard shows speed, fuel level, and engine temperature, vital signs show the body's key functions: heart rate, blood pressure, temperature, breathing rate, and oxygen levels.

Normal Ranges Reference

Vital Sign	Normal Range	Units
Temperature	36.5-37.3 °C	°C
Heart Rate	60-100 beats per minute	/min
Respiratory Rate	12-20 breaths per minute	/min
Blood Pressure	Systolic: 90-120, Diastolic: 60-80	mmHg
Oxygen Saturation	95-100%	%
Blood Glucose	Fasting: 70-99, Random: < 140	mg/dL

Data Model

Field	Type	Description
encounter_code	string	Which encounter these vital signs were taken during
recorded_at	datetime	When these measurements were taken
recorded_by	string	Who took these measurements
title	string	Their role (Doctor, Nurse, etc.)
observations	array of objects	The actual vital sign measurements

Example

{  
  "vital_signs": [  
    {
      "encounter_code": "E417001",  
      "recorded_at": "2025-03-17T09:40:00.000+07:00",  
      "recorded_by": "Khun Srey Mom",
      "title": "Nurse",  
      "observations": [  
        {  
          "name": "Systolic Blood Pressure",  
          "value": 135
        },  
        {  
          "name": "Diastolic Blood Pressure",  
          "value": 85
        },  
        {  
          "name": "Heart Rate",  
          "value": 92
        },  
        {  
          "name": "Temperature",  
          "value": 38.7
        },  
        {  
          "name": "Blood Oxygen",  
          "value": 97
        }
      ]  
    }  
  ]  
}

Medical History

Medical history is like reading the previous chapters of the patient's health story. Before treating someone, doctors need to know: What health problems have they had before? What medications are they taking? Are they allergic to anything? What runs in their family?

This information helps doctors understand the full picture and make better decisions about treatment.

History Categories

Category	What It Includes
Current Illness	What's happening now - symptoms, when they started, what makes them better or worse
Current Medications	What medicines the patient is taking right now
Past Medical History	Previous illnesses, hospitalizations, chronic conditions
Past Surgical History	Any surgeries the patient has had
Allergies	Things the patient is allergic to (foods, medicines, etc.)
Immunizations	Vaccinations the patient has received
Family History	Health problems that run in the family
Social History	Lifestyle factors like smoking, drinking, occupation

Data Model

Field	Type	Description
patient_code	string	Which patient this history belongs to
visit_code	string	Which visit this was recorded during
encounter_code	string	Which encounter this was discussed in
name	string	Category of history (from table above)
value	array of strings	List of relevant information for this category

Example

{  
  "medical_histories": [  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",  
      "encounter_code": "E417001",  
      "name": "Current Illness History",  
      "value": [  
        "Patient reports high fever with chills occurring every 48 hours, accompanied by headache and joint pain. Symptoms started 3 days ago after returning from a trip to Mondulkiri province."  
      ]  
    },  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",  
      "encounter_code": "E417001",  
      "name": "Allergies",  
      "value": [  
        "Penicillin",
        "Shellfish"
      ]  
    },  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",  
      "encounter_code": "E417001",  
      "name": "Family History",  
      "value": [  
        "Mother with diabetes",  
        "Father with hypertension"  
      ]  
    }
  ]  
}

Physical Examination

Physical examination is where the doctor becomes a detective, using their senses to gather clues about what's wrong with the patient. They look, listen, feel, and sometimes smell to understand what's happening inside the patient's body.

This is hands-on medicine - the doctor examines different parts of the body systematically, from head to toe, looking for signs of illness or injury.

Examination Areas

Body System	What Doctors Check
General Appearance	How the patient looks overall - alert, distressed, well-nourished
Head & Neck	Eyes, ears, nose, throat, neck lymph nodes
Heart & Lungs	Heart sounds, breathing sounds, chest movement
Abdomen	Belly tenderness, organ size, bowel sounds
Skin	Rashes, color changes, wounds
Nervous System	Reflexes, coordination, mental status
Muscles & Joints	Strength, movement, swelling

Data Model

Field	Type	Description
patient_code	string	Which patient was examined
visit_code	string	Which visit this examination was part of
encounter_code	string	Which encounter this examination occurred during
name	string	Which body system or area was examined
value	various	What the doctor found
value_type	string	Type of finding (text, complex data, etc.)
value_unit	string	Unit of measurement (if applicable)

Example

{  
  "physical_examinations": [  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",  
      "encounter_code": "E417001",  
      "name": "General Appearance",  
      "value": "Patient appears ill and tired, with intermittent shivering",  
      "value_type": "text",  
      "value_unit": null  
    },  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",  
      "encounter_code": "E417001",  
      "name": "Skin",  
      "value": "Warm to touch, slightly yellow color (jaundiced), no rash visible",  
      "value_type": "text",  
      "value_unit": null  
    }
  ]  
}

Laboratories

Laboratory tests are like sending samples to a detective lab to uncover hidden clues about the patient's condition. Blood, urine, and other samples are analyzed to reveal information that can't be seen with the naked eye.

These tests can confirm what doctors suspect, rule out certain conditions, or sometimes reveal unexpected findings that change the entire treatment plan.

Data Model

Field	Type	Description
patient_code	string	Which patient these tests belong to
visit_code	string	Which visit these tests were ordered during
encounter_code	string	Which encounter prompted these tests
request_code	string	Unique identifier for this lab request
requested_at	datetime	When the tests were ordered
requested_by	string	Which doctor ordered the tests
title	string	Doctor's role
results	array of objects	The test results

Result Model

Field	Type	Description
name	string	Name of the test
category	string	Type of test (Hematology, Chemistry, etc.)
value	various	The test result
value_type	string	Type of result (number, text, etc.)
value_unit	string	Unit of measurement
reference_range	string	Normal range for this test
interpretation	string	Is it normal, high, low?
verified_by	string	Lab technician who verified the result
recorded_by	string	Who entered the result

Example

{  
  "laboratories": [  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",  
      "encounter_code": "E417001",
      "request_code": "L7001",  
      "requested_at": "2025-03-17T10:30:00.000+07:00",  
      "requested_by": "Dr. Chhun Sovannarith",  
      "title": "Doctor",  
      "results": [  
        {  
          "name": "Malaria Blood Smear",  
          "category": "Parasitology",  
          "value": "Positive for P. falciparum",  
          "value_type": "string",  
          "value_unit": null,  
          "reference_range": "Negative",  
          "interpretation": "Positive - Malaria parasites found",  
          "verified_by": "Dr. Meas Chenda",  
          "recorded_by": "Lab Tech Chandaravuth"  
        },  
        {  
          "name": "Hemoglobin",  
          "category": "Hematology",  
          "value": 11.2,  
          "value_type": "float",  
          "value_unit": "g/dL",  
          "reference_range": "13.5-17.5",  
          "interpretation": "Low - Below normal range",  
          "verified_by": "Dr. Meas Chenda",  
          "recorded_by": "Lab Tech Chandaravuth"  
        }  
      ]  
    }  
  ]  
}

Diagnosis

Diagnosis is the moment when all the pieces of the puzzle come together. After listening to the patient, examining them, and reviewing test results, the doctor determines what's wrong. This is the "answer" to the medical mystery.

Sometimes there's one clear diagnosis, sometimes there are multiple conditions, and sometimes doctors need to consider several possibilities (differential diagnosis).

Diagnosis Types

Type	When It's Used
Primary	The main reason for this hospital visit
Secondary	Other conditions that also need attention
Differential	Possible diagnoses being considered
Admission	Initial diagnosis when patient arrives
Discharge	Final diagnosis when patient leaves

Data Model

Field	Type	Description
patient_code	string	Which patient this diagnosis belongs to
visit_code	string	Which visit this diagnosis was made during
encounter_code	string	Which encounter this diagnosis was determined in
diagnosis_type	string	Type of diagnosis (Primary, Secondary, etc.)
diagnosis_code	string	ICD-10 medical code for this condition
diagnosis_name	string	Name of the condition
diagnosis_description	string	More detailed description
diagnosed_at	datetime	When this diagnosis was made
diagnosed_by	string	Which doctor made this diagnosis

Example

{  
  "diagnoses": [  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",  
      "encounter_code": "E317001",  
      "diagnosis_type": "Primary",  
      "diagnosis_code": "B50.9",  
      "diagnosis_name": "Plasmodium falciparum malaria, unspecified",  
      "diagnosis_description": "Malaria caused by P. falciparum parasites, confirmed by blood smear",  
      "diagnosed_at": "2025-03-17T10:05:00.000+07:00",  
      "diagnosed_by": "Dr. Chhun Sovannarith"  
    }  
  ]  
}

Prescriptions

Updated on 2026-03-06

Prescriptions are the doctor's treatment plan written down as specific medications. After diagnosing the problem, the doctor decides which medicines will help the patient get better.

Some medications are given at the hospital during treatment, while others are prescribed for the patient to take at home. Each prescription includes detailed instructions on how much to take, when to take it, and for how long.

Data Model

Field	Type	Description
patient_code	string	Which patient this prescription is for
visit_code	string	Which visit this prescription was written during
encounter_code	string	Which encounter prompted this prescription
code	string	Unique identifier for this prescription
prescribed_at	datetime	When this prescription was written
prescribed_by	string	Which doctor wrote this prescription
title	string	Doctor's role
medications	array of objects	List of prescribed medications

Medication Model

Field	Type	Description
medicine_code	string	Unique identifier for this medication
medicine_name	string	Name of the medicine
strength	string	How strong the medicine is (e.g., "500mg")
form	string	What form it comes in (tablet, syrup, injection)
method	string	How to take it (oral, injection, topical)
unit	string	Unit of measurement
morning	numeric	How many to take in the morning
afternoon	numeric	How many to take in the afternoon
evening	numeric	How many to take in the evening
night	numeric	How many to take at night
days	integer	How many days to take this medicine
interval	string	How often to take it (e.g., "every 8 hours")
note	text	Special instructions
dispense	object	Optional Total quantity dispensed to the patient

Dispense Field

The dispense object contains:

• quantity (number): Total amount dispensed
• unit (string): Unit of measurement (e.g., "Boxes", "Bottles")

If not provided, the system calculates quantity as: (morning + afternoon + evening + night) × days

Example

{
  "prescriptions": [
    {
      "patient_code": "P25003877",
      "visit_code": "V420650",
      "encounter_code": "E417001",
      "code": "RX20250317001",
      "prescribed_at": "2025-03-17T10:10:00.000+07:00",
      "prescribed_by": "Dr. Chhun Sovannarith",
      "title": "Doctor",
      "medications": [
        {
          "medicine_code": "MED001",
          "medicine_name": "Artemether-Lumefantrine",
          "strength": "20/120mg",
          "method": "Oral",
          "unit": "Tablet",
          "morning": 4,
          "afternoon": 0,
          "evening": 4,
          "night": 0,
          "days": 3,
          "interval": null,
          "note": "Take with food. Complete the full course.",
          "dispense": {
            "quantity": 1,
            "unit": "Boxes"
          }
        },
        {
          "medicine_code": "MED002",
          "medicine_name": "Paracetamol",
          "strength": "500mg",
          "method": "Oral",
          "unit": "Tablet",
          "morning": 0,
          "afternoon": 0,
          "evening": 0,
          "night": 0,
          "days": 5,
          "interval": "8 hours",
          "note": "Take only when you have fever or pain.",
          "dispense": {
            "quantity": 1,
            "unit": "Boxes"
          }
        }
      ]
    }
  ]
}

Invoices

Invoices are the financial record of the patient's visit - what services were provided and what they cost. This includes everything from consultation fees to laboratory tests to medications.

In Cambodia's healthcare system, many patients are covered by health insurance programs (like HEF or NSSF), so the invoice also tracks what the patient pays versus what the insurance covers.

Data Model

Field	Type	Description
patient_code	string	Which patient this invoice belongs to
visit_code	string	Which visit this invoice covers
encounter_code	string	Which encounter these charges are from
code	string	Unique identifier for this invoice
payment_type	string	How this will be paid (HEF, NSSF, Cash, etc.)
invoice_date	datetime	When this invoice was created
total	number	Total amount of all charges
cashier	string	Who processed this invoice
services	array of objects	Medical services provided
medications	array of objects	Medications dispensed

Example

{  
  "invoices": [  
    {  
      "patient_code": "P25003877",  
      "visit_code": "V420650",
      "encounter_code": "E417001",  
      "code": "INV20250317001",  
      "payment_type": "HEF",  
      "invoice_date": "2025-03-17T11:00:00.000+07:00",  
      "total": 45000,  
      "cashier": "Sok Kunthea",  
      "services": [  
        {  
          "service_code": "SRV001",  
          "service_name": "Blood Smear for Malaria",  
          "service_category": "Laboratory Test",  
          "price": 15000,  
          "payment": 0,  
          "paid": false,
          "discount": 15000
        }  
      ],  
      "medications": [  
        {  
          "medicine_code": "MED001",  
          "medicine_name": "Artemether-Lumefantrine 20/120mg",  
          "quantity": 24,
          "unit": "Tablet",  
          "price": 1250,  
          "payment": 0,  
          "paid": false,
          "discount": 30000
        }  
      ]  
    }  
  ]  
}

Referrals

Sometimes a patient needs care that the current hospital can't provide - maybe they need specialized treatment, advanced equipment, or a higher level of care. When this happens, the patient is "referred" to another healthcare facility.

Referrals are like passing the patient's story to the next chapter, but at a different hospital. All the information about their condition, treatment so far, and why they need to be transferred is carefully documented.

Data Model

Field	Type	Description
referred_from	object	Information about where the patient came from
referred_to	object	Information about where the patient is going

Referral Details

Field	Type	Description
code	string	Unique identifier for this referral
referral_number	string	Official referral document number
transportation	string	How the patient will travel (Ambulance, Family car, etc.)
reason	string	Why the patient needs to be referred
has_called	boolean	Whether the receiving hospital was contacted in advance
caretaker_name	string	Person accompanying the patient
caretaker_phone	string	Contact number for the caretaker
referred_by	string	Doctor making the referral
referred_at	datetime	When the referral was made
received_by	string	Doctor receiving the patient
received_at	datetime	When the patient arrived at the new hospital
medications	string	Current medications the patient is taking
health_facility	object	Details about the receiving hospital

Example

{  
  "referrals": {  
    "referred_from": null,  
    "referred_to": {  
      "code": "REF20250317001",  
      "referral_number": "HCPP/REF/2025/317",  
      "transportation": "Ambulance",
      "health_facility": {
        "name": "Calmette Hospital",
        "code": "121020",
        "label": "National Referral Hospital",
        "type": "Tertiary"
      },  
      "reason": "Severe malaria with complications requiring intensive care and specialized treatment not available at this facility",  
      "has_called": true,  
      "caretaker_name": "Sok Channary (wife)",  
      "caretaker_phone": "012345678",  
      "referred_by": "Dr. Chhun Sovannarith",  
      "referred_at": "2025-03-17T11:30:00.000+07:00",  
      "received_by": "Dr. Pich Vothy",  
      "received_at": "2025-03-17T12:15:00.000+07:00",  
      "medications": "Currently on Artemether-Lumefantrine (1 dose given), IV fluids started"  
    }  
  }  
}

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Summary

Each component tells part of the patient's healthcare story. When connected together through their unique codes, they create a complete picture of the patient's journey from arrival to discharge, including all the care, tests, treatments, and outcomes along the way.