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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/diegolozadev/DataMed/llms.txt

Use this file to discover all available pages before exploring further.

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Database Schema

DataMed uses a relational database (PostgreSQL in production, SQLite in development) with a carefully designed schema to manage patient data, clinical exams, and program cycles.

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Core Models Overview

DataMed’s data model consists of three primary components:
  1. Patient Management: Patient demographics and enrollment
  2. Program Cycles: Ingreso model for 18-month capita cycles
  3. Clinical Exams: Multiple exam types linked to cycles

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Entity Relationship Diagram

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Patient Model

The foundational model storing patient demographics and clinical baseline data.

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Fields

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nombre
CharField(100)
required
Patient’s first name
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apellido
CharField(100)
required
Patient’s last name
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tipo_documento
CharField(3)
required
Document type: RC, TI, CC, CE, PA, PE
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documento
CharField(20)
required
Unique document number (primary identifier)
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fecha_nacimiento
DateField
required
Date of birth
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genero
CharField(10)
required
Gender: M (Masculino), F (Femenino), O (Otro)
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departamento
CharField(100)
required
Colombian department (default: SANTANDER)
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ciudad
CharField(100)
required
City from predefined list
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zona
CharField(10)
required
URBANA or RURAL
​
telefono
CharField(20)
required
Home phone number
​
celular
CharField(20)
required
Mobile phone number
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estado_civil
CharField(20)
required
Marital status: SOLTERO, CASADO, UNIÓN LIBRE, VIUDO, DIVORCIADO
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entidad_salud
CharField(100)
required
Health insurance provider (EPS): ECOPETROL, SANITAS
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estrato
IntegerField
required
Socioeconomic stratum (1-6)
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peso
DecimalField(5,2)
Weight in kilograms
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altura
DecimalField(4,2)
Height in meters
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perimetro_abdominal
DecimalField(5,2)
Abdominal circumference in centimeters
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cuello
DecimalField(5,2)
Neck circumference in centimeters
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medico_remitente
CharField(100)
required
Referring physician name
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especialidad
CharField(100)
required
Physician’s specialty
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diagnostico_clinico
TextField(1000)
required
Clinical diagnosis (currently limited to G47.3 - Sleep Apnea)
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programa
CharField(100)
required
Program: PROGRAMA AOS or PROGRAMA INSOMNIO
​
valor_capita
DecimalField(10,2)
required
Capita value (default: 259783)

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Computed Properties

apps/patients/models.py
@property
def ingreso_activo(self):
    return self.ingresos.filter(estado='ACTIVO').first()

@property
def esta_activo(self):
    return self.ingresos.filter(estado='ACTIVO').exists()

@property
def edad(self):
    today = date.today()
    age = today.year - self.fecha_nacimiento.year
    if (today.month, today.day) < (self.fecha_nacimiento.month, self.fecha_nacimiento.day):
        age -= 1
    return age

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Ingreso Model

Represents a patient’s enrollment in an 18-month program cycle. Critical for data organization.

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Fields

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paciente
ForeignKey(Patient)
required
Related patient (CASCADE delete)
​
fecha_inicio
DateField
required
Program start date
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fecha_fin
DateField
Program end date (null until terminated)
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estado
CharField(20)
required
Status: ACTIVO, SUSPENDIDO, TERMINADO (default: ACTIVO)
​
motivo
TextField
Reason for status change or termination

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Computed Property: mes_capita

Automatically calculates current program month (1-18):
apps/patients/models.py
@property
def mes_capita(self):
    if not self.fecha_inicio:
        return 0
    
    hoy = date.today()
    meses = (hoy.year - self.fecha_inicio.year) * 12 + (hoy.month - self.fecha_inicio.month) + 1
    
    if meses < 1: return 1
    if meses > 18: return 18
    return meses

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Design Pattern: Data Isolation

All clinical exams are linked to an Ingreso, not directly to Patient. This ensures:
  • Historical data preservation when cycles close
  • Clean separation between program cycles
  • Accurate capita month tracking

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Clinical Exam Models

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Monitoreo (CPAP/BiPAP Monitoring)

Tracks device usage and treatment effectiveness. Key Fields:
  • uso_diario: Daily usage percentage
  • dias_uso_horas_4: Days with ≥4 hours usage
  • hipopnea_basal: Baseline AHI (copied from PSG Basal)
  • hipopnea_residual: Residual AHI with treatment
  • porcentaje_correccion: Auto-calculated ((basal - residual) / basal) * 100
  • modo_ventilatorio: CPAP, BPAP, BPAP ST
  • presion_ipap, presion_epap: Pressure settings
  • mascara_cpap, tamano_mascara: Mask type and size

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PolisomnografiaBasal (Diagnostic Sleep Study)

Baseline polysomnography before treatment. Key Fields:
  • fecha_basal: Study date
  • iah: Apnea-Hypopnea Index
  • severidad_apnea: LEVE, MODERADA, GRAVE, NORMAL
  • ido: Oxygen Desaturation Index
  • eficiencia: Sleep efficiency percentage

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PolisomnografiaTitulacion (Pressure Titration Study)

Sleep study to determine optimal device settings. Key Fields:
  • tipo_titulacion: CPAP, BPAP, BPAP ST
  • fecha_titulacion: Study date
  • presion_ipap, presion_epap: Titrated pressures
  • frecuencia_respiratoria: Respiratory rate (rpm)
  • talla_mascara, tipo_mascara: Mask configuration

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Psicologia (Psychology Assessment)

Mental health screening for sleep disorder patients. Key Fields:
  • inventario_depre_beck: Beck Depression Inventory (0-63)
  • inventario_ansiedad_beck: Beck Anxiety Inventory (0-63)
  • escala_atenas: Athens Insomnia Scale (1-10)

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Nutricion (Nutrition Consultation)

Dietary and nutritional assessment. Key Fields:
  • estado_nutricional: DESNUTRICIÓN to OBESIDAD III
  • carbohidratos_pct: Carbohydrate percentage
  • rumiacion: SI/NO for nocturnal rumination
  • cafeina: Caffeine consumption (mg/day)

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Neumologia (Pulmonology Consultation)

Specialist respiratory consultation tracking. Key Fields:
  • fecha_consulta: Consultation date
  • medico_tratante: Physician name
  • especialidad: Medical specialty

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EquipoMedico (Medical Equipment)

Device and mask assignment tracking. Key Fields:
  • tipo_mascara_eq_medico: PILLOW NASAL, NASAL, ORONASAL
  • referencia_mascara: Mask model reference
  • talla_mascara: S, M, L
  • marca_equipo: BMC, RESMED, PHILIPS RESPIRONICS, etc.
  • serial_equipo: Device serial number
  • modo_ventilatorio: CPAP, BiPAP, BiPAP ST

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Seguimiento (Follow-up Tracking)

General follow-up appointment records. Key Fields:
  • fecha_atencion: Service date
  • tipo_servicio: Type of service provided

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SeguimientoAdaptacion (Adaptation Notes)

Detailed notes on patient adaptation to treatment. Key Fields:
  • observaciones: Detailed text observations
  • created_at: Timestamp (auto)

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Common Patterns

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User Tracking

All clinical exam models track who registered the data: 
registrado_por = models.ForeignKey(
    settings.AUTH_USER_MODEL,
    on_delete=models.SET_NULL,
    null=True,
    blank=True,
    related_name='<model>_registrados'
)
Benefits:
  • Audit trail for all clinical data
  • User info preserved even if account deleted (SET_NULL)
  • Query all exams registered by a user: user.monitoreos_registrados.all()

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Timestamps

All exam models have automatic timestamps: 
created_at = models.DateTimeField(auto_now_add=True)
  • Patient → Ingresos: patient.ingresos.all()
  • Ingreso → Monitoreos: ingreso.monitoreos.all()
  • Ingreso → Psicologias: ingreso.psicologias.all()

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Indexes and Performance

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Automatic Indexes

Django creates indexes for:
  • Primary keys (id)
  • Foreign keys (all relationships)
  • Unique fields (documento)

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Query Optimization

# Efficient: Prefetch related objects
patients = Patient.objects.prefetch_related('ingresos').all()

# Efficient: Filter at database level
active_patients = Patient.objects.filter(ingresos__estado='ACTIVO').distinct()

# Efficient: Annotate aggregate data
from django.db.models import Max
patients_with_latest = Patient.objects.annotate(
    ultima_atencion=Max('ingresos__seguimientos__fecha_atencion')
)

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Database Migrations

DataMed uses Django migrations to evolve the schema. Key migrations:
  • 0001_initial.py: Initial Patient model
  • 0003_ingreso.py: Added Ingreso model for cycles
  • 0007_polisomnografiatitulacion_polisomnografiabasal_...: Sleep study models
  • 0016_remove_equipomedico_patient_...: Migrated to Ingreso-based relationships

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Data Integrity

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Constraints

  • Unique constraint: Patient.documento
  • Required fields: Most fields have null=False, blank=False
  • Cascading deletes: Most relationships use CASCADE
  • Soft deletes: Users use SET_NULL to preserve audit trail

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Validation

Django enforces:
  • Field length limits
  • Choice constraints (e.g., estado must be ACTIVO/SUSPENDIDO/TERMINADO)
  • Foreign key integrity

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Next Steps

Migrations

Learn how to manage schema changes

Backup & Restore

Protect your data with backups

API Reference

Query and manipulate data via Django views

Patient Management

Understand patient lifecycle workflows

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