Health diagram for the three primary database models used in healthcare the relational model

Sample Answer

A diagrammatic representation of the three primary database models—Relational, Hierarchical, and NoSQL (specifically, Document)—as they relate to data in a healthcare context is provided below.

⚕️ Three Primary Database Models in Healthcare

1. Relational Model (Structured Data)

The relational model organizes data into one or more tables (or "relations") consisting of columns and rows. Each table stores data about a single entity, and relationships between entities are defined by keys (primary and foreign). This structure ensures data integrity and consistency.

Healthcare Context: Used for Electronic Health Records (EHRs), billing systems, and master patient indexes where structured, standardized, and highly consistent data is paramount (e.g., demographics, diagnoses codes, lab results).

2. Hierarchical Model (Tree Structure)

The hierarchical model organizes data in a tree-like structure, where each record type (node) has a single parent and can have many children. This creates a one-to-many relationship structure.

                  Patient Record (Parent)
                  /             \
      Clinical Encounter 1      Clinical Encounter 2
          /     \                 /     \
  Diagnosis    Treatment        Diagnosis    Treatment
  (Child)      (Child)          (Child)      (Child)
  
  Example Path: Patient J. Smith -> Encounter 1 (10/25/2025) -> Diagnosis (Hypertension)

Healthcare Context: Traditionally used for specific, predefined data relationships that are stable and have clear parent-child links, such as medical record indexes or departmental organizational charts where a specific data query will always follow the same path.

3. NoSQL Model: Document Database (Flexible Structure)

The NoSQL Document model stores data in flexible, semi-structured documents (often JSON format). An entire entity, along with all its related data, is stored in a single document, eliminating the need for strict, predefined table joins.

{
  "patient_id": "101",
  "name": "J. Smith",
  "date_of_birth": "1980-01-01",
  "address": "X Street",
  "vitals": [
    {"date": "2025-10-25", "bp": "130/85", "temp": "98.6"},
    {"date": "2025-10-26", "bp": "125/80", "temp": "98.8"}
  ],
  "encounters": [
    {
      "encounter_id": "5001",
      "provider": "Dr. A. Jones",
      "diagnosis_codes": ["I10", "E11.9"],
      "notes": "Patient reports minor chest pain."
    }
  ]
}

Healthcare Context: Used for data that is frequently changing, rapidly generated, or does not fit neatly into relational tables, such as IoT wearable device data, large volumes of clinical notes, image metadata, or genomic data, prioritizing flexibility and quick retrieval over strict integrity rules.