Question

 A health analytics platform maintains data about patients, diagnostic tests, doctors, and test results.
Analysts want to query trends across diseases, age groups, and regions. Design an ER diagram for
this system. Clearly identify entities, relationships, key attributes, and constraints. State assumptions
made.

05 Aug 2026
Answer :
Word Count : 727
A health analytics platform can be modeled using an Entity–Relationship (ER) diagram that represents patients, doctors, diagnostic tests, test results, diseases, and geographical regions. The main purpose of the ER model is to organize healthcare data in a structured manner so that analysts can efficiently study disease trends across different age groups, regions, doctors, and diagnostic tests. The first major entity is Patient, which represents individuals receiving healthcare services. Its key attribute is Patient_ID, which uniquely identifies each patient. Other attributes include Patient_Name, Date_of_Birth, Gender, Contact_Number, and Address. Age need not be stored separately because it can be derived from Date_of_Birth. Each patient belongs to a particular geographical region, so Patient can be associated with the Region entity. The Region entity has Region_ID as its primary key, along with Region_Name, State, and Country. One region can contain many patients, whereas each patient is assumed to belong to one primary region. Thus, the relationship between Region and Patient is one-to-many. The second important entity is Doctor. Doctor_ID acts as its primary key, while Doctor_Name, Specialization, Qualification, Contact_Number, and Hospital_Name can be stored as descriptive attributes. A doctor may attend to many patients, and a patient may be attended by several doctors over time. Therefore, Patient and Doctor have a many-to-many relationship. This relationship can be represented through an associative
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