EHR Database and Data Management
Provide a complete description of data entities (the objects for which you seek information, i.e., patients) and their relationships to the attributes collected for each entity (data collected for each entity, i.e., gender, birthdate, first name, last name, etc.) that apply to the hypothetical database. You can use a concept map similar to the “Database Concept Map” resource to help you describe the relationships between each entity and its attributes.
A data entity is an object with a list of attributes that distinguishes it from other objects. For instance, a patient is a data entity with possible attributes such as patient_id, patient_dob, and patient_gender. Another entity in the database is that of a doctor where we have attributes such as doctor_id, doctor_name, and specialization. There can also be an entity like a test that includes attributes such as test_name, test_date, test_time, and result. The above three entities relate to another. Entity relationships can be in the form of one to one (1:1), one to many (1:M), many to many (M: M), and many to one (M:1). Relationship sets also contain descriptive attributes (Villari et al., 2016). Given that it is possible to find a couple of patients sharing names, addresses, and other attributes, database languages provide for a mechanism of distinguishing one data entity from a host of others through an attribute referred to as a primary key. In the above example, the patient_id is the primary key that uniquely identifies a specific patient from a database list containing thousands of patients. Every entity has a key, just the same way every attribute has a domain. Below is an illustration that depicts the conceptual framework of the database.
Reference
Villari, M., Celesti, A., Giacobbe, M., & Fazio, M. (2016, June). Enriched the ER model to design a hybrid database for big data solutions. In 2016 IEEE Symposium on Computers and Communication (ISCC) (pp. 163-166). IEEE.