as below

7

M2_2_Relational_Database_Design

Brian Blake

George Mason University

Professor Ioulia Rytikova

AIT-524-002

January 29, 2023

Description of the Company

Radiant Healthcare Center is a multi-specialty healthcare organization that provides its patients with a wide range of medical services. It has branches in different parts of the country, each operating independently. The center offers various services, including primary care, preventive medicine, diagnostic services, and specialized medical and surgical treatments. The team of medical professionals at Radiant Healthcare Center is highly trained and experienced in various specialties, and they are dedicated to providing high-quality, compassionate care to their patients. They strive to create a comfortable and welcoming environment for patients and families and to ensure that patients receive the best possible care. With the opening of the 8th branch, Radiant Healthcare Center will continue to expand its reach and improve access to quality healthcare for more people.

Reasons for Database

Radiant Healthcare Center, as a multi-specialty healthcare organization, requires a database to manage and organize the vast amount of patient information it receives daily. A database would enable the center to store, retrieve, and update patient information such as medical history, treatment plans, and test results efficiently and efficiently. Radiant Healthcare Center needs a database to improve patient care. With a database, the center will facilitate quick access to patient information, including medical history, allergies, and current medications. It will enable medical professionals to provide more accurate diagnoses and treatment plans and to avoid potential adverse reactions or interactions between drugs.

A database will facilitate the sharing of patient information among different branches of Radiant Healthcare Center (Lubrano et al., 2021). It ensures continuity of care for patients who visit other units or are referred to specialists within the organization. A database is also essential for record-keeping and compliance with regulations. It will allow the center to easily store and retrieve patient information required for billing and insurance claims and comply with laws such as HIPAA.

Business Rules

1. Each patient can have one or more medical records. Each medical history must belong to one patient.

2. Each medical record can have one or more diagnostic results. Each diagnostic result must belong to one medical history.

3. Each diagnostic result can have one or more treatments. Each treatment must belong to one diagnostic development.

4. Each patient can have one or more appointments. Each appointment must belong to one patient.

5. Each appointment can have one or more diagnostic procedures. Each diagnostic system must belong to one position.

6. Each patient can have one or more prescriptions. Each prescription must belong to one patient.

7. Each prescription can have one or more medications. Each medication must belong to one drug.

Explanation

Each patient can have one or more medical records. Each medical history must belong to one patient. This relationship is 1:M as every patient may have many medical records, and each one belongs to only one patient. It is a weak relationship as medical records are independent of patients. The connection is optional on the “many” side because business rules say that every patient “may” have a medical history (Cichy and Rass, 2019). It is mandatory on the “one” side because business rules say that every medical record “must” belong to a patient. According to business rules, the cardinality on the many sides is (0, N) because it is optional and (1, 1) for the one side because it is mandatory.

Each medical record can have one or more diagnostic results. Each diagnostic result must belong to one medical history. This relationship is 1:M, as every medical record may have many diagnostic results, and each diagnostic result belongs to only one medical record. It is a weak relationship as diagnostic results are independent of medical records. The connection is optional on the “many” side because business rules say that every medical history “may” have a diagnostic result. It is mandatory on the “one” side because business rules state that every diagnostic development “must” belong to a medical record. According to business rules, the cardinality on the many sides is (0, N) because it is optional and (1, 1) for the one side because it is mandatory.

Each diagnostic result can have one or more treatments. Each treatment must belong to one diagnostic development. This relationship is 1:M, as every diagnostic result may have many treatments, and each therapy belongs to only one diagnostic result. It is a weak relationship as treatments are independent of diagnostic results (Palanisamy and Thirunavukarasu, 2019). The connection is optional on the “many” side because business rules say that every diagnostic development “may” have a treatment. It is mandatory on the “one” side because business rules state that every treatment “must” belong to a diagnostic result. According to business rules, the cardinality on the many sides is (0, N) because it is optional and (1, 1) for the one side because it is mandatory.

Each patient can have one or more appointments. Each appointment must belong to one patient. This relationship is 1:M, as every patient may have many meetings, and each work belongs to only one patient. It is a weak relationship as appointments are independent of patients. The connection is optional on the “many” side because business rules say that every patient “may” have a license. It is mandatory on the “one” side because business rules state that every appointment “must” belong to a patient. According to business rules, the cardinality on the many sides is (0, N) because it is optional and (1, 1) for the one side because it is mandatory.

ERD/EERD Diagram

Relationships:

Patient has many Medical_Records (1:M)

Medical_Record has many Diagnostic_Results (1:M)

Diagnostic_Result has many Treatments (1:M)

The patient has many Appointments (1:M)

Appointment has many Diagnostic_Procedures (1:M)

The patient has many Prescriptions (1:M)

Prescription has many Medications (1:M)

References

Cichy, C., & Rass, S. (2019). An overview of data quality frameworks.  IEEE Access,  7, 24634-24648.

Lubrano, F., Stirano, F., Varavallo, G., Bertone, F., & Terzo, O. (2021). HAMS: an integrated hospital management system to improve information exchange. In Complex, Intelligent and Software Intensive Systems: Proceedings of the 14th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS-2020) (pp. 334-343). Springer International Publishing.

Palanisamy, V., & Thirunavukarasu, R. (2019). Implications of big data analytics in developing healthcare frameworks–A review.  Journal of King Saud University-Computer and Information Sciences,  31(4), 415-425.