UNIVERSITY OF SOUTH AFRICA
College of Science, Engineering and Technology
⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄⋄
INF3703: Database II
Assignment 02 — Semester 1, 2026
⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄⋄
INF3703
Module Code:
Database II
Module Name:
Database Design: MediCare Community
Assignment Topic: Clinic
Assignment 02
Assignment Number:
26 June 2026
Due Date:
100
Total Marks:
Submitted in partial fulfilment of the requirements for Database II — UNISA 2026
,UNISA | INF3703 Database Design: MediCare Clinic
Question 1: Organisation and Problem Identification
1.1 Organisation Overview
The organisation selected for this assignment is MediCare Community Clinic (MCC), a fic-
tional primary healthcare facility modelled on the operational challenges of small-to-medium
public clinics found across South Africa. The clinic is situated in a peri-urban township area
and provides services to a large daily patient population. The case study is grounded in doc-
umented patterns of healthcare data management challenges within the South African public
health system, as identified by researchers including Luthuli and Kalusopa (2018), who found
that the management of medical records in KwaZulu-Natal public facilities suffered from sig-
nificant inefficiencies linked to paper-based systems.
MediCare Community Clinic offers the following core services: general outpatient consul-
tations, antenatal care, chronic disease management (including HIV/AIDS and tuberculosis
follow-ups), pharmacy dispensing, and basic laboratory investigations. The clinic operates
Monday to Saturday, sees an average of 150 patients per day, and employs twelve clinical staff
members comprising doctors, nurses, and pharmacists, supported by five administrative staff.
1.2 Identification of the Database Problem
At present, MediCare Community Clinic manages all patient records manually using a paper-
based filing system. Each patient is assigned a handwritten folder that is stored alphabetically in
a physical filing cabinet. This approach introduces several serious database-related problems:
• Data redundancy and duplication: Patients who visit the clinic multiple times are some-
times registered more than once because staff cannot locate existing folders quickly. This
creates duplicate patient records, making it impossible to maintain an accurate longitudinal
health history.
• Data inaccessibility: When a folder is misfiled or unavailable, the attending clinician has
no access to the patient’s previous diagnoses, prescriptions, or allergy information, creating
a patient safety risk.
• Lack of data integrity: Handwritten entries are subject to illegibility and transcription
errors. There are no constraints preventing a staff member from recording an incorrect
patient identifier or date.
• Inefficient appointment management: Appointment scheduling is done using a paper
register, which does not prevent double-booking and cannot generate any form of reporting
on attendance patterns.
• Pharmacy and stock management gaps: Medication dispensing records are kept sepa-
rately from the clinical notes, so there is no mechanism to flag drug interactions or detect
over-dispensing.
• Inability to generate reports: Clinic management cannot extract summary data for sub-
mission to district health authorities without manually counting records, a process that is
time-consuming and error-prone.
Page 2 of 16
, UNISA | INF3703 Database Design: MediCare Clinic
Critical Consideration
The absence of a relational database system at MediCare Community Clinic is not merely
an operational inconvenience. It constitutes a patient safety risk. Without structured
data management, allergies and contraindicated medications can go undetected. A well-
designed database directly supports clinical decision-making and regulatory compliance.
The proposed solution is to design a new relational database management system (RDBMS) for
MediCare Community Clinic that will centralise all patient, appointment, clinical, pharmacy,
and staff data into a single, structured, and queryable repository. This design covers the concep-
tual, logical, and physical models in accordance with established database design methodology
(Elmasri and Navathe, 2016).
Page 3 of 16
College of Science, Engineering and Technology
⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄⋄
INF3703: Database II
Assignment 02 — Semester 1, 2026
⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄ ⋄⋄
INF3703
Module Code:
Database II
Module Name:
Database Design: MediCare Community
Assignment Topic: Clinic
Assignment 02
Assignment Number:
26 June 2026
Due Date:
100
Total Marks:
Submitted in partial fulfilment of the requirements for Database II — UNISA 2026
,UNISA | INF3703 Database Design: MediCare Clinic
Question 1: Organisation and Problem Identification
1.1 Organisation Overview
The organisation selected for this assignment is MediCare Community Clinic (MCC), a fic-
tional primary healthcare facility modelled on the operational challenges of small-to-medium
public clinics found across South Africa. The clinic is situated in a peri-urban township area
and provides services to a large daily patient population. The case study is grounded in doc-
umented patterns of healthcare data management challenges within the South African public
health system, as identified by researchers including Luthuli and Kalusopa (2018), who found
that the management of medical records in KwaZulu-Natal public facilities suffered from sig-
nificant inefficiencies linked to paper-based systems.
MediCare Community Clinic offers the following core services: general outpatient consul-
tations, antenatal care, chronic disease management (including HIV/AIDS and tuberculosis
follow-ups), pharmacy dispensing, and basic laboratory investigations. The clinic operates
Monday to Saturday, sees an average of 150 patients per day, and employs twelve clinical staff
members comprising doctors, nurses, and pharmacists, supported by five administrative staff.
1.2 Identification of the Database Problem
At present, MediCare Community Clinic manages all patient records manually using a paper-
based filing system. Each patient is assigned a handwritten folder that is stored alphabetically in
a physical filing cabinet. This approach introduces several serious database-related problems:
• Data redundancy and duplication: Patients who visit the clinic multiple times are some-
times registered more than once because staff cannot locate existing folders quickly. This
creates duplicate patient records, making it impossible to maintain an accurate longitudinal
health history.
• Data inaccessibility: When a folder is misfiled or unavailable, the attending clinician has
no access to the patient’s previous diagnoses, prescriptions, or allergy information, creating
a patient safety risk.
• Lack of data integrity: Handwritten entries are subject to illegibility and transcription
errors. There are no constraints preventing a staff member from recording an incorrect
patient identifier or date.
• Inefficient appointment management: Appointment scheduling is done using a paper
register, which does not prevent double-booking and cannot generate any form of reporting
on attendance patterns.
• Pharmacy and stock management gaps: Medication dispensing records are kept sepa-
rately from the clinical notes, so there is no mechanism to flag drug interactions or detect
over-dispensing.
• Inability to generate reports: Clinic management cannot extract summary data for sub-
mission to district health authorities without manually counting records, a process that is
time-consuming and error-prone.
Page 2 of 16
, UNISA | INF3703 Database Design: MediCare Clinic
Critical Consideration
The absence of a relational database system at MediCare Community Clinic is not merely
an operational inconvenience. It constitutes a patient safety risk. Without structured
data management, allergies and contraindicated medications can go undetected. A well-
designed database directly supports clinical decision-making and regulatory compliance.
The proposed solution is to design a new relational database management system (RDBMS) for
MediCare Community Clinic that will centralise all patient, appointment, clinical, pharmacy,
and staff data into a single, structured, and queryable repository. This design covers the concep-
tual, logical, and physical models in accordance with established database design methodology
(Elmasri and Navathe, 2016).
Page 3 of 16
