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Introduction

Introduction Clinical management systems are essential for modern healthcare facilities. They help streamline operations, improve efficiency and provide better patient care. This case study explores a clinical management system designed to streamline patient appointments, physician interactions, and prescription management. The system also aims to maintain essential patient and appointment records. The system is designed to be user-friendly and easy to navigate. It offers many features to help clinics manage their operations effectively.

These features include

Schedule and manage patient appointments

  • The system allows clinics to schedule and manage patient appointments online or over the phone. It also provides features to track patient arrival, check-in, and check-out times.

Schedule and manage doctor's appointments

The system allows clinics to schedule and manage doctor's appointments online. It also provides features to track physician availability and ensure all appointments are scheduled properly.

Prescription management

The system allows clinics to electronically prescribe medications to patients. It also provides features to track medication inventory and expiration dates.

Patient and Appointment Records Management

The system stores and maintains all necessary patient and appointment records. This includes patient demographics, medical history, insurance information, and appointment details.

Reporting and Analytics

The system provides a variety of reports and analytics to help clinics track their performance and identify areas for improvement.

The practice management system described in this case study provides a number of benefits to healthcare facilities, including: Gained efficiency improvement: The system automates many tasks that are typically performed manually, such as scheduling appointments, prescription management and record keeping. This allows staff to focus on patient care.

Error Reduction

The system automates many tasks prone to human error, such as calculating medication doses and verifying insurance. This reduces the risk of errors and improves patient safety.

Advanced Patient Care

The system provides patients with a convenient and efficient way to make appointments, manage prescriptions, and access their medical records. This improves patient experience and satisfaction.

Improved communication

The system facilitates communication between patients, doctors, and other healthcare professionals. This helps ensure that patients receive the best care possible.

Better Decision Making

This system provides clinics with a variety of reports and analytics to help them track their performance and identify areas for improvement. This information can be used to make better decisions about resource allocation, staffing levels, and other operational issues.
 

Query 1

  • How many patients are there in the patient table?

select count(*) as Total_Patients from patient;

Query 2

  • Write a query to determine if there are more males than females in the patient table.

SELECT CASE WHEN COUNT(*) > (SELECT COUNT(*) FROM patient WHERE gender = 'Female') THEN 'There are more males than females in the patient table.' ELSE 'There are more females than males in the patient table.' END AS gender_count FROM patient WHERE gender = 'Male';

Query 3

  • Retrieve the names of patients who have 'Lee' in their name and 'follow-up' in the appointment notes.

SELECT patient.name
FROM patient
JOIN appointment ON patient.patient_id = appointment.patient_id
WHERE patient.name LIKE '%Lee%' AND appointment.notes LIKE '%follow-up%';

Query 4

  • Retrieve the medications that have been prescribed for patients whose names ending with 'Smith’.

SELECT medication.name as Medications
FROM medication
JOIN prescription ON medication.medication_id = prescription.medication_id
JOIN appointment ON appointment.appointment_id = prescription.appointment_id
JOIN patient ON patient.patient_id = appointment.patient_id
WHERE patient.name LIKE '%Smith';

Query 5

  • List the doctors who have not been assigned any appointments using a subquery.
    Select NAME from doctor
    WHERE doctor_id NOT IN
    (SELECT doctor_id from appointment);

Query 6

  • Retrieve the doctors who have prescribed medications containing 'pain' in their description more than 2 times.

SELECT doctor.name, COUNT(*) AS prescription_count
FROM doctor
JOIN appointment ON doctor.doctor_id = appointment.doctor_id
JOIN prescription ON prescription.appointment_id = appointment.appointment_id
JOIN medication ON prescription.medication_id = medication.medication_id
WHERE medication.description LIKE '%pain%'
GROUP BY doctor.doctor_id
HAVING COUNT(*) > 2;

Query 7

  • Write a query to find patients who have appointments scheduled in the month of June 2023.

SELECT patient.name
FROM patient
JOIN appointment ON patient.patient_id = appointment.patient_id
WHERE MONTH(appointment.appointment_date) = 6 AND YEAR(appointment.appointment_date) = 2023;


Query 8

  • Write a query to find the doctor with the highest number of appointments scheduled in a single day.

SELECT doctor.name, COUNT(*) AS appointment_count
FROM doctor
JOIN appointment ON doctor.doctor_id = appointment.doctor_id
GROUP BY doctor.doctor_id, appointment.appointment_date
ORDER BY appointment_count DESC
LIMIT 1;

Query 9

  • List the total number of appointments based on the day of the week.

SELECT DAYOFWEEK(appointment.appointment_date) AS day_of_week, COUNT(*) AS appointment_count
FROM appointment
GROUP BY DAYOFWEEK(appointment.appointment_date)
ORDER BY DAYOFWEEK(appointment.appointment_date);

Query 10

  • Display the patients if they are sharing the same birth month as another patient.

SELECT patient1.name AS patient1_name, patient2.name AS patient2_name
FROM patient patient1
JOIN patient patient2 ON patient1.patient_id != patient2.patient_id
WHERE MONTH(patient1.dob) = MONTH(patient2.dob)
GROUP BY patient1_name
ORDER BY patient1_name, patient2_name;

Query 11

  • How many patients have never had an appointment or scheduled any appointments so far?

SELECT COUNT(*) AS patient_count
FROM patient
LEFT JOIN appointment ON patient.patient_id = appointment.patient_id
WHERE appointment.appointment_id IS NULL;

Query 12

  • Show medications that have never been prescribed to by any doctor using a JOIN of your choice.

SELECT medication.name
FROM medication
left JOIN prescription ON medication.medication_id = prescription.medication_id
WHERE prescription.prescription_id IS NULL;

Query 13

  • List the doctors who have treated at least one patient from ‘WA’.

SELECT doctor.name, COUNT(DISTINCT patient.patient_id) AS patient_count
FROM doctor
JOIN appointment ON doctor.doctor_id = appointment.doctor_id
JOIN patient ON appointment.patient_id = patient.patient_id
WHERE patient.state_code = 'WA'
GROUP BY doctor.doctor_id
HAVING patient_count > 0;

Query 14

  • Which medicine has the second-highest overall prescription rate?

SELECT medication.name, COUNT(*) AS prescription_count
FROM medication
JOIN prescription ON medication.medication_id = prescription.medication_id
GROUP BY medication.medication_id
ORDER BY prescription_count DESC
LIMIT 1,1;

Query 15

  • Retrieve the patients who have never cancelled an appointment.

SELECT patient.name
FROM patient
JOIN appointment ON patient.patient_id = appointment.patient_id
WHERE appointment.status != 'cancelled';

Query 16

  • Retrieve the youngest and oddest female patient.

SELECT patient.name, patient.dob
FROM patient
WHERE patient.gender = 'Female'
ORDER BY patient.dob DESC, patient.name ASC
LIMIT 1;

Query 17

  • Find medications that have appeared only once in any prescription.

SELECT medication.name
FROM medication
JOIN prescription ON medication.medication_id = prescription.medication_id
GROUP BY medication.medication_id
HAVING COUNT(*) = 1;

Query 18

  • Find medications that have appeared only once in any prescription along with the doctors who prescribed them.

SELECT medication.name as Medication_Name, doctor.name as Doctor_Name
FROM medication, appointment, prescription, doctor
where medication.medication_id= prescription.medication_id AND
prescription.appointment_id = appointment.appointment_id AND
doctor.doctor_id = appointment.doctor_id
GROUP BY medication.medication_id
HAVING COUNT(*) = 1;

Query 19

  • Retrieve the patients who have had appointments with at least three different doctors.

SELECT patient.name
FROM patient
JOIN appointment ON patient.patient_id = appointment.patient_id
GROUP BY patient.patient_id
HAVING COUNT(DISTINCT appointment.doctor_id) >= 3;

Answer 20.

Based on the schema you provided, the tables are not in 3NF.

Justification:

The patients table is in 3NF, as all of its attributes are functionally dependent on the primary key (Appointment_id). However, the appointments table is not in 3NF, as the doctor_id attribute is transitively dependent on the primary key (Appointment_id). This means that the doctor_id attribute can be determined by the patient_id attribute alone.

Example:

Appointment -> Appointment_id, patient_id, doctor_id, appointment_date
In this example, we can see that the doctor_id attribute is transitively dependent on the primary key attribute. This is because we can determine the doctor_id attribute for a given patient by looking up the doctor_id attribute for the patient's most recent appointment.

To improve the database, we can do the following:

  • Split the appointments table into two tables: One table for the appointments themselves, and one table for the patient-doctor relationships. This will remove the transitive dependency between the doctor_id attribute and the primary key attribute.
  • Add a foreign key constraint to the patient_id attribute in the appointments table. This will ensure that all appointments are associated with a valid patient.

patients table
patient-> patient_id, name, date_of_birth, address, phone_number
appointments table
appointment -> appointment_id, patient_id, appointment_date
patient_doctor_relationships table
patient_doctor_relationships -> patient_id, doctor_id

This updated schema is in 3NF, as all attributes are functionally dependent on the primary key of their respective tables.

Conclusion

The clinical management system described in this case study is a valuable asset to any healthcare facility. This can help increase efficiency, streamline operations, reduce errors, improve patient care, improve communication and facilitate better decision making. Additional Considerations In addition to the benefits listed above, a Practice Management System can also help healthcare facilities: Improve Compliance: The System Can helps clinics comply with various regulations, such as HIPAA and GDPR. This is important because non-compliance can result in fines and other sanctions.

  • Increase Revenue: The system can help clinics increase revenue by improving efficiency and patient satisfaction. This can lead to more patients and more referrals.
  • Reduce costs: The system can help clinics reduce costs by automating tasks and reducing errors. This can allow staff to focus on more important tasks and improve the clinic's overall financial performance.

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