This synthetic healthcare dataset has been generated to serve as an educational resource for data science, machine learning, and data analysis applications in the healthcare industry. It mirrors real-world patient records, allowing users to practice data manipulation and develop analytical skills in a healthcare context.

Dataset Features:

• Age: Age of the patient at admission (in years).
• Gender: Gender of the patient.
• Blood Type: Patient's blood type (e.g., "A+", "O-").
• Medical Condition: Primary diagnosis or medical condition, such as "Diabetes," "Hypertension," or "Asthma."
• Date of Admission: The date when the patient was admitted.
• Insurance Provider: Name of the patient’s insurance provider (e.g., "Aetna," "Cigna").
• Billing Amount: Total charges for healthcare services provided (in monetary units).
• Room Number: Room number assigned to the patient during their stay.
• Admission Type: Type of admission, categorized as "Emergency," "Elective," or "Urgent."
• Discharge Date: Date when the patient was discharged.
• Test Results: Outcome of a medical test, categorized as "Normal," "Abnormal," or "Inconclusive."

Visualisation:

Usage:

This dataset can be used for:

• Healthcare research: To explore trends and patterns in patient admissions, conditions, and outcomes.
• Educational training: To teach data cleaning, transformation, and visualization techniques specific to healthcare data.
• Predictive modelling: To develop models that predict healthcare outcomes based on various patient and admission factors.

Coverage:

This dataset is synthetic and anonymized, making it a safe tool for experimentation and learning without compromising real patient privacy.

License:

CCO (Public Domain)

Who can use it:

• Researchers and educators: For studies or teaching purposes in healthcare analytics and data science.
• Data science enthusiasts: For learning, practising, and applying healthcare data manipulation and analysis techniques.