Synthetic Healthcare Patient Records Dataset
Synthetic EMRs & Patient Records
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About
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.
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