The "Synthetic Healthcare Dataset: "Demographics, Conditions, Treatments, and Outcomes for Research and Analysis" is a complete synthesis of realistic but fictitious data that represents various aspects of healthcare. The database contains data about the patient demographics: age, gender, and region, as well as the medical conditions diagnosed, the treatments administered and the outcomes observed.
The dataset has been created to resemble actual healthcare situations and can be used for research and analysis in the healthcare field. Researchers, data scientists, and healthcare professionals can use this dataset to discover the patterns, trends, and correlations related to disease prevalence, treatment effectiveness, patient outcomes, and other aspects. Besides, it is a good source for creating and testing models designed to enhance healthcare decision-making and patient care.
Through the collection of a wide variety of data, including patient characteristics, medical conditions, treatments and outcomes, this synthetic dataset provides a multifaceted base for conducting numerous analyses and experiments in the area of healthcare analytics.
Columns:
Patient_ID: Unique identifier for each patient.
Age: Age of the patient.
Gender: Gender of the patient.
Medical_Condition: The medical condition the patient is diagnosed with.
Treatment: The treatment administered to the patient.
Outcome: The outcome of the treatment (e.g., Improved, Stable, Worsened).
Insurance_Type: Type of insurance the patient has (e.g., Private, Public, Medicare).
Income: Annual income of the patient.
Region: Geographic region where the patient is located.
Smoking_Status: Smoking status of the patient (e.g., Non-smoker, Former smoker, Current smoker).
Admission_Type: Type of admission to the hospital (e.g., Elective, Emergency, Urgent).
Hospital_ID: Unique identifier for the hospital where the patient was treated.
Length_of_Stay: Length of hospital stay in days.