Patient Segmentation is a patient classification dataset for healthcare analytics and marketing. It aims to segment patients into meaningful groups by analyzing their demographics, health status, insurance type, and healthcare usage patterns to improve the effectiveness of personalized care and marketing.

Dataset composition:

• Contains 2,000 patient records
• Includes demographic information: age, gender, and geographic location (state, city).
• Health indicators: height, weight, BMI, number of chronic diseases, major medical conditions
• Healthcare usage: Annual visit frequency, days since last visit, average billing amount per visit
• Insurance and Participation Status: Insurance Type (Medicare, Medicaid, Private, Self-Pay), Preventive Care Participation Markers

Data Fields:

• Demographic fields include age, gender, and geographic location.
• Health indicator fields include height, weight, BMI, number of chronic diseases, and major medical conditions.
• The healthcare usage fields include annual visit frequency, number of days since the last visit, and average billing amount per visit.
• The insurance and participation fields include insurance type and preventive care participation flags.