SirWangai/Kenya-Health-Records-Analysis

Using Excel to Analyze Correlation Between Gender, Diagnosis and Cost of Healthcare # Health, Age, and Affordability: Correlational Insights from Multi-Hospital Patients This project examines patient-level health data collected across multiple hospitals, including demographic details, *such as names, gender, and age*, diagnosed conditions, treatments costs, and payment status, to explore how age and diagnosis correlate, and to assess the broader financial burden that healthcare costs place on patients ## Tools Used - Git - Excel ## Analysis Non-communicable conditions outnumber infectious ones in every age bracket Seniors are more prone to diagnosis across the board Lifestyle diseases carry the highest cost of burden ## Challenges Faced - Patients refused to have their data used - Making correlations is difficults since different hospitals have different pricings