SunyDB/Nigeria-Public-Health-Analysis

This project examines Nigerian public health data to uncover patterns in diseases, treatment outcomes, and healthcare delivery. Tools used include Microsoft Excel for data cleaning, analysis, and dashboard creation. # Nigeria-Public-Health-Analysis This project examines Nigerian public health data to uncover patterns in diseases, treatment outcomes, and healthcare delivery. Tools used include Microsoft Excel for data cleaning, analysis, and dashboard creation. ## Problem Statement Healthcare organizations require reliable data to monitor disease prevalence, treatment success rates, patient outcomes, and healthcare costs. This project seeks to identify key health trends and evaluate healthcare performance across different states and facility types. ## Dataset Preview ## Objectives 1. Analyze disease distribution across Nigeria 2. Evaluate treatment success and mortality rates 3. Examine treatment costs and healthcare access 4. Compare healthcare outcomes across facility types 5. Identify areas for improving healthcare delivery ## Tools Used - Microsoft Excel - Pivot Tables - Data Cleaning Techniques - Data Visualization - Dashboard Design - Data Cleaning Process The dataset was cleaned by: - Removing duplicate records. - Handling missing values. - Standardizing disease names. - Identifying inconsistent entries. - Correcting data quality issues. ## Key Performance Indicators (KPIs) - Total Patients - Treatment Success Rate - Mortality Rate - Average Treatment Cost - Average Days to Treatment - Disease Distribution - Facility Performance ## Dashboard Preview The dashboard provides insights into: - Disease distribution. - Treatment outcomes. - Facility performance. - Patient demographics. - Treatment costs. - Healthcare trends. ## Key Findings 1. High Treatment Success Rate Approximately 79% of patients recorded successful treatment outcomes, indicating generally positive healthcare interventions. 2. Mortality Rate The dataset shows a mortality rate of approximately 31%, highlighting the need for early diagnosis and timely treatment. 3. Disease Prevalence Diseases such as Malaria, Measles, Typhoid, Tuberculosis, and HIV accounted for most patient cases. 4. …