Project Description This project provides an in-depth analysis of hospital data, focusing on patient demographics, billing, departmental visits, provider ratings, and temporal trends. The analysis aims to offer actionable insights for improving hospital operations, patient care, and financial performance.
Table of Contents
Introduction Data Overview Analysis Summary Overall Patient and Billing Overview Patient Demographics Departmental and Diagnostic Insights Insurance Coverage and Providers Temporal Insights Key Recommendations
Introduction
The project analyzes hospital data to extract valuable insights that can inform better decision-making in healthcare management. The focus is on understanding patient trends, optimizing billing processes, and identifying key areas for improvement.
Data Overview
The data set includes information on patient visits, billing amounts, insurance coverage, provider ratings, and other operational metrics over two years. The analysis was conducted using Power BI.
Analysis Summary
Overall Patient and Billing Overview Total Patients: 4,973 Total Billing: £3 million, with £2 million covered by insurance and £1 million payable by patients. Payment Status: 61.7% paid, 38.3% pending.
Patient Demographics
Gender Distribution: Nearly equal, with 50.05% female and 49.95% male. Age Group: The 50-64 age group was the largest, while the 18-24 age group had the fewest patients. Racial Distribution: Black patients were the largest group, followed by Asian and White patients.
Departmental and Diagnostic Insights
Highest Volume Department: Cardiology, followed by General Surgery and Orthopedics. Top Diagnosis: Hypertension, affecting 2,006 patients.
Insurance Coverage and Providers
Top Insurer: AXA, covering 1,690 patients. Provider Ratings: Dr. Olu Abisola had the highest rating (5.45), while Dr. Sade Kikiola attended to the most patients (1,873).
Temporal Insights
Yearly Trends: 2024 had more visits than 2025. Monthly Trends: January had the highest visits, October the least. Weekly Trends: Most visits occurred on weekends.
Key Recommendations
Enhance Payment Collection: Focus on improving the 38.3% of pending payments to boost revenue.
Targeted Health Initiatives: Implement programs for middle-aged and senior populations, given their higher hospital utilization.
Expand Cardiology Services: Given its high patient volume and billing, further investment in this department could be beneficial.
Optimize Weekend Services: With weekends seeing the highest patient traffic, staffing and resources should be adjusted accordingly.
Insurance Partnerships: Strengthen relationships with top insurers like AXA to ensure coverage aligns with patient needs.
Tools and Technologies Data Analysis: PowerBI, Excel Data Visualization: PowerBI