This project focuses on analyzing hospital data using SQL to uncover meaningful insights about patient care, resource utilization, and medical expenses.
The SQL queries address real-world business questions such as patient volume, doctor availability, departmental performance, hospital stays, and financial trends.
- SQL (PostgreSQL/MySQL compatible) – Data querying & analysis
- Data Types – VARCHAR, INT, DATE, NUMERIC
- Functions Used – Aggregate (SUM, AVG, MAX), Date Functions, CAST, GROUP BY, ORDER BY, LIMIT
- File Format –
.sqlscripts,.pdffor project report
The dataset contains hospital-level records including:
- Hospital Name
- Location (City)
- Department
- Number of Doctors
- Number of Patients
- Admission & Discharge Dates
- Medical Expenses
Hospitals and healthcare administrators often struggle to monitor patient loads, doctor availability, and financial performance. Without structured analysis, it becomes difficult to optimize resources, reduce costs, and improve patient outcomes.
- Analyze patient volume by hospital, department, and city
- Evaluate doctor-to-patient ratios and average availability
- Track medical expenses across hospitals and time periods
- Measure hospital stay durations and department-wise averages
- Identify top-performing and underperforming departments
- Q1: Total number of patients across all hospitals
- Q2: Average number of doctors per hospital
- Q3: Top 3 departments with the highest patient counts
- Q4: Hospital with maximum medical expenses
- Q5: Daily average medical expenses per hospital
- Q6: Longest hospital stay duration
- Q7: Total patients treated per city
- Q8: Average patient stay length per department
- Q9: Department with the lowest number of patients
- Q10: Monthly medical expenses report
- Resource Allocation: Helped identify cities and departments with the highest patient volumes, guiding better staffing decisions.
- Financial Analysis: Tracked hospitals with the highest and lowest expenses, enabling cost control measures.
- Operational Efficiency: Measured patient stay durations, highlighting areas for process improvement.
- Strategic Decisions: Monthly expense trends revealed seasonal spikes, supporting budget planning.
This SQL project demonstrates how structured queries can transform raw hospital records into actionable insights.
By addressing patient care trends, financial performance, and departmental efficiency, the analysis supports data-driven healthcare management.