An interactive Streamlit web app for visualizing and analyzing healthcare data. This dashboard provides real-time insights into patient demographics, doctor performance, treatment trends, hospital facility utilization, and billing analysis using Python.
🔗 Click here to view the Live Streamlit App
-
📊 Patient Demographics Analysis
- Age & Gender distribution
- City-wise patient count
- Patient feedback ratings
-
🩺 Doctor Performance Dashboard
- Average ratings and reviews
- Specialty-wise analysis
- Treatment load per doctor
-
💉 Treatment Insights
- Top treatments & diagnosis trends
- Admission & discharge patterns
- Monthly treatment volume
-
🏨 Facility Utilization
- Department & ward usage
- Bed occupancy by time
- Daily footfall analysis
-
💰 Billing Dashboard
- Revenue trends
- Treatment cost breakdown
- Insurance vs Non-insurance billing
- Frontend: Streamlit
- Backend: Python
- Libraries Used:
pandas,numpymatplotlib,seaborn,plotlystreamlit
-
Increase doctor and nurse availability in high-admission areas like Emergency or Cardiology to reduce wait times and improve care.
-
Identify doctors with average ratings below 3 and schedule training sessions or feedback reviews to enhance patient experience.
-
Run health awareness campaigns in cities or regions with the most patient visits to attract more patients and build trust.
-
Review and optimize treatments with the highest average costs to ensure better affordability for patients.
-
Speed up the discharge process by streamlining workflows, especially for departments with long hospital stays.