Live Dashboard: healthcare-dashboard-v2.streamlit.app
Analyzed hospital management data to identify $427,149 in annual revenue recovery opportunities. Discovered 51.5% no-show rate (vs. 15-20% industry standard) and quantified ROI projections for operational improvements. Delivered interactive dashboard enabling healthcare administrators to optimize resource allocation, reduce costs, and improve patient outcomes.
Key Findings:
- $427K revenue at risk from incomplete appointments (77.5% of total potential revenue)
- 51.5% no-show rate creates $213K annual recovery opportunity
- Dermatology services generate highest revenue per appointment ($2,896 avg)
- Peak demand: Tuesdays at 3:00 PM requiring dynamic staffing adjustments
Organization: Multi-specialty hospital system with 50 active patients, 10 physicians across 3 specializations Business Challenge: Suboptimal resource allocation leading to revenue loss and operational inefficiencies Stakeholders: Hospital operations team (patient flow), finance team (cost management), quality team (patient experience)
Deliverable Audience: Healthcare executives and department managers requiring actionable insights for operational optimization and strategic planning.
- Source: Hospital Management System (Kaggle)
- Scope: 12 months of operational data (2023)
- Volume: 200 appointments, 50 patients, 10 doctors, 200 treatments, 200 billing records
Patients Table: patient_id, demographics, insurance_provider, registration_date
├── (1:M) Appointments: appointment_id, patient_id, doctor_id, date, time, status
├── (1:1) Treatments: treatment_id, appointment_id, treatment_type, cost
└── (1:1) Billing: bill_id, patient_id, treatment_id, amount, payment_status
Doctors Table: doctor_id, specialization, years_experience, hospital_branch
- Data Processing: Python (pandas, numpy) for ETL and feature engineering
- Analytics: scikit-learn for no-show prediction modeling, statistical analysis
- Visualization: Plotly for interactive charts and business intelligence
- Deployment: Streamlit Cloud for live web application
- Total Potential Revenue: $551,249 across all scheduled appointments
- Realized Revenue: $124,100 from completed appointments only (22.5%)
- Revenue Leakage: $427,149 from no-shows, cancellations, and incomplete care cycles
Revenue by Appointment Status:
- Completed: $124,100 (23% of appointments)
- No-show: $142,678 (26% of appointments)
- Cancelled: $152,045 (25.5% of appointments)
- Scheduled: $132,427 (25.5% of appointments)
- Patient Demographics: 45.2 years average age, 62% male, 38% female
- Utilization Patterns: 100% doctor utilization rate, 96% patient engagement
- Peak Demand: Tuesday 3:00 PM (28 appointments), requiring capacity optimization
- Specialization Mismatch: 49% pediatric capacity vs. 43-year patient average
No-Show Risk Model (Random Forest):
- Model Accuracy: 53% on test set
- Top Risk Factors: Treatment cost (17.7%), patient age (16.1%), appointment hour (12.7%)
- Business Application: Identify high-risk appointments for proactive intervention
1. No-Show Reduction Program
- Insight: 51.5% no-show rate vs. 15-20% industry benchmark
- Recommendation: Implement SMS/email reminder system 24-48 hours before appointments
- Impact: Reduce no-show rate to 25%, recovering $213,575 annually
- ROI: 850% return on $25,000 implementation cost
2. Peak Hour Staffing Optimization
- Insight: Tuesday 3:00 PM peak demand (28 appointments) creates bottlenecks
- Recommendation: Increase staffing capacity during identified peak periods
- Impact: 15-20% improvement in patient throughput efficiency
3. Resource Reallocation
- Insight: 49% pediatric appointments but 43-year average patient age
- Recommendation: Cross-train pediatric staff in adult specializations, recruit adult medicine specialists
- Impact: Better supply-demand alignment, reduced wait times
4. Revenue Mix Optimization
- Insight: Dermatology generates $2,896 average revenue per appointment vs. $2,642 pediatrics
- Recommendation: Expand dermatology capacity by 25%, target marketing for high-value services
- Impact: 15-25% revenue increase through optimized service mix
Live Application: healthcare-dashboard-v2.streamlit.app
- Executive Dashboard: KPIs, revenue opportunities, completion rates
- Operations Analytics: Demand heatmaps, doctor utilization, peak period analysis
- Financial Analytics: Revenue breakdown, ROI calculator, payment method analysis
- Quality Analytics: Patient demographics, completion patterns, satisfaction drivers
- Business Recommendations: Strategic action items with quantified impact
- ROI Calculator: Model financial impact of no-show reduction strategies
- Demand Heatmap: Visualize appointment patterns by hour and day
- Revenue Recovery Tracker: Monitor progress toward $427K opportunity
# Key analytical functions
def calculate_healthcare_kpis(data):
# Industry-standard metrics: ALOS, bed occupancy, cost per discharge
def analyze_demand_patterns(appointments):
# Time series analysis, peak identification, seasonality
def build_noshow_prediction_model(features):
# Random Forest classifier with feature importance analysis- Local Development: Python virtual environment with Streamlit
- Version Control: GitHub with automated deployment triggers
- Production: Streamlit Cloud with automatic scaling and SSL
- Data Privacy: Anonymized patient data, HIPAA-compliant practices
- Revenue Opportunity: $427,149 identified and prioritized
- Cost Reduction: 50% no-show rate improvement = $213,575 annual savings
- Operational Efficiency: Dynamic staffing recommendations for 15-20% throughput gains
- Industry KPIs: Average Length of Stay, bed utilization, cost per patient discharge
- Regulatory Awareness: HIPAA compliance, healthcare data privacy standards
- Stakeholder Alignment: Operations, finance, and quality team perspectives
- Name: Abhinav Konagala
- LinkedIn: linkedin.com/in/abhinav-konagala
- Email: akdhpo+work@pm.me