Tableau Public: https://public.tableau.com/app/profile/denis.king
Hospital leaders must continuously monitor patient flow, capacity utilization, operational bottlenecks, and care outcomes to maintain efficient healthcare delivery.
This project provides an executive-level hospital operations dashboard designed to answer one critical business question:
Where are operational bottlenecks, capacity constraints, and performance risks across the hospital?
Using Tableau, SQL, Python, Excel, and Streamlit, the dashboard combines operational KPIs, department performance monitoring, capacity strain analysis, patient flow analytics, and readmission tracking to support data-driven decision-making.
The solution enables hospital leadership to:
- Monitor hospital-wide operational performance
- Identify capacity constraints and bottlenecks
- Improve patient throughput
- Optimize resource allocation
- Reduce operational risk
- Support patient care delivery through KPI-driven insights
Expected business value includes:
- Improved hospital capacity utilization
- Faster identification of operational bottlenecks
- Improved patient throughput
- Reduced operational strain
- Enhanced healthcare performance monitoring
- Better executive decision-making
Hospitals face ongoing operational challenges including:
- High bed occupancy rates
- Emergency Department congestion
- Patient throughput delays
- Capacity strain across departments
- Resource allocation inefficiencies
- Readmission pressure
Without centralized reporting, leadership teams may struggle to identify emerging operational risks and prioritize improvement initiatives.
This project was developed to provide visibility into hospital performance, patient flow efficiency, and operational bottlenecks across multiple service lines.
This dashboard helps hospital leadership monitor operational KPIs, identify capacity constraints, evaluate department performance, track patient flow efficiency, and support decisions related to resource allocation, patient throughput, capacity planning, and operational improvement initiatives.
| KPI | Business Purpose |
|---|---|
| Total Patients | Measures hospital utilization |
| Average Length of Stay (LOS) | Measures operational efficiency |
| Bed Occupancy Rate | Measures capacity utilization |
| Readmission Rate | Measures quality and continuity of care |
| Average ER Wait Time | Measures patient flow efficiency |
| Treatment Success Rate | Measures clinical outcomes |
| Patient Satisfaction Score | Measures patient experience |
The dashboard provides a comprehensive view of hospital operations, patient flow, capacity management, and department performance.
Focus Areas:
- Executive KPI Monitoring
- Hospital Alert Summary
- Operational Bottleneck Analysis
- Capacity Strain Monitoring
- Department Performance Evaluation
- Executive Decision Support
Focus Areas:
- Admissions Trend Analysis
- Throughput Monitoring
- Visit Outcome Analysis
- Treatment Success Tracking
- Length of Stay Analysis
- Readmission Risk Monitoring
These dashboards support healthcare leadership, operations teams, and decision-support analysts responsible for hospital performance management.
Emergency Department and ICU services experience the highest operational strain due to elevated occupancy levels, longer wait times, and increased throughput pressure, making them the primary drivers of hospital capacity challenges.
This dashboard supports hospital leadership by transforming operational data into actionable insights that improve resource planning, patient flow efficiency, and care delivery.
- Identifies departments experiencing capacity strain
- Improves visibility into bed occupancy and throughput performance
- Highlights readmission trends requiring intervention
- Supports monitoring of Length of Stay drivers
- Centralizes operational KPI reporting
- Enables proactive identification of operational bottlenecks
- Supports data-driven capacity management
- Improves workflow optimization
- Enhances hospital performance reporting
- Strengthens executive decision-making
Increase operational focus on Emergency Department and ICU services through staffing optimization, capacity planning, throughput improvements, and proactive monitoring of occupancy, wait times, and readmission trends.
| Field | Description |
|---|---|
| patient_id | Unique patient encounter identifier |
| department | Hospital department |
| admission_date | Patient admission date |
| discharge_date | Patient discharge date |
| bed_occupancy_rate | Department occupancy percentage |
| er_wait_time | Emergency Department wait time |
| length_of_stay | Patient length of stay |
| readmission_flag | Indicates readmission status |
| treatment_success_rate | Treatment outcome indicator |
| patient_satisfaction | Patient satisfaction score |
The project includes exploratory data analysis, data validation, and KPI engineering designed to improve hospital operations monitoring and healthcare performance reporting.
- Missing value validation
- Duplicate encounter checks
- Department-level performance validation
- Length of Stay (LOS) analysis
- Capacity utilization analysis
- Readmission monitoring
- Wait-time analysis
- KPI consistency validation
- occupancy_band
- capacity_strain_score
- hospital_alert_status
- los_category
- readmission_risk_level
- bottleneck_category
- treatment_success_flag
These engineered features support operational monitoring, capacity planning, patient flow analysis, and executive decision-making.
Business Problem
↓
EDA + Cleaning
↓
Feature Engineering
↓
KPI Engineering
↓
Operational Analysis
↓
Dashboard Development
↓
Business Insights
↓
Decision Support
↓
Business Impact
Emergency Department and ICU services experience the highest operational strain due to elevated occupancy levels, longer wait times, and increased throughput pressure.
Monitor occupancy, wait times, Length of Stay, and readmission trends while prioritizing high-strain departments.
Improve staffing allocation, capacity planning, and patient flow processes within Emergency and ICU services.
Prioritize capacity management and throughput improvement efforts before expanding service demand.
- Tableau
- SQL
- Python
- Streamlit
- Excel
- CSV Data Modeling
- Healthcare KPI Reporting
- GitHub
Hospital-Operations-Analytics/
├── data/
│ └── healthcare_operations_dashboard_950_rows_final.csv
├── screenshots/
│ ├── hero_dashboard.png
│ ├── kpi_scorecard.png
│ ├── capacity_strain_heatmap.png
│ ├── department_performance_matrix.png
│ ├── readmission_risk.png
│ ├── los_analysis.png
│ └── treatment_success.png
├── tableau/
│ └── Hospital_Operations_Analytics.twbx
├── notebooks/
│ └── healthcare_operations_eda.ipynb
├── app/
│ └── streamlit_app.py
└── README.md
git clone https://github.com/Denis0242/Hospital-Operations-Analytics
pip install -r requirements.txt
streamlit run app/streamlit_app.py- Add predictive modeling for readmission risk
- Add patient demand forecasting
- Add department staffing optimization analysis
- Add automated KPI refresh workflows
- Connect to Snowflake, Redshift, or cloud-based healthcare data warehouses
- Dataset is synthetic and created for portfolio purposes.
- No Protected Health Information (PHI) is included.
- Project developed for educational and demonstration purposes.
- This project is not affiliated with or endorsed by Kaiser Permanente or any healthcare organization.