Optimizing Healthcare Efficiency with Power BI: A Live Case Study Using Real-World Hospital Data
Healthcare systems today are drowning in fragmented data. Billing inefficiencies, reporting delays, and manual processes cost organizations both time and money. In this talk, I’ll present a real-world solution: an end-to-end Power BI dashboard that transforms raw hospital data into actionable insights.

Built on a cleaned and enriched version of the Kaggle Hospital Dataset (2019–2024), this dashboard identifies billing anomalies, visualizes cost drivers by medical condition, and segments patient stays to uncover operational inefficiencies.

🔍 Key Features Showcased:

MoM (Month-over-Month) Billing Trend Analysis – Detect unusual cost spikes in real-time

Stay Category Segmentation – Short, Medium, Long, Very Long stays for targeted care strategy

ICD Code Mapping – Linking diagnoses to billing impact for smarter planning

Multi-Hospital Comparison – KPI breakdown across six leading institutions

Self-Service Filters – Designed for non-technical users to explore the data dynamically

⚙️ Technical Stack: Power BI, DAX, Python (data cleanup), Streamlit (embedding)
🤝 Collaborative Credit: Special thanks to Andrew Malinow for the ICD-10 integration guidance

🔊 Audience Takeaways:

How to go from raw, unstructured hospital data to a business-ready reporting tool

Strategies to visualize and act on billing inefficiencies using Power BI

The impact of accessible analytics tools in operational healthcare decision-making

Practical steps to integrate anomaly detection and forecasting into healthcare BI workflows