Healthcare Data Analytics for a U.S Based Private Hospital
Project category
Healthcare Data Analytics for Hospital
Starlake Medical Center
United States
2.5 months
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Project Overview
A well-established U.S private hospital (250 beds, 500+ staff; ~50,000 patients/year) was managing bookings, admissions, discharges, and staffing with manual, siloed processes. This led to long patient wait times, delayed bed turnover, and uneven staff utilization.
We implemented a centralized Healthcare Operations Dashboard in Power BI that unifies data across EHR, scheduling, admissions/discharge (ADT), and revenue cycle systems. The solution adds AI-driven scheduling and real-time monitoring to streamline patient flow and resource allocation.
Key KPIs Tracked
The dashboard is designed to focus on the most critical KPIs for healthcare & hospital operations:
- Appointment wait time & no-show rate
- Admission lead time & discharge turnaround time (D2D)
- Bed occupancy, ALOS (average length of stay), bed turnaround
- OT/OR utilization, room utilization by department
- Staff utilization & staffing gaps by shift/unit
- ED throughput (door-to-doc, LWBS)
- Readmission rate (7/30-day) & clinical escalations
- Billing accuracy, AR days, claim denial rate
Solution Offered — Healthcare Dashboard
A unified Healthcare Operations Dashboard built on Power BI that centralizes patient flow, ADT, bed management, OR/OT usage, staffing, and revenue cycle metrics. The system combines real-time monitoring, AI-driven scheduling, and governed data modeling to improve wait times, bed turnover, utilization, staffing efficiency, ED throughput, readmissions, and billing accuracy.
Requirement Gathering & Data Integration
- We connected all major hospital systems—EHR/EMR, ADT, scheduling, OR/OT, staffing, and billing—so every operational KPI sits in one place. This brought together appointment data, ED timestamps, bed details, procedure logs, and financial records.
- We also built a secure data pipeline (APIs/ETL) to pull in real-time updates for wait times, occupancy, staff rosters, ED flow, OR usage, AR days, and denial reasons without manual effort.
Data Quality & Modeling
- We cleaned and standardized all timestamps and medical codes (departments, procedures, encounter types) to ensure accurate reporting of ALOS, occupancy, discharge times, OR delays, and readmissions.
- A structured data model (star schema) was created for appointments, encounters, beds, staff, ED events, OR/OT cases, and revenue, enabling dependable dashboards for staffing use, room use, AR days, denials, and clinical escalations.
AI Scheduling & Forecasting
- We built predictive models to estimate clinic demand, ED arrivals, OR case volume, bed needs, and readmission risk—helping teams reduce wait times, manage surges, and prevent unplanned bottlenecks.
- AI-powered rostering was implemented to find staffing gaps, assign the right skills to the right shift, reduce overtime, and ensure teams are aligned with peak demand.
Dashboard Design & Automation
- We created a real-time operational dashboard in Power BI featuring patient flow heatmaps, live bed status, discharge readiness lists, ED queues, OR/OT utilization, and revenue cycle insights for AR and denials.
- Automated refresh and alerting were added to notify teams when wait times go up, occupancy hits limits, OR delays occur, staffing issues appear, or billing errors are detected.
Change Management & Governance
- We defined clear KPI rules and ownership for metrics like wait times, ALOS, OR use, staffing gaps, ED throughput, readmissions, AR days, and denials so everyone measures performance the same way.
- Role-based dashboards and hands-on training were provided for admin, nursing, OR, ED, scheduling, and finance teams, ensuring they use the KPIs effectively for daily operations and ongoing improvement.
Key Features of the Dashboard
Clear, real-time visibility that connects patient flow with staffing and capacity—so leaders can act before bottlenecks appear.
Business Benefits
A single source of truth that shortens queues, speeds bed turnover, and aligns staffing to demand—improving both patient experience and financial outcomes.
01
Reduced Wait Times
AI-assisted slotting and proactive surge alerts compress appointment lead times and smooth daily peaks.
02
Faster Admissions & Discharges
ADT orchestration, discharge readiness, and bed-turn timers reduce bottlenecks and unlock capacity.
Optimized Staff Utilization
Demand-aligned rosters balance workloads, cut overtime reliance, and reduce unit-level shortages.
04
Better Throughput & Utilization
Higher OR/OT and room utilization with fewer idle blocks and faster turnarounds.
05
Stronger Financial Performance
Cleaner documentation and billing reduce denials, shorten AR days, and improve cash flow.
Who Gains Actionable Insights from This Dashboard?
Tech Stack Used
Built for real-time hospital operations with unified data, automated pipelines, and AI-driven forecasting. The stack combines Power BI for live insights, SQL warehousing for governed data, and Python-based models for smarter scheduling and resource planning.
Microsoft Power BI
AI Scheduling & Forecasting (Python)
SQL Server Data Warehouse
Results Achieved
Sustained, measurable improvements across access, capacity, staffing, and revenue integrity.
Key Results:
By unifying operations on a real-time Power BI dashboard and adding AI-driven scheduling, the hospital streamlined patient flow, aligned staffing to demand, and improved financial performance—while giving every team clear, actionable insight to run the day.