30–50% wait-time reduction
Higher provider utilization
Live operational alerts
Reported outcomes from this engagement; not projected results for a new pilot.Patient flowExample
Where is the queue building?
Arrived
Room ready
With provider
Front desk reviews the arrival queue
Results
After rollout, the clinic delivered:
- 30–50% wait-time reduction through clearer scheduling and resource allocation.
- Higher utilization of physicians and exam rooms without stretching patient experience.
- Better satisfaction scores as bottlenecks became visible and fixable.
- Faster billing cycles with earlier visibility into denial patterns.
- Leadership decisions backed by live KPIs instead of anecdotal end-of-month reviews.
The Challenge
A multi-provider clinic needed to balance patient care with throughput and financial health. They faced:
- Long Patient Wait Times: Scheduling and workflow bottlenecks drove frustration at the front desk and in exam rooms.
- Underutilized Resources: Little visibility into physician and room capacity left slots idle while other areas ran over.
- Billing Inefficiencies: Cycle delays and denials slowed cash flow.
- No Single Performance View: Leadership couldn't see wait, utilization, and satisfaction in one place.
- Scattered Systems: EHR, scheduling, billing, and surveys didn't talk to each other.
What We Built
We delivered centralized KPI tracking and operational alerting:
- System Integration: Connected EHR/EMR, practice management, billing, and survey sources via APIs and secure database links.
- Unified Data Platform: Aggregated clinic data in Microsoft Fabric with HIPAA-aligned controls.
- KPI Dashboards: Built role-specific Power BI views for managers and providers covering wait times, utilization, satisfaction, and financial metrics.
- Trend Analysis: Surfaced performance trends across locations and providers for targeted coaching.
- Automated Reporting: Scheduled daily and weekly scorecards so leadership stopped chasing spreadsheets.
- Root Cause Drill-downs: Enabled click-through from wait-time spikes to underlying schedule and staffing drivers.


