Client Background:
The client operated a multi-site imaging infrastructure portfolio spanning MRI, CT, and ultrasound, requiring coordination across clinical operations, scheduling, radiology, and financial management.
Challenges:
- Limited visibility into modality-wise utilization, throughput, and idle capacity across hospital sites.
- Fragmented workflows affecting scheduling efficiency, referral management, and demand allocation.
- Unclear profitability differences across imaging modalities and scan types.
- Pressure to expand imaging capacity while controlling costs and maximizing existing asset productivity.
Engagement Objective:
The engagement aimed to evaluate imaging asset utilization and profitability, identify operational and demand-related inefficiencies, and develop a practical optimization roadmap to improve returns from existing infrastructure while informing future capacity decisions.
Approach:
The study combined secondary research, expert interviews, and operational benchmarking to assess imaging infrastructure performance. Our team:
- Compared modality-wise utilization, throughput, and capacity performance across hospital sites and peer networks
- Evaluated scan-mix economics, referral pathways, and demand distribution to identify revenue and capacity improvement opportunities
- Examined scheduling, staffing, workflows, maintenance, and service-cost structures to identify efficiency levers
- Developed utilization and expansion scenarios to assess capacity requirements and alternatives to significant capital expenditure
Solutions Offered:
- Modality-wise benchmarking of MRI, CT, and ultrasound utilization and throughput.
- Assessment of scan-mix profitability, referral leakage, and demand distribution.
- Identification of scheduling, staffing, and maintenance cost optimization opportunities.
- Capacity planning scenarios comparing utilization improvements with infrastructure expansion.
- Prioritized roadmap for imaging productivity, profitability, and infrastructure planning.
Client Impact:
- Improved MRI, CT, and ultrasound utilization by identifying throughput bottlenecks, scheduling gaps, and idle capacity.
- Improved profitability per imaging asset through scan-mix optimization, referral alignment, staffing efficiency, and maintenance cost control.
- Unlocked additional imaging capacity through benchmarking, demand redistribution, and throughput optimization, reducing reliance on new capital expenditure.
- Enabled data-driven expansion decisions through scenario-based capacity modeling, minimizing unnecessary investments and supporting scalable growth.
Outcome Snapshot:
