Reconciling quality and cost: A case study in interventional radiology

Area of Science:

• Healthcare Management
• Operations Research
• Radiology

Background:

• Interventional radiology suites face complex cost structures including capacity, supply, and delay.
• Optimizing operational efficiency is crucial for managing healthcare costs and improving patient care.

Purpose of the Study:

• To introduce a method for calculating delay costs in interventional radiology.
• To analyze the relationship between service quality and overall operational costs.
• To determine optimal capacity allocation for improved efficiency.

Main Methods:

• Calculated total costs encompassing capacity, supply, and delay.
• Determined capacity costs from labor, lease, and overhead expenses.
• Quantified supply costs based on procedural material usage.
• Calculated delay and marginal delay costs using queueing models and inpatient waiting times.

Main Results:

• Quality improvements enhanced patient safety and outcomes.
• Average daily delay costs decreased significantly (from 1275 € to 294 €).
• Marginal delay costs reduced substantially (from ~2000 € to ~500 €).
• Annual savings of approximately 290,000 € were achieved, including cost transfers and increased revenue.
• Optimal daily capacity was identified as 4.2 procedures.

Conclusions:

• A novel approach for calculating delay costs and optimizing capacity allocation was successfully developed.
• Enhancing quality in terms of safety, outcome, efficiency, and timeliness directly leads to cost reduction.
• A mismatch between demand and capacity negatively impacts both quality and cost, while full utilization with random demand increases waiting times and expenses.