Capacity Prioritization Initiative Reduced the Wait Time for Port Placement and Facilitated Increased Volume of Port Placements at a Large County Health System

Reducing Wait Times for Radiology Exams Around Holiday Periods: A Monte Carlo Simulation

Reducing patient wait times is a key operational goal and impacts patient outcomes. The purpose of this study is to explore the effects of different radiology scheduling strategies on exam wait times before and after holiday periods at an outpatient imaging facility using computer simulation. An idealized Monte Carlo simulation of exam scheduling at an outpatient imaging facility was developed based on the actual distribution of scheduled exams at outpatient radiology sites at a tertiary care medical center. Using this simulation, we examined three scheduling strategies: (1) no scheduling modifications, (2) increase imaging capacity before or after the holiday (i.e. increase facility hours), and (3) use a novel rolling release scheduling paradigm. In the third scenario, a fraction of exam slots are blocked to long-term follow-up exams and made available only closer to the exam date, thereby preventing long-term follow-up exams from filling the schedule and ensuring slots are available for non-follow-up exams. We examined the effect of these three scenarios on utilization and wait times, which we defined as the time from order placement to exam completion, during and after the holiday period. The baseline mean wait time for non-follow-up exams was 5.4 days in our simulation. When no scheduling modifications were made, there was a significant increase in wait times in the week preceding the holiday when compared to baseline (10.0 days vs 5.4 days, p < 0.01). Wait times remained elevated for 4 weeks following the holiday. Increasing imaging capacity during the holiday and post-holiday period by 20% reduced wait times by only 6.2% (9.38 days vs 10.0 days, p < 0.01). Increasing capacity by 50% resulted in a 7.1% reduction in wait times (9.28 days, p < 0.01), and increasing capacity by 100% resulted in a 13% reduction in wait times (8.75 days, p < 0.01). In comparison, using a rolling release model produced a reduction in peak wait times equivalent to doubling capacity (8.76 days, p < 0.01) when 45% of slots were reserved. Improvements in wait times persisted even when rolling release was limited to the 3 weeks preceding or 1 week following the holiday period. Releasing slots on a rolling basis did not significantly decrease utilization or increase wait times for long-term follow-up exams except in extreme scenarios where 80% or more of slots were reserved for non-follow-up exams. A rolling release scheduling paradigm can significantly reduce wait time fluctuations around holiday periods without requiring additional capacity or impacting utilization.