Computer simulation and stochastic programming to reduce patient wait times in an outpatient infusion center.

Abstract

181 Background: As cancer treatment demand outpaces the capacity of outpatient facilities, providers are challenged to provide timely, cost-effective, safe, and patient-centered care. Reduction in patient wait times can help address these challenges through more efficient care delivery. Operations research techniques such as simulation and stochastic programming can inform more efficient patient scheduling. Methods: After 60 hours of observation by two students in one NCI-designated comprehensive cancer center's outpatient infusion center, 9 months of data from the electronic medical record and scheduling systems were used to calculate patient wait times, defined as the difference between scheduled time to begin infusion and actual time and actual administration time. After mapping the patient flow through the center, a computer simulation model was created to examine the effects on patient wait times and total hours of operation under different scheduling paradigms. To create different appointment schedules, both simple heuristic approaches and a more complex stochastic programming model were developed. These methods take into account the variability in infusion times. We generated 35 appointment schedules and evaluated their performance by running 100 replications for each one. Results: The baseline average patient wait time was 130.48 minutes (95% CI 122.38-138.68). Computer simulation results show that schedules generated by the stochastic programming model perform better than baseline and simple heuristics, reaching a 70% reduction in waiting times. Schedules that allocated patients with longer infusion times to earlier appointments resulted in both reduced average patient wait times and total hours of operation. Conclusions: Operations research techniques can improve care delivery in an outpatient infusion center. Based on our results from the computer simulation model, scheduling patients with longer infusion times earlier in the day results in shorter patient waiting times and total length of day of operations. Next steps include guideline development for appointment scheduling staff that attains maximal efficiency.