The encyclopedia · Engineering & Operations · Operational decision · 2009–2013
Duke found nurses bottlenecked chemotherapy, so it optimized nurse schedules.
Simulation showed nurses bottlenecked patient flow at Duke's cancer center; mixed-integer programming and simulation-optimization fixed the nurse schedule.
Duke Cancer Institute
The solution
Duke Cancer Institute, a large cancer center, wanted to improve patient access to chemotherapy. Patients flow through the outpatient clinic, radiology, pharmacy, laboratory services, and the oncology treatment facility, where waiting times hurt the experience.
Researchers built a discrete-event simulation to predict patient waiting time and resource utilization across the center. The studies showed that nurse unavailability during oncology treatment created a serious bottleneck in patient flow.
They then developed a mixed-integer programming model to relieve the bottleneck by optimizing weekly and monthly scheduling of different nurse types, and a simulation-optimization model to optimize nurse shift start times. Duke Cancer Institute implemented the recommendations.
Why it worked
- Simulation pointed at a bottleneck that intuition and budgets had missed.
- Scheduling fixes are cheap relative to adding treatment capacity.
- The same tools let the center test changes before touching the clinic.
What can be applied
Before adding capacity, simulate the whole patient journey—the real bottleneck may be a resource nobody suspected, and scheduling fixes can cost nothing compared with building more.
Aftermath
The work was a finalist for the 2012 INFORMS Daniel H. Wagner Prize and published in Interfaces in 2013; Duke implemented the recommended schedules.
Sources
- Improving Patient Access to Chemotherapy Treatment at Duke Cancer Institute
- Improving Patient Access to Chemotherapy Treatment at Duke Cancer Institute
- 2012 Wagner Prize Finalist – University of Michigan & Duke Medicine
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