MODELING THE IMPACT OF MAKE-AHEAD CHEMOTHERAPY DRUG POLICIES THROUGH DISCRETE-EVENT SIMULATION

During an outpatient chemotherapy infusion visit, patients typically have blood work done, see their oncologist in the clinic, wait for the pharmacy to prepare their drugs, and receive their infusion. The time variability at each of these steps can introduce delays, which not only negatively impact the patient but propagate through the system to negatively impact other patients and staff as well. One major opportunity to reduce patient waiting time is by pre-mixing (i.e., making drugs before the patient arrives for their infusion appointment) at the pharmacy. This, however, requires careful consideration of the trade-off between time savings versus the potential cost of wasting a drug if the patients are deemed ineligible for treatment on the day of their appointment. We present a discrete-event simulation model to predict the effectiveness of various make-ahead drug policies utilizing data from our collaborators at the University of Michigan Rogel Cancer Center (UMRCC).