How Simulation Modeling Reduces Oncology Clinic Wait Times | Dr. Andrew Evens

How can a busy cancer center nearly double its daily patient capacity without adding staff or expanding physical space? In this interview, Dr. Andrew Evens (Rutgers Cancer Institute) details how his team used simulation modeling to uncover hidden operational bottlenecks in a high-volume blood cancer and bone marrow transplant unit—reducing wait times and transforming clinic flow. Watch the full video & read the article on Oncology Data Advisor: https://oncdata.com/simulation-modeling-reducing-oncology-clinic-wait-times What You’ll Learn in This Episode 🔹Mapping Multi-Step Oncology Workflows: Why sequential visits—encompassing check-in, consent, lab testing, vitals, physician evaluation, and infusion—create compound delays across cancer centers. 🔹 Leveraging Simulation Modeling: How partnering with healthcare analytics researchers allowed the team to simulate operational changes (such as staffing levels and lab turnaround times) before implementing them in the clinic. 🔹 Uncovering Hidden Bottlenecks: Why the simulation model revealed laboratory turnaround times and a unified intake queue for all infusion patients as the real barriers, rather than staffing ratios. 🔹 The "Fast Track" Redesign: How separating supportive care patients (transfusions, IV fluids) from those receiving anticancer therapy reduced congestion and nearly doubled daily treatment capacity. 🔹 Operational AI & Cross-Disciplinary Leadership: How disease-agnostic modeling serves as a strategic application of operational AI, and why institutions can solve complex operational challenges by leveraging internal multidisciplinary talent.