Researchers at Rutgers University say a digital simulation of patient flow helped identify operational bottlenecks that reduced treatment delays and increased capacity at a blood cancer clinic, according to a study published in the Annals of Operations Research.

The study describes how investigators from the New Brunswick, New Jersey-based Rutgers Cancer Institute and Rutgers Business School created a computer simulation, or "digital twin," of the institute's hematology-oncology clinic. The model was built using electronic health record timestamps and direct observations of patient movement through the clinic, allowing researchers to test workflow changes before implementing them.

At the time of the project, the clinic treated about 50 infusion patients each day while also managing more than 200 outpatient visits for services such as blood tests, transfusions and consultations. Some infusion appointments lasted as long as eight hours.
The analysis found that the primary bottlenecks were laboratory testing and patient scheduling rather than nursing staff. Blood samples were being processed at an off-site laboratory, creating turnaround times of about 90 minutes before treatment could begin. Simulations indicated that moving laboratory services on-site and spreading appointments more evenly throughout the day could shorten average visits by 75 to 90 minutes, even with a 20% increase in patient volume.

Following those changes, laboratory turnaround times fell to less than 30 minutes, and the clinic increased daily infusion capacity from roughly 50 patients to about 80. The clinic also implemented a fast-track workflow that separates supportive care visits, such as transfusions, from cancer treatment appointments.

Andrew Evens, chief physician officer of the Jack & Sheryl Morris Cancer Center and Rutgers Cancer Institute and a senior author of the study, said the approach could be applicable to other oncology practices, although each organization would need to analyze its own operations rather than adopt Rutgers' model directly.

The researchers said similar simulation methods may also be useful in other healthcare settings, including outpatient clinics, emergency departments and surgical units.

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