Abstract

Radiotherapy (RT) resources need to be used wisely to balance workload and patient throughput. There are no known strategies on how to plan resource use around longer vacation periods to avoid patient waiting times. We created a simulation model over the RT workflow to evaluate different scenarios for this purpose. The simulation model mimics a large modern RT department in Sweden. It was based on real data on patient referral patterns and resource use extracted from clinical systems (3666 treatment courses). Workshops with managers and staff were held to investigate nine different scenarios for the summer vacation period including one scenario to validate the model. Different capacity reductions, vacation period lengths and timing of the vacation periods between the preparatory part of the RT workflow and the treatment part were evaluated. For an eight-week period, resource utilization was predicted to be high both before and after the vacation period regardless of timing. However, more patients would be waiting with completed preparations with simultaneous vacation periods than when the preparatory part started one-two weeks prior to the treatment part. With shorter vacation periods, treatment would require overtime during the vacation period with higher levels of patients waiting compared to an eight-week scenario. Our proposed strategy aided managers to identify a preferred scenario for the summer vacation period with the preparatory part starting one-two weeks prior to the treatment part for an eight-week vacation period. This can help other RT departments to plan for similar situations.

Highlights

  • The global cancer incidence is increasing, with the consequence of an increased demand for radiotherapy (RT) [1]

  • Model development and simulations were conducted in Stella Ar­ chitect, in close collaboration between experienced modelers (PH, SH, and MG) and experts in RT (JL, TBE, and CO)

  • Summer vacation period to 50% for both parts, fewer patients were waiting with completed preparations compared to the simultaneous reduction (Scenario 7; Fig. 2b)

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Summary

Introduction

The global cancer incidence is increasing, with the consequence of an increased demand for radiotherapy (RT) [1]. Resource planning in RT is important to establish or maintain short waiting times as long waiting times to RT can impact clinical outcomes and can cause high levels of anxiety for the patient, their relatives, and caregivers [4]. The available resources must, be used in the best possible way without jeopardizing clinical outcomes, without exhausting RT staff, and at the same time handle the expected increase in referrals. This means that the RT community must be open for new working methods to meet future challenges, but the already high workload in RT limits the possibilities to evaluate and implement such strategies

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