Improving workflow control in radiotherapy using discrete-event simulation

Bruno Vieira*, Derya Demirtas, Jeroen B. Van De Kamer, Erwin W. Hans, Wim Van Harten

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background: In radiotherapy, minimizing the time between referral and start of treatment (waiting time) is important to possibly mitigate tumor growth and avoid psychological distress in cancer patients. Radiotherapy pre-treatment workflow is driven by the scheduling of the first irradiation session, which is usually set right after consultation (pull strategy) or can alternatively be set after the pre-treatment workflow has been completed (push strategy). The objective of this study is to assess the impact of using pull and push strategies and explore alternative interventions for improving timeliness in radiotherapy. Methods: Discrete-event simulation is used to model the patient flow of a large radiotherapy department of a Dutch hospital. A staff survey, interviews with managers, and historical data from 2017 are used to generate model inputs, in which fluctuations in patient inflow and resource availability are considered. Results: A hybrid (40% pull/60% push) strategy representing the current practice (baseline case) leads to 12% lower average waiting times and 48% fewer first appointment rebooks when compared to a full pull strategy, which in turn leads to 41% fewer patients breaching the waiting time targets. An additional scenario analysis performed on the baseline case showed that spreading consultation slots evenly throughout the week can provide a 21% reduction in waiting times. Conclusions: A 100% pull strategy allows for more patients starting treatment within the waiting time targets than a hybrid strategy, in spite of slightly longer waiting times and more first appointment rebooks. Our algorithm can be used by radiotherapy policy makers to identify the optimal balance between push and pull strategies to ensure timely treatments while providing patient-centered care adapted to their specific conditions.

Original languageEnglish
Article number199
Number of pages13
JournalBMC medical informatics and decision making
Volume19
Issue number199
DOIs
Publication statusPublished - 24 Oct 2019

Fingerprint

Workflow
Radiotherapy
Referral and Consultation
Appointments and Schedules
Therapeutics
Patient-Centered Care
Administrative Personnel
Neoplasms
Interviews
Psychology
Growth

Keywords

  • Discrete-event simulation
  • Radiotherapy
  • Resource planning
  • Waiting times
  • Workflow control

Cite this

@article{f97c42154ea04459a43964b955de4927,
title = "Improving workflow control in radiotherapy using discrete-event simulation",
abstract = "Background: In radiotherapy, minimizing the time between referral and start of treatment (waiting time) is important to possibly mitigate tumor growth and avoid psychological distress in cancer patients. Radiotherapy pre-treatment workflow is driven by the scheduling of the first irradiation session, which is usually set right after consultation (pull strategy) or can alternatively be set after the pre-treatment workflow has been completed (push strategy). The objective of this study is to assess the impact of using pull and push strategies and explore alternative interventions for improving timeliness in radiotherapy. Methods: Discrete-event simulation is used to model the patient flow of a large radiotherapy department of a Dutch hospital. A staff survey, interviews with managers, and historical data from 2017 are used to generate model inputs, in which fluctuations in patient inflow and resource availability are considered. Results: A hybrid (40{\%} pull/60{\%} push) strategy representing the current practice (baseline case) leads to 12{\%} lower average waiting times and 48{\%} fewer first appointment rebooks when compared to a full pull strategy, which in turn leads to 41{\%} fewer patients breaching the waiting time targets. An additional scenario analysis performed on the baseline case showed that spreading consultation slots evenly throughout the week can provide a 21{\%} reduction in waiting times. Conclusions: A 100{\%} pull strategy allows for more patients starting treatment within the waiting time targets than a hybrid strategy, in spite of slightly longer waiting times and more first appointment rebooks. Our algorithm can be used by radiotherapy policy makers to identify the optimal balance between push and pull strategies to ensure timely treatments while providing patient-centered care adapted to their specific conditions.",
keywords = "Discrete-event simulation, Radiotherapy, Resource planning, Waiting times, Workflow control",
author = "Bruno Vieira and Derya Demirtas and {Van De Kamer}, {Jeroen B.} and Hans, {Erwin W.} and {Van Harten}, Wim",
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Improving workflow control in radiotherapy using discrete-event simulation. / Vieira, Bruno; Demirtas, Derya; Van De Kamer, Jeroen B.; Hans, Erwin W.; Van Harten, Wim.

In: BMC medical informatics and decision making, Vol. 19, No. 199, 199, 24.10.2019.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Improving workflow control in radiotherapy using discrete-event simulation

AU - Vieira, Bruno

AU - Demirtas, Derya

AU - Van De Kamer, Jeroen B.

AU - Hans, Erwin W.

AU - Van Harten, Wim

PY - 2019/10/24

Y1 - 2019/10/24

N2 - Background: In radiotherapy, minimizing the time between referral and start of treatment (waiting time) is important to possibly mitigate tumor growth and avoid psychological distress in cancer patients. Radiotherapy pre-treatment workflow is driven by the scheduling of the first irradiation session, which is usually set right after consultation (pull strategy) or can alternatively be set after the pre-treatment workflow has been completed (push strategy). The objective of this study is to assess the impact of using pull and push strategies and explore alternative interventions for improving timeliness in radiotherapy. Methods: Discrete-event simulation is used to model the patient flow of a large radiotherapy department of a Dutch hospital. A staff survey, interviews with managers, and historical data from 2017 are used to generate model inputs, in which fluctuations in patient inflow and resource availability are considered. Results: A hybrid (40% pull/60% push) strategy representing the current practice (baseline case) leads to 12% lower average waiting times and 48% fewer first appointment rebooks when compared to a full pull strategy, which in turn leads to 41% fewer patients breaching the waiting time targets. An additional scenario analysis performed on the baseline case showed that spreading consultation slots evenly throughout the week can provide a 21% reduction in waiting times. Conclusions: A 100% pull strategy allows for more patients starting treatment within the waiting time targets than a hybrid strategy, in spite of slightly longer waiting times and more first appointment rebooks. Our algorithm can be used by radiotherapy policy makers to identify the optimal balance between push and pull strategies to ensure timely treatments while providing patient-centered care adapted to their specific conditions.

AB - Background: In radiotherapy, minimizing the time between referral and start of treatment (waiting time) is important to possibly mitigate tumor growth and avoid psychological distress in cancer patients. Radiotherapy pre-treatment workflow is driven by the scheduling of the first irradiation session, which is usually set right after consultation (pull strategy) or can alternatively be set after the pre-treatment workflow has been completed (push strategy). The objective of this study is to assess the impact of using pull and push strategies and explore alternative interventions for improving timeliness in radiotherapy. Methods: Discrete-event simulation is used to model the patient flow of a large radiotherapy department of a Dutch hospital. A staff survey, interviews with managers, and historical data from 2017 are used to generate model inputs, in which fluctuations in patient inflow and resource availability are considered. Results: A hybrid (40% pull/60% push) strategy representing the current practice (baseline case) leads to 12% lower average waiting times and 48% fewer first appointment rebooks when compared to a full pull strategy, which in turn leads to 41% fewer patients breaching the waiting time targets. An additional scenario analysis performed on the baseline case showed that spreading consultation slots evenly throughout the week can provide a 21% reduction in waiting times. Conclusions: A 100% pull strategy allows for more patients starting treatment within the waiting time targets than a hybrid strategy, in spite of slightly longer waiting times and more first appointment rebooks. Our algorithm can be used by radiotherapy policy makers to identify the optimal balance between push and pull strategies to ensure timely treatments while providing patient-centered care adapted to their specific conditions.

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