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Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer

BACKGROUND: This study shows how dynamic simulation modeling can be applied in the context of the nationwide implementation of Whole Genome Sequencing (WGS) for non-small cell lung cancer (NSCLC) to inform organizational decisions regarding the use of complex and disruptive health technologies and h...

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Autores principales: van de Ven, Michiel, IJzerman, Maarten, Retèl, Valesca, van Harten, Wim, Koffijberg, Hendrik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962015/
https://www.ncbi.nlm.nih.gov/pubmed/35350994
http://dx.doi.org/10.1186/s12874-022-01571-3
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author van de Ven, Michiel
IJzerman, Maarten
Retèl, Valesca
van Harten, Wim
Koffijberg, Hendrik
author_facet van de Ven, Michiel
IJzerman, Maarten
Retèl, Valesca
van Harten, Wim
Koffijberg, Hendrik
author_sort van de Ven, Michiel
collection PubMed
description BACKGROUND: This study shows how dynamic simulation modeling can be applied in the context of the nationwide implementation of Whole Genome Sequencing (WGS) for non-small cell lung cancer (NSCLC) to inform organizational decisions regarding the use of complex and disruptive health technologies and how these decisions affect their potential value. METHODS: Using the case of the nationwide implementation of WGS into clinical practice in lung cancer in the Dutch healthcare system, we developed a simulation model to show that including service delivery features across the diagnostic pathway can provide essential insight into the affordability and accessibility of care at the systems level. The model was implemented as a hybrid Agent-Based Model and Discrete-Event Simulation model in AnyLogic and included 78 hospital agents, 7 molecular tumor board agents, 1 WGS facility agent, and 5313 patient agents each year in simulation time. RESULTS: The model included patient and provider heterogeneity, including referral patterns, capacity constraints, and diagnostic workflows. Patient preference and adoption by healthcare professionals were also modeled. The model was used to analyze a scenario in which only academic hospitals have implemented WGS. To prevent delays in the diagnostic pathway, the capacity to sequence at least 1600 biopsies yearly should be present. There is a two-fold increase in mean diagnostic pathway duration between no patients referred or all patients referred for further diagnostics. CONCLUSIONS: The systems model can complement conventional health economic evaluations to investigate how the organization of the workflow can influence the actual use and impact of WGS. Insufficient capacity to provide WGS and referral patterns can substantially impact the duration of the diagnostic pathway and thus should be considered in the implementation of WGS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01571-3.
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spelling pubmed-89620152022-03-30 Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer van de Ven, Michiel IJzerman, Maarten Retèl, Valesca van Harten, Wim Koffijberg, Hendrik BMC Med Res Methodol Research BACKGROUND: This study shows how dynamic simulation modeling can be applied in the context of the nationwide implementation of Whole Genome Sequencing (WGS) for non-small cell lung cancer (NSCLC) to inform organizational decisions regarding the use of complex and disruptive health technologies and how these decisions affect their potential value. METHODS: Using the case of the nationwide implementation of WGS into clinical practice in lung cancer in the Dutch healthcare system, we developed a simulation model to show that including service delivery features across the diagnostic pathway can provide essential insight into the affordability and accessibility of care at the systems level. The model was implemented as a hybrid Agent-Based Model and Discrete-Event Simulation model in AnyLogic and included 78 hospital agents, 7 molecular tumor board agents, 1 WGS facility agent, and 5313 patient agents each year in simulation time. RESULTS: The model included patient and provider heterogeneity, including referral patterns, capacity constraints, and diagnostic workflows. Patient preference and adoption by healthcare professionals were also modeled. The model was used to analyze a scenario in which only academic hospitals have implemented WGS. To prevent delays in the diagnostic pathway, the capacity to sequence at least 1600 biopsies yearly should be present. There is a two-fold increase in mean diagnostic pathway duration between no patients referred or all patients referred for further diagnostics. CONCLUSIONS: The systems model can complement conventional health economic evaluations to investigate how the organization of the workflow can influence the actual use and impact of WGS. Insufficient capacity to provide WGS and referral patterns can substantially impact the duration of the diagnostic pathway and thus should be considered in the implementation of WGS. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12874-022-01571-3. BioMed Central 2022-03-27 /pmc/articles/PMC8962015/ /pubmed/35350994 http://dx.doi.org/10.1186/s12874-022-01571-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
van de Ven, Michiel
IJzerman, Maarten
Retèl, Valesca
van Harten, Wim
Koffijberg, Hendrik
Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer
title Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer
title_full Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer
title_fullStr Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer
title_full_unstemmed Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer
title_short Developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer
title_sort developing a dynamic simulation model to support the nationwide implementation of whole genome sequencing in lung cancer
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8962015/
https://www.ncbi.nlm.nih.gov/pubmed/35350994
http://dx.doi.org/10.1186/s12874-022-01571-3
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