Abstract
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.
| Original language | English |
|---|---|
| Article number | 83 |
| Journal | BMC Medical Research Methodology |
| Volume | 22 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 27 Mar 2022 |
Bibliographical note
Funding Information:This study was financed by a grant from ZonMW (grant number 80-84600-98-1002). ZonMW otherwise was not involved in this study. This study is created in collaboration with the Technology Assessment of Next Generation sequencing for personalized Oncology (TANGO) consortium.
Funding Information:
Dr. van Harten and Dr. Retèl have both received non-restricted research grants from Agendia B.V. and Novartis. Dr. IJzerman received a non-restricted research grant from Illumina. All other authors have no conflicts of interest to disclose.
Publisher Copyright:
© 2022, The Author(s).
