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ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients
BACKGROUND: Improved multiple sclerosis (MS) diagnosis and increased availability of intravenous disease-modifying treatments can lead to overburdening of infusion centres. This study was focused on developing a decision-support tool to help infusion centres plan their operations. METHODS: A discret...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117085/ https://www.ncbi.nlm.nih.gov/pubmed/35585305 http://dx.doi.org/10.1007/s40258-022-00733-0 |
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author | Lacinova, Kristyna Thokala, Praveen Nicholas, Richard Dobay, Pamela Scalfaro, Erik Angehrn, Zuzanna Brennan, Roisin Boer, Ibolya Lines, Carol Adlard, Nicholas |
author_facet | Lacinova, Kristyna Thokala, Praveen Nicholas, Richard Dobay, Pamela Scalfaro, Erik Angehrn, Zuzanna Brennan, Roisin Boer, Ibolya Lines, Carol Adlard, Nicholas |
author_sort | Lacinova, Kristyna |
collection | PubMed |
description | BACKGROUND: Improved multiple sclerosis (MS) diagnosis and increased availability of intravenous disease-modifying treatments can lead to overburdening of infusion centres. This study was focused on developing a decision-support tool to help infusion centres plan their operations. METHODS: A discrete event simulation model (‘ENTIMOS’) was developed using Simul8 software in collaboration with clinical experts. Model inputs included treatment-specific clinical parameters, resources such as infusion chairs and nursing staff, and costs, while model outputs included patient throughput, waiting time, queue size, resource utilisation, and costs. The model was parameterised using characteristics of the Charing Cross Hospital Infusion Centre in London, UK, where 12 infusion chairs were deployed for 170 non-MS and 860 MS patients as of March 2021. The number of MS patients was projected to increase by seven new patients per week. RESULTS: The model-estimated waiting time for an infusion is, on average, 8 days beyond clinical recommendation in the first year of simulation. Without corrective action, the delay in receiving due treatment is anticipated to reach 30 days on average at 30 months from the start of simulation. Such system compromise can be prevented either by adding one infusion chair annually or switching 7% of existing patients or 24% of new patients to alternative MS treatments not requiring infusion. CONCLUSION: ENTIMOS is a flexible model of patient flow and care delivery in infusion centres serving MS patients. It allows users to simulate specific local settings and therefore identify measures that are necessary to avoid clinically significant treatment delay resulting in suboptimal care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40258-022-00733-0. |
format | Online Article Text |
id | pubmed-9117085 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-91170852022-05-19 ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients Lacinova, Kristyna Thokala, Praveen Nicholas, Richard Dobay, Pamela Scalfaro, Erik Angehrn, Zuzanna Brennan, Roisin Boer, Ibolya Lines, Carol Adlard, Nicholas Appl Health Econ Health Policy Original Research Article BACKGROUND: Improved multiple sclerosis (MS) diagnosis and increased availability of intravenous disease-modifying treatments can lead to overburdening of infusion centres. This study was focused on developing a decision-support tool to help infusion centres plan their operations. METHODS: A discrete event simulation model (‘ENTIMOS’) was developed using Simul8 software in collaboration with clinical experts. Model inputs included treatment-specific clinical parameters, resources such as infusion chairs and nursing staff, and costs, while model outputs included patient throughput, waiting time, queue size, resource utilisation, and costs. The model was parameterised using characteristics of the Charing Cross Hospital Infusion Centre in London, UK, where 12 infusion chairs were deployed for 170 non-MS and 860 MS patients as of March 2021. The number of MS patients was projected to increase by seven new patients per week. RESULTS: The model-estimated waiting time for an infusion is, on average, 8 days beyond clinical recommendation in the first year of simulation. Without corrective action, the delay in receiving due treatment is anticipated to reach 30 days on average at 30 months from the start of simulation. Such system compromise can be prevented either by adding one infusion chair annually or switching 7% of existing patients or 24% of new patients to alternative MS treatments not requiring infusion. CONCLUSION: ENTIMOS is a flexible model of patient flow and care delivery in infusion centres serving MS patients. It allows users to simulate specific local settings and therefore identify measures that are necessary to avoid clinically significant treatment delay resulting in suboptimal care. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40258-022-00733-0. Springer International Publishing 2022-05-19 2022 /pmc/articles/PMC9117085/ /pubmed/35585305 http://dx.doi.org/10.1007/s40258-022-00733-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial 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-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Article Lacinova, Kristyna Thokala, Praveen Nicholas, Richard Dobay, Pamela Scalfaro, Erik Angehrn, Zuzanna Brennan, Roisin Boer, Ibolya Lines, Carol Adlard, Nicholas ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients |
title | ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients |
title_full | ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients |
title_fullStr | ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients |
title_full_unstemmed | ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients |
title_short | ENTIMOS: A Discrete Event Simulation Model for Maximising Efficiency of Infusion Suites in Centres Treating Multiple Sclerosis Patients |
title_sort | entimos: a discrete event simulation model for maximising efficiency of infusion suites in centres treating multiple sclerosis patients |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117085/ https://www.ncbi.nlm.nih.gov/pubmed/35585305 http://dx.doi.org/10.1007/s40258-022-00733-0 |
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