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A decision support tool with health economic modelling for better management of DVT patients
BACKGROUND: Responding to the increasing demand for Deep Vein Thrombosis (DVT) treatment in the United Kingdom (UK) at times of limited budgets and resources is a great challenge for decision-makers. Therefore, there is a need to find innovative policies, which improve operational efficiency and ach...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790817/ https://www.ncbi.nlm.nih.gov/pubmed/36567380 http://dx.doi.org/10.1186/s13561-022-00412-9 |
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author | Lebcir, Reda Yakutcan, Usame Demir, Eren |
author_facet | Lebcir, Reda Yakutcan, Usame Demir, Eren |
author_sort | Lebcir, Reda |
collection | PubMed |
description | BACKGROUND: Responding to the increasing demand for Deep Vein Thrombosis (DVT) treatment in the United Kingdom (UK) at times of limited budgets and resources is a great challenge for decision-makers. Therefore, there is a need to find innovative policies, which improve operational efficiency and achieve the best value for money for patients. This study aims to develop a Decision Support Tool (DST) that assesses the impact of implementing new DVT patients’ management and care policies aiming at improving efficiency, reducing costs, and enhancing value for money. METHODS: With the involvement of stakeholders from a number of DVT services in the UK, we developed a DST combining discrete event simulation (DES) for DVT pathways and the Socio Technical Allocation of Resources (STAR) approach, an agile health economics technique. The model was inputted with data from the literature, local datasets from DVT services, and interviews conducted with DVT specialists. The tool was validated and verified by various stakeholders and two policies, namely shifting more patients to community services (CSs) and increasing the usage of the Novel Oral Anticoagulant (NOAC) drug were selected for testing on the model. RESULTS: Sixteen possible scenarios were run on the model for a period of 5 years and generated treatment activity, human resources, costing, and value for money outputs. The results indicated that hospital visits can be reduced by up to 50%. Human resources’ usage can be greatly lowered driven mainly by offering NOAC treatment to more patients. Also, combining both policies can lead to cost savings of up to 50%. The STAR method, which considers both service and patient perspectives, produced findings that implementing both policies provide a significantly higher value for money compared to the situation when neither is applied. CONCLUSIONS: The combination of DES and STAR can help decision-makers determine the interventions that have the highest benefits from service providers' and patients’ perspectives. This is important given the mismatch between care demand and resources and the resulting need for improving operational and economic outcomes. The DST tool has the potential to inform policymaking in DVT services in the UK to improve performance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13561-022-00412-9. |
format | Online Article Text |
id | pubmed-9790817 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-97908172022-12-27 A decision support tool with health economic modelling for better management of DVT patients Lebcir, Reda Yakutcan, Usame Demir, Eren Health Econ Rev Research BACKGROUND: Responding to the increasing demand for Deep Vein Thrombosis (DVT) treatment in the United Kingdom (UK) at times of limited budgets and resources is a great challenge for decision-makers. Therefore, there is a need to find innovative policies, which improve operational efficiency and achieve the best value for money for patients. This study aims to develop a Decision Support Tool (DST) that assesses the impact of implementing new DVT patients’ management and care policies aiming at improving efficiency, reducing costs, and enhancing value for money. METHODS: With the involvement of stakeholders from a number of DVT services in the UK, we developed a DST combining discrete event simulation (DES) for DVT pathways and the Socio Technical Allocation of Resources (STAR) approach, an agile health economics technique. The model was inputted with data from the literature, local datasets from DVT services, and interviews conducted with DVT specialists. The tool was validated and verified by various stakeholders and two policies, namely shifting more patients to community services (CSs) and increasing the usage of the Novel Oral Anticoagulant (NOAC) drug were selected for testing on the model. RESULTS: Sixteen possible scenarios were run on the model for a period of 5 years and generated treatment activity, human resources, costing, and value for money outputs. The results indicated that hospital visits can be reduced by up to 50%. Human resources’ usage can be greatly lowered driven mainly by offering NOAC treatment to more patients. Also, combining both policies can lead to cost savings of up to 50%. The STAR method, which considers both service and patient perspectives, produced findings that implementing both policies provide a significantly higher value for money compared to the situation when neither is applied. CONCLUSIONS: The combination of DES and STAR can help decision-makers determine the interventions that have the highest benefits from service providers' and patients’ perspectives. This is important given the mismatch between care demand and resources and the resulting need for improving operational and economic outcomes. The DST tool has the potential to inform policymaking in DVT services in the UK to improve performance. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13561-022-00412-9. Springer Berlin Heidelberg 2022-12-26 /pmc/articles/PMC9790817/ /pubmed/36567380 http://dx.doi.org/10.1186/s13561-022-00412-9 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 Lebcir, Reda Yakutcan, Usame Demir, Eren A decision support tool with health economic modelling for better management of DVT patients |
title | A decision support tool with health economic modelling for better management of DVT patients |
title_full | A decision support tool with health economic modelling for better management of DVT patients |
title_fullStr | A decision support tool with health economic modelling for better management of DVT patients |
title_full_unstemmed | A decision support tool with health economic modelling for better management of DVT patients |
title_short | A decision support tool with health economic modelling for better management of DVT patients |
title_sort | decision support tool with health economic modelling for better management of dvt patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9790817/ https://www.ncbi.nlm.nih.gov/pubmed/36567380 http://dx.doi.org/10.1186/s13561-022-00412-9 |
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