Model-based approaches to decision making in healthcare delivery
dc.contributor | Aalto-yliopisto | fi |
dc.contributor | Aalto University | en |
dc.contributor.advisor | Flander, Louisa, Dr. Principal Fellow, University of Melbourne School of Population and Global Health, Australia | |
dc.contributor.author | Dillon, Mary | |
dc.contributor.department | Tieto ja palvelujohtamisen laitos | fi |
dc.contributor.department | Department of Information and Service Management | en |
dc.contributor.school | Kauppakorkeakoulu | fi |
dc.contributor.school | School of Business | en |
dc.contributor.supervisor | Vilkkumaa, Eeva, Assist. Prof., Aalto University School of Business, Department of Information and Service Management, Finland | |
dc.date.accessioned | 2024-05-11T09:00:14Z | |
dc.date.available | 2024-05-11T09:00:14Z | |
dc.date.defence | 2024-05-24 | |
dc.date.issued | 2024 | |
dc.description.abstract | Healthcare systems worldwide face escalating pressures from aging populations, advancements in pharmaceuticals and technologies, strained services, and economic constraints. Hence, robust decision-making processes are imperative to maximise population health. Mathematical modelling has proven to be a valuable tool for addressing such healthcare challenges. Recent experiences, exemplified by the COVID-19 pandemic, have demonstrated the effectiveness of mathematical modelling in decision-making in healthcare delivery. This thesis contributes to the advancement of model-based decision-making in healthcare with a focus on practical applicability. It leverages two healthcare domains, colorectal cancer screening and the blood supply chain, to illustrate the benefit of model-based approaches in improving costeffectiveness and resource utilisation in public healthcare delivery. One avenue for informed decision-making aimed at achieving an equitable, efficient, and high-quality healthcare system is health technology assessment; a process that employs analytical methods to evaluate the value of healthcare technologies or interventions throughout their life cycle. In this thesis, the long-term evaluation of appropriate modal of colorectal cancer screening practices and resource allocation is considered through cost-effectiveness analyses. Second, given that healthcare systems are inherently fraught with uncertainty, there exists a necessity for day-to-day decisions that remain robust in the face of the unknown. This thesis employs mathematical optimisation models to address decision-making under uncertainty, particularly within the management of blood inventories. Optimisation entails the selection of the decision alternatives to maximise a specified objective. Stochastic programming is utilised to incorporate uncertain blood demand into models that define optimal blood inventory policies. Optimisation is a powerful tool when decisions made today must remain valid into the future. In conclusion, this thesis underscores the role of model-based approaches in healthcare decisionmaking. By applying these approaches in the contexts of colorectal cancer screening and the blood supply chain, this research contributes to enhancing the efficiency, cost-effectiveness, and overall quality of public healthcare delivery. | en |
dc.format.extent | 46 + app. 72 | |
dc.format.mimetype | application/pdf | en |
dc.identifier.isbn | 978-952-64-1790-5 (electronic) | |
dc.identifier.isbn | 978-952-64-1789-9 (printed) | |
dc.identifier.issn | 1799-4942 (electronic) | |
dc.identifier.issn | 1799-4934 (printed) | |
dc.identifier.issn | 1799-4934 (ISSN-L) | |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/127714 | |
dc.identifier.urn | URN:ISBN:978-952-64-1790-5 | |
dc.language.iso | en | en |
dc.opn | Morton, Alec, Prof., University of Strathclyde, UK | |
dc.publisher | Aalto University | en |
dc.publisher | Aalto-yliopisto | fi |
dc.relation.haspart | [Publication 1]: Dillon, M., Flander, L., Buchanan, D.D., Macrae, F.A., Emery, J.D., Winship, I.M., Boussioutas, A., Giles, G.G., Hopper, J.L., Jenkins, M.A. and Ait Ouakrim, D. Family history-based colorectal cancer screening in Australia: A modelling study of the costs, benefits, and harms of different participation scenarios. PLoS medicine, 15(8), p.e1002630, 2018. DOI: 10.1371/journal.pmed.1002630 | |
dc.relation.haspart | [Publication 2]: Dillon, M. Planning for the next pandemic: The Finnish colorectal cancer screening programme. In European Decision Science Institute Conference, Dublin, 14 pages, May 2022. | |
dc.relation.haspart | [Publication 3]: Dillon, M., Oliveira, F. and Abbasi, B. A two-stage stochastic programming model for inventory management in the blood supply chain. International Journal of Production Economics, 187, 27-41, 2017. DOI: 10.1016/j.ijpe.2017.02.006 | |
dc.relation.haspart | [Publication 4]: Dillon, M., Vauhkonen, I., Arvas, M., Ihalainen, J., Vilkkumaa, E., Oliveira, F. Supporting platelet inventory management decisions: What is the effect of extending platelets’ shelf life. European Journal of Operational Research, 310(2), 640–654, 2023. Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202308114678. DOI: 10.1016/j.ejor.2023.03.007 | |
dc.relation.ispartofseries | Aalto University publication series DOCTORAL THESES | en |
dc.relation.ispartofseries | 89/2024 | |
dc.rev | Morton, Alec, Prof., University of Strathclyde, UK | |
dc.rev | Gutjahr, Walter, Prof., University of Vienna, Austria | |
dc.subject.keyword | optimisation | en |
dc.subject.keyword | stochastic programming | en |
dc.subject.keyword | health economics | en |
dc.subject.keyword | decision support | en |
dc.subject.other | Management | en |
dc.title | Model-based approaches to decision making in healthcare delivery | en |
dc.type | G5 Artikkeliväitöskirja | fi |
dc.type.dcmitype | text | en |
dc.type.ontasot | Doctoral dissertation (article-based) | en |
dc.type.ontasot | Väitöskirja (artikkeli) | fi |
local.aalto.acrisexportstatus | checked 2024-05-27_1445 | |
local.aalto.archive | yes | |
local.aalto.formfolder | 2024_05_10_klo_14_14 | |
local.aalto.infra | Science-IT |
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