Estimating costs and benefits of stroke management: A population-based simulation model
dc.contributor.author | Bayer, S | |
dc.contributor.author | Eom, K | |
dc.contributor.author | Sivapragasam, N | |
dc.contributor.author | Silva, DAD | |
dc.contributor.author | Choon, G | |
dc.contributor.author | Koh, H | |
dc.contributor.author | Tan, KB | |
dc.contributor.author | Ansah, JP | |
dc.contributor.author | Matchar, DB | |
dc.date.accessioned | 2021-05-05T06:34:57Z | |
dc.date.available | 2021-05-05T06:34:57Z | |
dc.date.issued | 2020-01-01 | |
dc.date.updated | 2021-05-05T06:34:48Z | |
dc.description.abstract | The paper demonstrates how a system dynamics approach can support strategic planning of health care services and can in particular help to balance cost-effectiveness considerations with budget impact considerations when assessing a comprehensive package of stroke care interventions in Singapore. A population-level system dynamics model is used to investigate 12 intervention scenarios based on six stroke interventions (a public information campaign, thrombolysis, endovascular therapy, acute stroke unit (ASU), out-of-hospital rehabilitation, and secondary prevention). Primary outcomes included cumulative discounted costs and quality-adjusted life years (QALYs) gained, as well as cumulative net monetary benefit by 2030. All intervention scenarios result in an increase in net monetary benefit by 2030; much of these gains were realized through improved post-acute care. Findings highlight the importance of coordination of care, and affirms the economic value of current stroke interventions. | |
dc.identifier.issn | 0160-5682 | |
dc.identifier.issn | 1476-9360 | |
dc.identifier.uri | ||
dc.language | en | |
dc.publisher | Informa UK Limited | |
dc.relation.ispartof | Journal of the Operational Research Society | |
dc.relation.isversionof | 10.1080/01605682.2020.1772018 | |
dc.subject | System dynamics | |
dc.subject | stroke | |
dc.subject | health systems | |
dc.title | Estimating costs and benefits of stroke management: A population-based simulation model | |
dc.type | Journal article | |
duke.contributor.orcid | Matchar, DB|0000-0003-3020-2108 | |
pubs.begin-page | 1 | |
pubs.end-page | 13 | |
pubs.organisational-group | School of Medicine | |
pubs.organisational-group | Duke Clinical Research Institute | |
pubs.organisational-group | Duke Global Health Institute | |
pubs.organisational-group | Pathology | |
pubs.organisational-group | Medicine, General Internal Medicine | |
pubs.organisational-group | Duke | |
pubs.organisational-group | Institutes and Centers | |
pubs.organisational-group | University Institutes and Centers | |
pubs.organisational-group | Institutes and Provost's Academic Units | |
pubs.organisational-group | Clinical Science Departments | |
pubs.organisational-group | Medicine | |
pubs.publication-status | Published |
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