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6/25/2024 11:51:38 AM | Browse: 227 | Download: 691
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Received |
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2024-03-08 01:54 |
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Peer-Review Started |
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2024-03-08 01:54 |
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First Decision by Editorial Office Director |
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2024-04-30 02:39 |
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Return for Revision |
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2024-04-30 02:39 |
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Revised |
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2024-05-12 17:47 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2024-05-27 02:46 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2024-05-27 08:15 |
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Articles in Press |
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2024-05-27 08:15 |
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Edit the Manuscript by Language Editor |
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2024-06-02 00:31 |
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Typeset the Manuscript |
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2024-06-12 00:39 |
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Publish the Manuscript Online |
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2024-06-25 09:25 |
| ISSN |
2222-0682 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Statistics & Probability |
| Manuscript Type |
Minireviews |
| Article Title |
Method “Monte Carlo” in healthcare
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Tsvetelina Velikova, Niya Mileva and Emilia Naseva |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria |
BG-RRP-2.004-0008 |
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| Corresponding Author |
Emilia Naseva, PhD, Senior Scientist, Faculty of Public Health “Prof. Tsekomir Vodenicharov, MD, Dsc”, Medical University of Sofia, 15 Acad. I. E. Geshov Blvd, Sofia 1431, Bulgaria. e.naseva@foz.mu-sofia.bg |
| Key Words |
Health economics; Statistical techniques; Stochastic methods; Decision analysis; Modeling; Healthcare; Simulation; Monte Carlo |
| Core Tip |
The potential of the Monte Carlo method in healthcare spreads across decision-making, risk analysis, and modeling- in healthcare. Emphasizing versatility, the method navigates uncertainties, offering insights for optimal resource allocation, cost-effectiveness evaluations, and strategic planning in the healthcare domain. The Monte Carlo technique could be demystified through clear illustrations and real-world examples, empowering practitioners to harness its power for robust analyses, enhancing decision accuracy, and contributing to improved healthcare strategies and outcomes. |
| Publish Date |
2024-06-25 09:25 |
| Citation |
Velikova T, Mileva N, Naseva E. Method “Monte Carlo” in healthcare. World J Methodol 2024; 14(3): 93930 |
| URL |
https://www.wjgnet.com/2222-0682/full/v14/i3/93930.htm |
| DOI |
https://dx.doi.org/10.5662/wjm.v14.i3.93930 |
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