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Optimization-driven framework to understand health care network costs and resource allocation
In the last several decades, the U.S. Health care industry has undergone a massive consolidation process that has resulted in the formation of large delivery networks. However, the integration of these networks into a unified operational system faces several challenges. Strategic problems, such as e...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8354985/ https://www.ncbi.nlm.nih.gov/pubmed/33942227 http://dx.doi.org/10.1007/s10729-021-09565-1 |
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author | Bravo, Fernanda Braun, Marcus Farias, Vivek Levi, Retsef Lynch, Christine Tumolo, John Whyte, Richard |
author_facet | Bravo, Fernanda Braun, Marcus Farias, Vivek Levi, Retsef Lynch, Christine Tumolo, John Whyte, Richard |
author_sort | Bravo, Fernanda |
collection | PubMed |
description | In the last several decades, the U.S. Health care industry has undergone a massive consolidation process that has resulted in the formation of large delivery networks. However, the integration of these networks into a unified operational system faces several challenges. Strategic problems, such as ensuring access, allocating resources and capacity efficiently, and defining case-mix in a multi-site network, require the correct modeling of network costs, network trade-offs, and operational constraints. Unfortunately, traditional practices related to cost accounting, specifically the allocation of overhead and labor cost to activities as a way to account for the consumption of resources, are not suitable for addressing these challenges; they confound resource allocation and network building capacity decisions. We develop a general methodological optimization-driven framework based on linear programming that allows us to better understand network costs and provide strategic solutions to the aforementioned problems. We work in collaboration with a network of hospitals to demonstrate our framework applicability and important insights derived from it. |
format | Online Article Text |
id | pubmed-8354985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-83549852021-08-25 Optimization-driven framework to understand health care network costs and resource allocation Bravo, Fernanda Braun, Marcus Farias, Vivek Levi, Retsef Lynch, Christine Tumolo, John Whyte, Richard Health Care Manag Sci Article In the last several decades, the U.S. Health care industry has undergone a massive consolidation process that has resulted in the formation of large delivery networks. However, the integration of these networks into a unified operational system faces several challenges. Strategic problems, such as ensuring access, allocating resources and capacity efficiently, and defining case-mix in a multi-site network, require the correct modeling of network costs, network trade-offs, and operational constraints. Unfortunately, traditional practices related to cost accounting, specifically the allocation of overhead and labor cost to activities as a way to account for the consumption of resources, are not suitable for addressing these challenges; they confound resource allocation and network building capacity decisions. We develop a general methodological optimization-driven framework based on linear programming that allows us to better understand network costs and provide strategic solutions to the aforementioned problems. We work in collaboration with a network of hospitals to demonstrate our framework applicability and important insights derived from it. Springer US 2021-05-03 2021 /pmc/articles/PMC8354985/ /pubmed/33942227 http://dx.doi.org/10.1007/s10729-021-09565-1 Text en © The Author(s) 2021 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/) . |
spellingShingle | Article Bravo, Fernanda Braun, Marcus Farias, Vivek Levi, Retsef Lynch, Christine Tumolo, John Whyte, Richard Optimization-driven framework to understand health care network costs and resource allocation |
title | Optimization-driven framework to understand health care network costs and resource allocation |
title_full | Optimization-driven framework to understand health care network costs and resource allocation |
title_fullStr | Optimization-driven framework to understand health care network costs and resource allocation |
title_full_unstemmed | Optimization-driven framework to understand health care network costs and resource allocation |
title_short | Optimization-driven framework to understand health care network costs and resource allocation |
title_sort | optimization-driven framework to understand health care network costs and resource allocation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8354985/ https://www.ncbi.nlm.nih.gov/pubmed/33942227 http://dx.doi.org/10.1007/s10729-021-09565-1 |
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