Optimization-driven framework to understand health care network costs and resource allocation
Abstract 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. Strateg...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer US
2021
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| Online Access: | https://hdl.handle.net/1721.1/133156 |
| _version_ | 1826196268602359808 |
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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 | MIT |
| description | Abstract
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. |
| first_indexed | 2024-09-23T10:24:13Z |
| format | Article |
| id | mit-1721.1/133156 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:24:13Z |
| publishDate | 2021 |
| publisher | Springer US |
| record_format | dspace |
| spelling | mit-1721.1/1331562021-11-01T14:36:56Z 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 Abstract 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. 2021-10-27T16:37:27Z 2021-10-27T16:37:27Z 2021-05-03 2021-05-09T03:11:16Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/133156 Bravo, Fernanda, Braun, Marcus, Farias, Vivek, Levi, Retsef, Lynch, Christine et al. 2021. "Optimization-driven framework to understand health care network costs and resource allocation." PUBLISHER_CC en https://doi.org/10.1007/s10729-021-09565-1 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer US Springer US |
| spellingShingle | 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 |
| url | https://hdl.handle.net/1721.1/133156 |
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