Optimization-driven framework to understand health care network costs and resource allocation

Fernanda Bravo (), Marcus Braun, Vivek Farias, Retsef Levi, Christine Lynch, John Tumolo and Richard Whyte
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Fernanda Bravo: UCLA Anderson School of Management
Marcus Braun: DataRobot
Vivek Farias: MIT, Sloan School of Management
Retsef Levi: MIT, Sloan School of Management
Christine Lynch: Beth Israel Deaconess Medical Center
John Tumolo: Beth Israel Deaconess Medical Center
Richard Whyte: Beth Israel Deaconess Medical Center

Health Care Management Science, 2021, vol. 24, issue 3, No 12, 640-660

Abstract: 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.

Keywords: Health care delivery networks; Resource allocation; Cost allocation; Optimization; Operations research (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10729-021-09565-1

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