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

• Published in: Health care management science Vol. 24; no. 3; pp. 640 - 660
• Main Authors: Bravo, Fernanda, Braun, Marcus, Farias, Vivek, Levi, Retsef, Lynch, Christine, Tumolo, John, Whyte, Richard
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.09.2021; Springer Nature B.V
• Subjects: Business and Management; Costs; Diagnosis-Related Groups; Econometrics; Health Administration; Health care access; Health Care Costs; Health care networks; Health Informatics; Humans; Linear programming; Management; Operations Research/Decision Theory; Optimization; Resource Allocation; United States > US; Cost allocation; Operations research; Health care delivery networks; Optimization; Resource allocation
• ISSN: 1386-9620; 1572-9389
• DOI: 10.1007/s10729-021-09565-1

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.