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Issues And Trends In Healthcare Delivery System01:29

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Using Visual and Narrative Methods to Achieve Fair Process in Clinical Care
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Optimization-driven framework to understand health care network costs and resource allocation.

Fernanda Bravo1, Marcus Braun2, Vivek Farias3

  • 1UCLA Anderson School of Management, 110 Westwood Plaza, Gold Hall B411, Los Angeles, CA, 90095, USA. fernanda.bravo@anderson.ucla.edu.

Health Care Management Science
|May 4, 2021
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Summary
This summary is machine-generated.

Large healthcare networks face integration challenges. An optimization framework using linear programming improves understanding of network costs and resource allocation for better strategic decisions.

Keywords:
Cost allocationHealth care delivery networksOperations researchOptimizationResource allocation

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Area of Science:

  • Health Services Research
  • Operations Research
  • Healthcare Management

Background:

  • The U.S. healthcare industry has experienced significant consolidation, forming large delivery networks.
  • Integrating these networks presents challenges in strategic decision-making, resource allocation, and operational efficiency.
  • Traditional cost accounting methods are inadequate for managing complex multi-site healthcare networks.

Purpose of the Study:

  • To develop an optimization-driven framework for modeling healthcare network costs and operational constraints.
  • To address strategic challenges in resource allocation, capacity management, and case-mix definition within large healthcare networks.
  • To provide a methodological approach for improving the integration and efficiency of consolidated healthcare systems.

Main Methods:

  • Development of a general methodological framework based on linear programming.
  • Application of the framework to a network of hospitals to analyze network costs and trade-offs.
  • Modeling of operational constraints and resource allocation within a multi-site network.

Main Results:

  • The proposed framework enhances the understanding of network costs and operational trade-offs.
  • Demonstrated applicability in providing strategic insights for resource allocation and capacity decisions.
  • Identified limitations of traditional cost accounting in complex healthcare networks.

Conclusions:

  • An optimization-driven framework offers a superior approach to traditional cost accounting for healthcare network management.
  • The methodology provides strategic solutions for challenges in access, resource allocation, and operational efficiency.
  • Effective modeling is crucial for successful integration and strategic decision-making in consolidated healthcare systems.