Ensuring Equitable Access to Liver Transplant Using Linear Programming Duality, Network Flow, and Simulation

Abstract

Donor livers are allocated via the Model for End-Stage Liver Disease (MELD) score. Women are consistently 4.8 less likely to receive a liver transplant than men. Women are disadvantaged by their smaller abdominal cavities which cannot accommodate larger donated livers. They are also disadvantaged by lower natural creatinine levels, a waste product correlated with liver disease. We proposed increasing female MELD scores to reach an equitable allocation of livers. To decide how many points should be added, we created a linear program to model liver allocation. This linear program used transplant data to test how total MELD points and total number of lives saved changes when a new constraint to enforce equity is introduced. Next, we used the linear programming duality theorem to calculate how many points should be added to female MELD scores. We then designed a network flow model to capture the size incompatibilities that women face when they are only able to accept small livers. We used data analysis to decide how to restrict the flow of livers between small donors and large patients and created new allocation rules reserving smaller livers for smaller patients to equalize the rate of transplant between all size groups.

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Document Details

Document Type
Technical Report
Publication Date
May 16, 2022
Accession Number
AD1171883

Entities

People

  • Sarah G. Sorensen

Organizations

  • United States Naval Academy

Tags

DTIC Thesaurus Topics

  • Abdomen
  • Abstracts
  • Algorithms
  • Blood Groups
  • Boundaries
  • Creatinine
  • Diseases And Disorders
  • Health
  • Health Care
  • Health Care Management
  • Health Services
  • Linear Programming
  • Liver Diseases
  • Operations Research
  • Optimization
  • Procurement
  • Transplantation
  • Transplants
  • United States
  • United States Naval Academy

Readers

  • Oncology
  • Operations Research
  • Toxicology/Environmental Toxicology

Technology Areas

  • Biotechnology