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Inconsistent values and algorithmic fairness: a review of organ allocation priority systems in the United States

  • 0Department of Cardiothoracic Surgery, Stanford University School of Medicine, Center for Academic Medicine, 453 Quarry Road, Room 267, MC 5661, Stanford, CA, 94304, USA.
Bmc Medical Ethics +

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October 17, 2024

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October 17, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Current organ allocation scores prioritize model performance over ethical considerations, potentially leading to discrimination and hindering access for underserved populations. Standardization and transparency are needed for equitable organ distribution.

Area Of Science

  • Transplantation policy
  • Medical ethics
  • Health equity

Background

  • The Organ Procurement and Transplant Network (OPTN) Final Rule mandates equitable organ allocation using organ-specific priority stratification.
  • Current organ allocation scores primarily rely on mortality predictions.

Purpose Of The Study

  • To examine the alignment between ethical priorities and statistical design in organ prioritization systems.
  • To identify inconsistencies in ethical standards within US organ allocation scores.

Main Methods

  • Literature search of PubMed for organ allocation history, policy, and ethics in the United States.
  • Analysis of 127 relevant articles across kidney, liver, lung, and heart transplants.

Main Results

  • Current risk scores prioritize model performance, neglecting ethical concerns in variable selection (e.g., race, sex, geography).
  • Inconsistencies in ethical standards were found, including MELD exceptions, race in KDRI, geographical limits in LAS, and inadequate stratification in Heart Tier.
  • These issues create obstacles for medically underserved populations, blurring the line between evidence-based models and discrimination.

Conclusions

  • Efforts are needed to address statistical and ethical concerns in organ allocation models.
  • Standardization and transparency in policy development are crucial for ensuring fairness, equitability, and evidence-based risk predictions in organ transplantation.

Keywords:

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